Medical knowledge | Infectology » Scientometric Mapping of Virology Research, A Global Perspective

Source: http://www.doksinet SCIENTOMETRIC MAPPING OF VIROLOGY RESEARCH: A GLOBAL PERSPECTIVE A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF PHILOSOPHY IN LIBRARY AND INFORMATION SCIENCE Submitted by P.MURUGESAN Reg. No: 2K10FT-LIS03 Research Supervisor DR.M SURULINATHI DEPARTMENT OF LIBRARY AND INFORMATION SCIENCE BHARATHIDASAN UNIVERSITY TIRUCHIRAPPALLI – 620 024 TAMIL NADU AUGUST - 2013 Source: http://www.doksinet DECLARATION I hereby declare that the dissertation entitled “SCIENTOMETRICMAPPING OF VIROLOGY RESEARCH: A GLOBAL PERSPECTIVE”, which is being submitted in partial fulfillment of requirements for the award of Master of Philosophy in Library and Information Science, is the result of the work carried out by me under the guidance and the supervision of Dr. M Surulinathi, Assistant Professor, Department of Library and Information Science, Bharathidasan University. I further declare that this dissertation has not

been previously submitted to any other institution / university for any degree / diploma by any one. Place: Tiruchirappalli Date: (P.MURUGESAN) Source: http://www.doksinet CERTIFICATE This is to certify that the dissertation entitled “SCIENTOMETRICMAPPING OF VIROLOGY RESEARCH: A GLOBAL PERSPECTIVE”,submitted in partial fulfillment of the requirements for the degree of Master of Philosophy in Library and Information Science, Bharathidasan University is a record of Bonafide research work carried out by P.MURUGESAN, (Reg No: 2K10FT-LIS03) Part Time Scholar under my supervision and guidance and no part of this work has been submitted for the award of any degree, diploma, associate ship, fellowship or any other similar title. . Dr.M SURULINATHI Assistant Professor Dept. of Library and Information Science Bharathidasan University Tiruchirappalli – 620 024. Dr. S SRINIVASARAGAVAN Librarian, Professor & Head Department of Library and Information Science Bharathidasan

University Tiruchirappalli – 620 024. Source: http://www.doksinet ACKNOWLEDGEMENT I am thankful to the Almighty for his blessings bestowed on me in all my endeavors. I am grateful to my guide Dr. M Surulinathi, Assistant Professor, Bharathidasan University for his guidance, encouragement and inducement for having lend his valuable time and expertise modeling my research work, with extreme patience and offering valuable comments and guidance from the beginning to the end of this endeavor. I express my heartfelt thanks to Dr. S Srinivasa Ragavan, Librarian, Professor & Head, Dept. of Library & Information Science, Bharathidasan University for providing me opportunity and necessary facilities for research work and for his kind help to complete this research work successfully. I also thank the other faculty members Dr. C Ranganathan, Dr N Amsaveni, Dr. R Balasubramani and DrBJeyapragash for their timely help I also acknowledge the Technical Officer B. Neelakandan and others of

the library for their support I express my sincere thanks to my parents and brother and my husband who helped and supported me in all my endeavors. Last but not least I extend my heartfelt thanks to my friends. (P.Murugesan) Source: http://www.doksinet CONTENTS CHAPTER CONTENTS PAGE NO. I INTRODUCTION 1 II REVIEW OF LITERATURE 39 III RESEARCH DESIGN 62 IV ANALYSIS AND INTERPRETATION 65 V FINDINGS AND CONCLUSION 102 BIBLIOGRAPHY 105 Source: http://www.doksinet LIST OF ABBREVIATIONS GCS Global Citation Score shows the total number of citations to a paper in the Web of Science. LCR Local Cited References shows the number of citations in a papers reference list to other papers within the collection LCS Local Citation Score shows the count of citations to a paper within the collection NCR Number of Cited References shows the number of cited references in the papers bibliography. Recs Number of Records shows the number of records where a given item is

found. TLCS Total Local Citation Score TLCS/t Total Local Citation Score per year TGCS Total Global Citation Score TGCS/t Total Global Citation Score per year TLCR Total Local Cited Reference TLCSb Total Local Citation Score beginning TLCSe Total Local Citation Score end Source: http://www.doksinet LIST OF TABLES SI.NO PARTICULARS PAGE NO 1 Year wise Distribution of Publications 65 2 Document wise Distribution of Publications 68 3 Single Vs Multiple-Authors 69 4 Authorship Pattern 70 5 Ranking of Authors (Productivity of Authors) 71 6 Journal wise Distribution of Publications 75 7 Keyword wise Distribution of Publications 80 8 Institution wise Distribution of Publications 83 9 Country wise Distribution of Publications 85 10 Top 50 Highly Cited Papers 98 Source: http://www.doksinet LIST OF FIGURES S.NO PARTICULARS PAGE NO 1 Year wise Distribution of Publications 66 2 Document wise Distribution of Publications 68 3 Single Vs

Multiple-Authors 69 4 Authorship Pattern 70 5 Historiograph by top 100 GCS 95 6 Published items in each year 96 7 Citation in each year 96 8 Citation map of Highly cited paper 101 Source: http://www.doksinet CHAPTER – I INTRODUCTION Concept of Virology: Historical Perspective Many viruses have co-evolved with mammals and other animals over long periods of time. Examples of such viruses are herpesviruses, which have been traced back to fish and birds, as well as mammals. It is thought that herpesviruses have existed for two hundred million years or longer, and that they have infected humans since the early times of our speciation. Other viruses have entered human populations only recently, due to changes in agriculture (use of domestic animals), population dynamics (urbanization), migration of populations, commerce and changes in the environment. Examples of these agents include measles virus and HIV-1. Vaccines Attempts to control smallpox have existed for

almost one thousand years. The early method was called variolation, and involved the Source: http://www.doksinet inoculation of healthy individuals with material from a smallpox pustule, by scratching of the arm. This crude method was effective, but was accompanied by serious side effects including disseminated skin lesions and even death in about 1% of cases. However, this was preferable to the very high fatality rate of the natural infection (25% or so, and more in children). The concept of vaccination (vacca = cow) arose in the 1790s, when Jenner made the observation that milk maids exposed to cowpox were protected against smallpox. Jenner showed that the deliberate inoculation of a boy with cowpox virus resulted in protection from smallpox. The cowpox vaccine was propagated for many years in humans, before being grown in animals, but at some point the cowpox virus unknowingly became replaced by the virus now known as vaccinia. Vaccinia virus has been found in “cowpox”

vaccines dating from the 1870s, and it is not clear how the virus arose – although it may have arisen in horses. Source: http://www.doksinet The derivation of deliberately attenuated vaccines did not occur until the work of Pasteur in the 1880s, who serially passaged rabies virus in rabbits in order to derive a weakened (attenuated) strain that still elicited protective immunity but which failed to cause disease. Discovery of viruses In the 1890s, scientists discovered that the agent which caused tobacco mosaic disease was a filterable agent smaller than bacteria. By the early 1900s, additional viruses had been identified, including viruses which caused tumors in chickens (e.g, the Rous sarcoma virus) as well as yellow fever virus (the first human virus to be discovered, in 1901). Definitive Properties of Viruses Perhaps the defining single feature of viruses is that they are obligate intracellular molecular parasites. A more complete list of the defining properties of viruses

is as follows: 1. Viruses are obligate intracellular molecular parasites, which are very small and infectious. 2. The virus genome is composed either of DNA or RNA 3. The virus genome directs the synthesis of virion components within an appropriate host cell. 4. Progeny virus particles are produced by the assembly of newly made viral components. 5. Progeny virus particles spread infection to new cells Size of viruses Source: http://www.doksinet Classification of Viruses Classical virus classification schemes have been based on the consideration of four major properties of viruses: 1. The type of nucleic acid which is found in the virion (RNA or DNA) 2. The symmetry and shape of the capsid 3. The presence or absence of an envelope 4. The size of the virus particle More recent classification systems adopted by the International Committee on Viral Taxonomy (ICTV) have really emphasized the viral genome as the primary determinant for viral taxonomy. Furthermore, there is a drift

towards the use of genomics for virus classification – that is sequence analysis of the viral genome, and comparison to other known viral sequences. The naming system for viruses that has been adopted by the ICTV is very useful for animal viruses, and is widely used. Latinized virus family names start with capital letters and end with the suffix –viridae (e.g, Herpesviridae) These formal names are often used interchangably with the common names for viruses (e.g, herpesviruses) Levels of taxonomy Taxonomic level Suffix (comment) Example Order -virales (a group of related families) Mononegavirales Family -viridae Paramyxoviridae Subfamily -virinae Paramyxovirinae Genus -virus Morbillivirus Species (an individual virus) Measles virus Source: http://www.doksinet Baltimore System for Virus Classification The Baltimore system for virus classification is a system of classification which complements the ICTV classification system. It is especially useful for

understanding viral replication strategies and will be discussed later. Genetic Content of Viruses DNA viruses: Almost all DNA viruses which infect animals contain double-stranded DNA. Exceptions include the Parvoviridae (e.g, parvovirus B19, adeno-associated virus) and the Circoviridae (these include the recently discovered TT virus, which may be related to the development of some cases of hepatitis). RNA viruses: Almost all RNA viruses contain single-stranded RNA. Exceptions include the Reoviridae (e.g, rotaviruses) which contain double-stranded RNA Other RNA viruses can be broadly subdivided as follows: • Viruses with positive strand (+) RNA genomes – i.e, genomes of the same polarity as mRNA. Viruses in this category include picornaviruses and caliciviruses. In addition, retroviruses contain two copies of +RNA, although they replicate by a unique mechanism. • Viruses with negative strand (-) RNA genomes – i.e, genomes of opposite polarity to mRNA. Viruses in this

category all have helical capsids. Three members of the class are sufficiently closely related to comprise a distinct taxonomic order – the Mononegavirales (rhadboviruses, paramyxoviruses and filoviruses). The other (-) strand Source: http://www.doksinet RNA viruses have segmented genomes (orthomyxoviruses have 8 segments while arenaviruses and bunyaviruses have either two or three segments, respectively. The arenaviruses and some bunyaviruses are also unique in that they possess ambisense genomes (i.e, their genomes contain both (+) and (-) strand RNAs). PhysicoChemical Properties Capsid (sometimes refered to as nucleocapsid): This is the protective protein shell surrounding the viral genome. Capsids are typically formed from a small number of protein subunits, which are assembled into repeating, symmetrical structures. The major classes of capsid symmetry are (1) helical (rod-like) and (2) icosahedral (sphere-like). Virus structure will be discussed in greate r detail

later, but suffice to say that virus shapes and sizes are highly diverse. The size of the capsid will, in large measure, dictate the amount of genetic material which can be packaged into the virus particle. Envelope: Many animal viral envelopes are surrounded by a lipid bilayer, which is derived from the host cell membrane during the process of virus budding. These viral envelopes also contain virally-encoded proteins, which are often glycoproteins. These envelope proteins and glycoproteins often play a role in the processes of virus attachment and entry/uptake. Important: Envelopes are not present on all viruses, and that viruses which contain envelopes are usually less stable those that do not, e.g herpes-viruses, which do and polio and human papillomaviruses (wart viruses), which do not Source: http://www.doksinet Unifying Principles All viruses employ in order to survive: 1. All viruses package their genomes inside a particle to ensure transfer from host to host. 2. All viruses

can establish themselves in a host population, so as to ensure virus survival 3. The viral genome contains the information needed to initiate and complete an infectious cycle within a susceptible, permissive host cell. An infectious cycle includes attachment and entry/uptake, production of viral mRNA and proteins, genome replication and assembly and release of new particles. Study of Viruses Growing and maintaining viruses in the laboratory requires the ability to maintain cultures of cells which the virus can replicate itself in. In some cases, this is relatively easy to do, while in other cases (e.g, hepatitis C virus, human papillomaviruses) it can be quite difficult to get the virus to replicate in cell culture. The culture of animal cells typically involves the use of culture medium containing salts, amino acids, vitamins, glucose, antibiotics, buffers and, usually, blood serum which provides a source of necessary cellular growth factors. For some cells, defined serum-free media

have been developed, which contain specific growth factors, but in most cases, the addition of serum, with its complex mixture of nutritive factors, works best. Different cell types and cell lines have different media requirements. All animal cells derive ultimately from living tissue In some cases, these cells have been in culture for so long that they have long since ceased to resemble the tissue from which they were first isolated. Source: http://www.doksinet Continuous cell lines of this kind are very convenient because they grow well and can be used to generate large amounts of virus. However, continuous cell lines are not useful for examining the effects of virus infection on cellular processes, since these cell lines are so different from the cells which the virus might normally infect in vivo. Thus, to study the effects of virus infection on cellular metabolism, differentiation, function and survival it is often best to use primary cells. Cells with the properties of

transformed cells can also be generated from tumors. In general, tumor cells have a phenotype that is broadly similar to that of continuous cell lines. Typically, tumor cells will generate tumors in the original host species, although this ability can be lost upon extensive passage. Comparison of the properties of primary cells versus continuous cell lines or tumor cells Property Primary cells Continuous cell lines or tumor-derived cell lines Derivation Normal tissue Tumor tissue, or by exposure of primary cells to a mutagen or transforming agent Chromosomes Normal Aneuploid. Abnormal chromosomes, and/or altered chromosome numbers Lifespan Serum dependence Finite. After 5-20 generations, the Immortal. If fed, the cells will grow cells will senesce and die. forever. Require high amounts of serum to Need little serum. grow. Contact inhibition Cell growth is arrested when cells No contact inhibition of cell growth or touch each other. movement Anchorage Require

adherence to a solid support Grow in suspension dependence for growth (except for lymphoid cells) Differentiation state Fully differentiated De-differentiated Source: http://www.doksinet Reintroduction into Can reintroduce into the original host May cause tumors in the original host animals species without causing a tumor species Comparison of primary cells versus growth transformed cells and continuous cell lines LIBRAMETRY TO SCIENTOMETRICS Application of quantitative techniques to library and bibliographical work was until recently known as statistical bibliography. Witting (1978) stated that the term ‘statistical bibliography’ was traced and used by Hulme in 1923. Ranganathan (1948, 1969) announced the term ‘Librarmetry’ on the lines of biometry, econometry, and pschometry and illustrated with a few examples of the application of statistics to library science. Prof PC Mahalanobis, founder of the Indian Statistical Institute, Calcutta stated that the

statistics was the ‘key technology’ for all development and forecasting studies. The ‘bibliometric’ term was coined by Pritchard (1969) who described that bibliometrics was a simple statistical method of bibliography used to evaluate and quantify the growth of a subject. He also described the scope of the Librametry and defined Bibliometrics as the “statistical distribution of the processes relating to establish a theory for the structural aspects of a library”. Garfield (1970) indicated that proper bibliometric analysis could identify the present focus of scientific research. Ravichandra Rao (1981) stated that the information process and handling of information in libraries and information in libraries and information centres were done by quantitatively analyzing their characteristics and behaviour of documents by library staff and library users. The British Standards Institution defines ‘bibliometrics’ as the study of the use of documents and patterns of publications

in which mathematical and statistical methods have been applied. According to Howkins (1981) the term bibliometrics implied the “quantitative Source: http://www.doksinet analysis of the bibliographical features of the body of a literature”. More recently Sengupta (1973) has defined this term as the “organisation, classification and quantitative evolution of publication pattern of all micro and macro level communication along with the authorship pattern by mathematical and statistical calculus”. INFORMATRICS The most recent metric term ‘Informatrics’ which comes from German. In 1979, Nacke first proposed the word ‘informatrics’ and described as to cover all parts of information science, dealing with the measurement of information phenomenon and the application of mathematical methods to the discipline’s problems to parts of the information retrieval theory and bibliometrics. In the second international conference on ‘bibliometrics, scientometrics and

informatrics’ held at Canada, Hemalatha Iyer, (1987) pointed out that the late Prof. BC Brooke’s suggestion about the term ‘informatrics’ was most meaningful to represent bibliometrics, scientometrics and many other quantitative studies related to information science. In the third conference held at Bangalore, India in 1991, the term informatrics was used as a generic term and was described as “use and development of a variety of measures to study the several properties of information in general and documents in particular”. Obviously this covers bibliometrics and scientometrics. BIBLIOMETRICS Bibliometrics means literally "book measurement" but the term is used about all kinds of documents (with journal articles as the dominant kind of document). What are measured are not the physical properties of documents but statistical patterns in variables such as authorship, sources, subjects, geographical origins, and citations. Source: http://www.doksinet "The

definition and purpose of bibliometrics is to shed light on the process of written communications and of the nature and course of a discipline (in so far as this is displayed through written communication) by means of counting and analyzing the various facets of written communication. (Pritchard, 1969)" (Here quoted from Nicholas & Ritchie, 1978) Egghe & Rousseau (1990) write: "Historically, bibliometrics developed mainly in the West, and arose from statistical studies of bibliographies. Before the term "bibliometrics" was proposed by Pritchard (1969), the term "statistical bibliography" was in some use. According to Prichard (1969), it was Hulme (1923) who initiated the term "statistical bibliography". Hulme used the term to describe the process of illuminating the history of science and technology by counting documents. Pritchards timely proposal caught on immediately, but the content of the term remained somewhat of a problem

(Broadus, 1987). According to Prichard, bibliometrics means the application of mathematics and statistical methods to books and other communication media". Bibliometrics is particularly related to research in scientific communication. Schmidmaier (1984) discuss the history of bibliometrics and demonstrates its relation to the concept "the science of science", which is traced to lectures given by Carl Christian Friedrich Krause in 1829. In the former USSR was G M Dobrovs investigation of the science of science from 1966 a pioneer work. Cole and Eales, who analyzed books published between 1550 and 1860 with regards to developments in subject matter, published the first genuine bibliometric investigation in 1917. Source: http://www.doksinet Investigations by P. L K Gross in 1927 and H H Henkle in 1938 on biochemical literature together with later works by S. R Ranganathan (1969) and Solla Price (1976) belong to the foundational literature of bibliometrics (Ranganathan

proposed the term librametrics in 1948). In European information science journals bibliometric investigations began to be popular in the 1970ties and 1980ties. Hungary, Eastern Germany and Switzerland belong to the countries, which early started to do research in bibliometrics. Bibliometrics is an LIS research method. It is a quantitative study of the Literature on a topic and is used to identify patterns of publication, authorship, and secondary journal coverage to get an insight into the growth of knowledge on that topic. This leads to better organization of information resources which, is essential for effective and efficient use. Bibliometrics has attained a sophistication and complexity, and has a national, international, and interdisciplinary character. The present study focuses attention on the bibliometric analysis publication in the area of ecology. The term “Bibliometrics” was coined by Pritchard in 1969, and its practice can be traced back to the second decade of the

20th century. A very early example of a bibliometric study was a “statistical analysis of the literature” of comparative anatomy from 1543 to 1860, which counted books and journal article titles, and grouped them by countries of origin within periods. In 1923, Hulme conducted a study on the history of science. His analysis was based on the seventeen sections of the English International Catalogue of Scientific Literature. Source: http://www.doksinet A third study was the pioneering work of Gross and Gross, reported in 1927. They counted and analyzed the citations in articles in the Journal of the American Chemical Society, and produced a list of significant journals in chemical education. Another prominent work was Bradford (1934) on the distribution of lubrication research. This research formed the backbone of the theoretical foundation of the bibliometric study, known as the “Bradfords Law of Scattering.” Bibliometrics has been known by other names, including

“statistical analysis of the literature” (Cole and Eales 1917), while Hulme used the term “statistical bibliography” in 1923. In 1948, the great library scientist Dr. SR Ranganathan coined the term “librametry”, which referred to measurement used to streamline library services. “Bibliometrics” is analogous to Ranganathans librametrics, the Russian concept scientometrics, FIDs infometrics, and to some other well established sub-disciplines such as econometrics, psychometrics, sociometrics, biometrics, technometrics, chemometrics, and climetrics, where mathematics and statistics have been systematically applied to study and solve problems in a given field. The term “scientometrics” is currently used for the application of quantitative methods to the history of science, and obviously overlaps with bibliometrics to a considerable extent. Bibliometrics is a type of research method used in library and information science. It utilizes quantitative analysis and statistics

to describe patterns of publication within a given field or body of literature. Researchers may use bibliometric methods of evaluation to determine the influence of a single writer, for example, or to describe the relationship between two or more writers or works. One common way of conducting bibliometric research is to use the Social Science Citation Index, the Science Citation Index or the Arts and Humanities Citation Index to trace citations. Source: http://www.doksinet LAWS OF BIBLIOMETRICS One of the main areas in bibliometric research concerns the application of bibliometric laws. The three most commonly used laws in bibliometrics are: Lotkas Law of Scientific Productivity, Bradfords Law of Scatter, and Zipfs Law of Word Occurrence. LOTKA’S LAW Lotkas Law describes the frequency of publication by authors in a given field. It states that " . the number (of authors) making n contributions is about 1/n² of those making one; and the proportion of all contributors, that

make a single contribution, is about 60 percent" (Lotka 1926, cited in Potter 1988). This means that out of all the authors in a given field, 60 percent will have just one publication, and 15 percent will have two publications (1/2² times .60) 7 percent of authors will have three publications (1/3² times 60), and so on According to Lotkas Law of scientific productivity, only six percent of the authors in a field will produce more than 10 articles. Lotkas Law, when applied to large bodies of literature over a fairly long period of time, can be accurate in general, but not statistically exact. It is often used to estimate the frequency with which authors will appear in an online catalog (Potter 1988). BRADFORD’S LAW Bradfords Law serves as a general guideline to librarians in determining the number of core journals in any given field. It states that journals in a single field can be divided into three parts, each containing the same number of articles: 1) a core of journals on

the subject, relatively few in number, that produces approximately one-third of all the articles, 2) a second zone, containing the same number of articles as the first, but a greater number of journals, and 3) a third zone, containing the same number of articles as the second, but a still greater number Source: http://www.doksinet of journals. The mathematical relationship of the number of journals in the core to the first zone is a constant n and to the second zone the relationship is n². Bradford expressed this relationship as 1:n:n². Bradford formulated his law after studying a bibliography of geophysics, covering 326 journals in the field. He discovered that 9 journals contained 429 articles, 59 contained 499 articles, and 258 contained 404 articles. So it took 9 journals to contribute onethird of the articles, 5 times 9, or 45, to produce the next third, and 5 times 5 times 9, or 225, to produce the last third. As may be seen, Bradfords Law is not statistically accurate,

strictly speaking. But it is still commonly used as a general rule of thumb (Potter 1988). ZIPF’S LAW Zipfs Law is often used to predict the frequency of words within a text. The Law states that in a relatively lengthy text, if you "list the words occurring within that text in order of decreasing frequency, the rank of a word on that list multiplied by its frequency will equal a constant. The equation for this relationship is: r x f = k where r is the rank of the word, f is the frequency, and k is the constant (Potter 1988). Zipf illustrated his law with an analysis of James Joyces Ulysses. "He showed that the tenth most frequent word occurred 2,653 times, the hundredth most frequent word occurred 265 times, the two hundredth word occurred 133 times, and so on. Zipf found, then that the rank of the word multiplied by the frequency of the word equals a constant that is approximately 26,500" (Potter 1988). Zipfs Law, again, is not statistically perfect, but it is very

useful for indexers. CITATION ANALYSIS Source: http://www.doksinet Another major area of bibliometric research uses various methods of citation analysis in order to establish relationships between authors or their work. Here is a definition of citation analysis, and definitions of co-citation coupling and bibliographic coupling, which are specific kinds of citation analysis. When one author cites another author, a relationship is established Citation analysis uses citations in scholarly works to establish links. Many different links can be ascertained, such as links between authors, between scholarly works, between journals, between fields, or even between countries. Citations both from and to a certain document may be studied. One very common use of citation analysis is to determine counting the number of times the author has cited the impact of a single author on a given field by counting the number of times the author by others. One possible drawback of this approach is that

authors may be citing the single author in a negative context (saying that the author doesnt know what s/hes talking about, for instance) (Osareh 1996). CO-CITATION COUPLING Co-citation coupling is a method used to establish a subject similarity between two documents. If papers A and B are both cited by paper C, they may be said to be related to one another, even though they dont directly cite each other. If papers A and B are both cited by many other papers, they have a stronger relationship. The more papers they are cited by, the stronger their relationship is. BIBLIOGRAPHIC COUPLING Bibliographic coupling operates on a similar principle, but in a way it is the mirror image of co-citation coupling. Bibliographic coupling links two papers that cite the same articles, so that if papers A and B both cite paper C, they may be said to be related, even though Source: http://www.doksinet they dont directly cite each other. The more papers they both cite, the stronger their relationship

is. WEB APPLICATIONS OF BIBLIOMETRICS Recently, a new growth area in bibliometrics has been in the emerging field of webmetrics, or cybermetrics as it is often called. Webmetrics can be defined as using of bibliometric techniques in order to study the relationship of different sites on the World Wide Web. Such techniques may also be used to map out (called "scientific mapping" in traditional bibliometric research) areas of the Web that appear to be most useful or influential, based on the number of times they are hyperlinked to other Web sites. SCIENTOMETRICS Scientometrics is concerned with the quantitative features and characteristics of science and scientific research. Emphasis is placed on investigations in which the development and mechanism of science are studied by statistical mathematical methods. Scientometrics is the science of measuring and analysing science. In practice, scientometrics is often done using bibliometrics, which is a measurement of the impact of

(scientific) publications. Modern scientometrics is mostly based on the work of Derek J de Solla Price and Eugene Garfield. The latter founded the Institute for Scientific Information, which is heavily used for scientometric analysis. Methods of research include qualitative, quantitative and computational approaches. One significant finding in the field is a principle of cost escalation to the effect that achieving further findings at a given level of importance grow Source: http://www.doksinet exponentially more costly in the expenditure of effort and resources. Related fields are the history of science and technology, philosophy of science and sociology of scientific knowledge. Scientometrics--the quantitative study of scientific communication--challenges science and technology studies by demonstrating that organized knowledge production and control is amenable to measurement. Scientometrics isthe science of measuring and analysing science In practice, scientometrics is often

done using bibliometrics, which is a measurement of the impact of (scientific) publications. (Wikipedia) Scientometrics is the science of measuring and analyzing science. In practice, scientometrics is often done using bibliometrics that is measurement of (scientific) publications. Scientometrics means literally "measurement of science" In reality it means the application of statistical indicators (especially bibliometric indicators) as a mean for the evaluation of scientific productivity. "The term "scientometrics" (derived from the Russian "naukometria") was used mainly in the East and is defined as the study of the measurement of scientific and technological progress. This also explains the foundation in 1978 and the title of the journal Scientometrics in Hungary. For more information on the history and the contents of these names, we refer the reader to Egghe (1988f) . Scientometrics deals mainly with science policy applications . "

(Egghe & Rousseau, 1990) Source: http://www.doksinet Scientometrics is a discipline, which uses statistical and computational techniques in order to understand the structure and dynamics of science. Scientometrics is concerned with the quantitative features and characteristics of science and scientific research. Emphasis is placed on investigations Scientometrics is the science of measuring and analysing science. In practice, scientometrics is often done using bibliometrics, which is a measurement of the impact of scientific publications. Modern scientometrics is mostly based on the work of Derek J. de Solla Price and Eugene Garfield The latter founded the Institute for Scientific Information, which is heavily used for scientometric analysis. Methods of research include qualitative, quantitative and computational approaches One significant finding in the field is a principle of cost escalation to the effect that achieving further findings at a given level of importance

grow exponentially more costly in the expenditure of effort and resources. Related fields are the history of science and technology, philosophy of science and sociology of scientific knowledge. Journals in the field include Scientometrics and Journal of the American Society for Information Science and Technology. The International Society for Scientometrics and Infometrics founded in 1993 is an association of professionals in the field. Scientometrics are used to quantify scientific activities. Generally quantification of scientific activities is measurable by producing statistics on scientific publications indexed in indicator databases such as SCOPUS and ISI. Scientometric data can be useful to measure research collaborations among scientific environments and to monitor the evolution of special scientific subjects and fields. Also decision and policy-makers are going to be interested in scientometric indicators. Source: http://www.doksinet Scientometrics is “the study of the

measurement of scientific and technological progress” (Garfield, 1979). Its origin is in the quantitative study of science policy research, or the science of science, which focuses on a wide variety of quantitative measurements, or indicators, of science at large. Typically input and output of science programs correspond to two major categories of indicators. Input indicators include the amount of research grants awarded to institutions and the number of people receiving scientific degrees; output indicators include the number of scientific articles published, the number of citations to each article, and the number of patents granted. Science policy and program evaluation studies have used such indicators to measure the scientific strength of various countries, regions, or research institutions. Domain analysts have used such indicators to describe the intellectual structure of a knowledge domain. Scientometrics is the demographics of the worldwide scientific community. As Garfield

put it, “One can follow the growth or decline of various fields or identify where the action is.” Scientometrics is a branch of library and information science. Scientometric tools can be used to measure and compare the scientific activities at various levels of aggregation including institutions, sectors, provinces and countries. They can also be used to measure research collaborations, to map scientific networks and to monitor the evolution of scientific fields. Scientometric indicators give policy-makers objective, reproducible and therefore verifiable information that goes beyond the anecdotal. Scientometrics empirically describe the constantly changing relationship between science, technology and the research productivity. This consequently sheds more light on the structure of subject literature and better organization of information resources which can ultimately be effectively used for various purposes including regeneration of information. Source: http://www.doksinet

SCIENTOMETRIC INDICATORS Measuring scientific performance is both more complicated, and important, than it might seem at first. Various methods for measurement and comparison have been proposed, none of which are perfect. Measuring scientific productivity and its impact, through citation analysis, most often does evaluation of scientific work. Citation analysis includes measuring the number of citations, types of citations, self-citations (among authors, coauthors, institutions, countries or journals) and “independent” citations. In the evaluation of the status of author, institution or country, it is significant in which journals were the research results published, to what degree were they noticed and who noticed them and formalised that by citing. The status of the journal in which the research is published, as well as the status of the citing journal is some of frequently used indicators for evaluating individual scientists and institutions and are gained through the use of

impact factor (IF). However, to use IF in general, and so called standard or Garfield IF in particular, as a basic indicator for the evaluation of an institution or individuals work is to misunderstand its real meaning. Journal IF is a measure of a frequency with which an “average“ article was cited during a certain period of time. IF helps in evaluation of a journal’s quality. It is not to be used for evaluation of a single article, or of a single scientist A journal IF can potentially be an indirect measure for the value of an article, because we can suppose it has passed a strict review procedure, but the real value is gained a posteriori, through citation counts and its influence on the IF. As a scientometric indicator, h-index mainly serves for comparing scientists from the same disciplines and with similar work experience. The same can be said when using it for journals. Namely, two individuals with similar h-indices are comparable in terms of their overall scientific

impact, even if their total number of papers or citations is very different. Conversely, comparing two individuals (preferably of similar length of work experience in science) with a similar number of total papers, or of total citation count, and very different hvalues, the one with the higher h is likely to be the more accomplished scientist (1). According to Braun et al. (2) h-index combines the effect of “quantity” (number of publications) and “quality” (citation rate) in a rather specific, balanced way. Source: http://www.doksinet Could scientific Performance be measured? The methods that might spring to mind at first are: • Peer review. A good idea in principle, but it is subject to human nature so perceived performance will inevitably be affected by personal relationships. Also if a lesser-known scientist publishes a more eminent colleague published a groundbreaking publication he/she would likely get less recognition than if the same paper. • Number of articles

published. A long publication list tends to look good on your CV, but the number of articles published gives no indication of the impact that your publications have had on the field. A small number of publications that have been well heeded by colleagues in the field (i.e they are cited often) are better than a long list of publications cited poorly, or not at all. • Average number of citations per article published. So if it’s citations we are interested in, then surely the average number of citations per article is a better number to look at. Well, not really The average could be skewed greatly by one highly-cited article so does not allow a good comparison of overall performance Scientometric indicators are vital role in evaluation of scientific work of both, the individual author, and journal as a whole. Emphasis is put on the value and significance of a new scientometric indicators h-index, g-index, b-b index, Citation Map, Citation Report, SCImago Journal Rank (SJR),

Source Normalized Impact per Paper (SNIP), Clustering Analysis and so on. Source: http://www.doksinet H-INDEX Taking into account already mentioned facts; h-index is one of the indicators, which can help in evaluating scientific work of an individual scientist, institution, discipline, and journal. However, it should not be considered independently of the scientific discipline, the length of a scientist’s work experience, scientific productivity, co-authorships, the citation count, the types of citations and other relevant parameters. The h-index is based on a list of publications ranked in descending order by the Times Cited. The value of h is equal to the number of papers (N) in the list that have N or more citations. This metric is useful because it discounts the disproportionate weight of highly cited papers or papers that have not yet been cited. In the h-index example below, the h-index is 30 because there are 30 articles with 30 or more citations that appear above the green

line. Conceptually, the h-index is pretty simple. Researcher just plot papers versus the number of citations you (or someone else) have received and the h-index are the number of papers at which the 45degree line (citations=papers) intercepts the curve, as shown in the diagram, i.e h= the number of papers that have received at least h citations. Source: http://www.doksinet Calculating the h-index Value - The h-index factor is based on the depth of your Web of Science subscription and your selected time span. Items that do not appear on the Results page will not be factored into the calculation. If your subscription depth is 10 years, then the hindex value is based on this depth even though a particular author may have published articles more than 10 years ago. Moreover, the calculation only includes items in Web of Science books and articles in non-covered journals are not included The h-index was developed by JE Hirsch and published in Proceedings of the National Academy of

Sciences of the United States of America 102 (46): 16569-16572 November 15 2005. The h-index has been quickly adopted as the metric of choice for many committees and bodies. The advantage of the h-index is that it combines productivity (ie number of papers produced) and impact (number of citations) in a single number. So both productivity and impact are required for a high h index; neither a few highly cited papers nor a long list of papers with only a handful of (or no!) citations will yield a high h index. Source: http://www.doksinet G-INDEX The g-index is an index for quantifying scientific productivity based on publication record. It was suggested in 2006 by Leo Egghe The index is calculated based on the distribution of citations received by a given researchers publications. Given a set of articles ranked in decreasing order of the number of citations that they received, the g-index is the (unique) largest number such that the top g articles received (together) at least g2

citations. The g-index has been characterized in terms of three natural axioms by Woeginger (2008). The simplest of these three axioms states that by moving citations from weaker articles to stronger articles, ones research index should not decrease. The g-index is very similar to the h-index, and attempts to address its shortcomings. Like the h-index, the g-index is a natural number and thus lacks in discriminatory power. Therefore, Richard Tol proposed a rational generalisation. Tol also proposed a collective g-index. Given a set of researchers ranked in decreasing order of their g-index, the g 1 -index is the (unique) largest number such that the top g 1 researchers have on average at least a gindex of g 1 . H-B INDEX The h-b-index is an extension of the h-index suggested in 2005 by Jorge E. Hirsch of the University of California, San Diego to quantify the scientific productivity of physicists and other scientists based on their publication record. The h-b-index developed by Michael

Banks Source: http://www.doksinet of the Max Planck Institute for Solid State Research in Germany, takes the index further by evaluating the impact of compounds used in solid-state Physics and scientific topics in general. The h-b-index is defined in the same manner as the h-index, but is based on a topic (or compound) search instead of a scientist’s name. The h-index defined by J Hirsch is: A scientist has index h if h of his/her N p papers has at least h citations each, and the other (N p – h) papers have at most h citations each. For the case of a topic it is useful to define the h-b index in terms of the number of years, n as h = nm If the h-b index is linear with the number of years, then m is given as the gradient. In this respect, a compound or topic with a large m and h-b index can be defined as a hot topic. CLUSTER ANALYSIS Cluster analysis classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of interval variables.

The purpose of cluster analysis is to discover a system of organizing observations, usually people, into groups, where members of the groups share properties in common. It is cognitively easier for people to predict behavior or properties of people or objects based on group membership, all of whom share similar properties. It is generally cognitively difficult to deal with individuals and predict behavior or properties based on observations of other behaviors or properties. Source: http://www.doksinet Multivariate Statistics: Cluster Analysis Cluster Analysis is a multivariate analysis technique that seeks to organize information about variables so that relatively homogeneous groups, or "clusters," can be formed. The clusters formed with this family of methods should be highly internally homogenous (members are similar to one another) and highly externally heterogeneous (members are not like members of other clusters. Although cluster analysis is relatively simple, and can

use a variety of input data, it is a relatively new technique and is not supported by a comprehensive body of statistical literature. So, most of the guidelines for using cluster analysis are rules of thumb and some authors caution that researchers should use cluster analysis Cluster analysis methods will always produce a grouping. The groupings produced by cluster analysis may or may not prove useful for classifying objects. If the groupings discriminate between variables not used to do the grouping and those discriminations are useful, then cluster analysis is useful. For example, if grouping zip code areas into fifteen categories based on age, gender, education, and income discriminates between wine drinking behaviors, it would be very useful information if one were interested in expanding a wine store into new areas. Cluster analysis may be used in conjunction with discriminant function analysis. After multivariate data are collected, observations are grouped using cluster

analysis. Discriminant function analysis is then used on the resulting groups to discover the linear structure of either the measures used in the cluster analysis and/or different measures. Source: http://www.doksinet Cluster analysis methods are not clearly established. There are many options one may select when doing a cluster analysis using a statistical package. Cluster analysis is thus open to the criticism that a statistician may mine the data trying different methods of computing the proximities matrix and linking groups until he or she "discovers" the structure that he or she originally believed was contained in the data. One wonders why anyone would bother to do a cluster analysis for such a purpose. Historiographical Analysis Historiography is commonly defined as the "history of historical writing." A historiographical analysis, thus, has as its main objective to explore and explain the origins and development of historical texts and the ideas

presented in them. In this respect, historiography may be considered a branch of the wider field of intellectual history or the history of ideas. The importance of historiographical analysis The study of historiography is the basis of all historical work. Historians need to be aware and understand the works that have been produced in the past if they want to make significant contributions to their fields of study. Kinds of historiographical analysis There are many issues on which a historiographical analysis may concentrate. There are very general works on historiography that look at the history of the discipline as a whole. These works go from the ancient Greeks and Romans to present post-modern interpretations. They Source: http://www.doksinet look at histories produced in different parts of the world throughout different time periods. For example, Gilderhus, Mark T. History and Historians A Historiographical Introduction (1987) or Breisach, E. Historiography: Ancient, Medieval

and Modern (1994) There are also more specific works that concentrate on particular ideas, topics or time periods. CITATION MAP A Citation Map is a graphical representation that shows the citation relationships (cited references and citing articles) between a paper and other papers using various visualization tools and techniques. Using citation mapping, can analyze which researchers are citing your papers and also choose to organize and color code the results by author, year, journal title, subject category, and more. Researchers can also set up a graphical representation of the papers that you have cited in a published work and can then choose to organize and color code the results by author, year, journal title, subject category, and more. CITATION REPORT The Citation Report provides aggregate citation statistics for a set of search results. These statistics include:  The total number of times all items have been cited  The average number of times an item has been cited

The number of times an item has been cited each year JOURNAL ANALYZER The Scopus Journal Analyzer provides a quick, easy and transparent view of journal performance, now enriched with two journal metrics - SJR and SNIP also available at www.journalmetricscom Source: http://www.doksinet Using citations from nearly 18,000 titles from 5,000 international publishers, the Scopus Journal Analyzer gives editors, publishing teams, researchers and librarians quick, easy access to a transparent and objective overview of the journal landscape going back to 1996. The Scopus Journal Analyzer turns a laborious task into a simple comparison – leaving you with more time to analyze the results and make clear, informed decisions. Benefits Journal evaluation is becoming increasingly relevant within academic, government and corporate markets. All these user groups can benefit from the Scopus Journal Analyzer’s unique timesaving and comparative features. Editors/publishing teams: The Scopus

Journal Analyzer gives quick, easy access to an objective and transparent overview of the performance of your own and your competitors’ journals over time. This can help you analyze and manage journal portfolios more effectively, identify new growth areas, set out a strategy to increase performance or decide which journals you would like to be an editorial board member for. Researchers: The Scopus Journal Analyzer enables you to search for journals within a specific field, identify which are the most influential and find out who publishes them. This will help you to decide where to publish to get the best visibility for your work and how to prioritize your submissions. It can also help you to decide which journal you would like to review for publications. Librarians and information specialists: The Scopus Journal Analyzer enables you to search for all journals in a specific subject area and view their current details and performance over Source: http://www.doksinet time. This will

help you ensure you are only investing in the most influential and relevant journals. SNIP and SJR can also help you in your advisory role with your faculty to help them identify the most impactful Journals even in niche areas. The Scopus Journal Analyzer’s unique functionality provides you with five graphical representations of the journals: SCImago Journal Rank (SJR) is a measure of the scientific prestige of scholarly sources: value of weighted citations per document. A source transfers its own prestige, or status, to another source through the act of citing it. A citation from a source with a relatively high SJR is worth more than a citation from a source with a lower SJR. Source Normalized Impact per Paper (SNIP) measures contextual citation impact by weighting citations based on the total number of citations in a subject field. The impact of a single citation is given higher value in subject areas where citations are less likely, and vice versa. Citations displays the total

number of citations the selected journals receives over the course of each year % Not Cited provides the percentage of all documents that did not receive citations in that year. Percent Review provides a new metric to the Journal Analyzer, which represents the percentage of articles in a journal that are categorized as a review. In addition to often being titled as a review, review articles offer a concise synopsis of a subject or body of literature. Source: http://www.doksinet CHAPTER – II REVIEW OF LITERATURE This chapter devotes to examine the review of works relating to various aspects of Scientometric studies. It could be observed that there are various research studies highlighting the importance of Scientometric analysis and their applications to library management and Source: http://www.doksinet administration. This type of analysis enables the researcher to identify the research gap in the previous studies. Review of related studies further avoids the duplication

work that has already been done in that area. It also helps the researcher to study the different aspects of the problem It enables the researcher to identify the unexplored areas, in order to create new grounds for research. By considering this efficiency of various dimensions of Scientometric studies, the researcher has presented the literature on the basis of reverse chronological order. Bajwa, R. S, Yaldram, K, & Rafique, S (2013) have presented an analysed of the research trends in Pakistan in the field of nanoscience and nanotechnology. Starting with just seven publications in the year 2000, this number has steadily increased to 542 for the year 2011. Among the top 15 institutions with publications in nanotechnology 13 are universities and only two are R&D organizations. Almost 35 % of the research publications are in the field of material sciences followed by chemistry and physics in that order. The growth in the publications for period 2000-2011 is studied through

relative growth rate and doubling time. The authorship pattern is measured by different collaboration parameters, like collaborative index, degree of collaboration, collaboration coefficient and modified collaboration coefficient. Finally the quality of papers is assessed by means of the h-index, g-index, hg-index and pindex. 2012 Akadémiai Kiadó, Budapest, Hungary Alhaider, I., Ahmed, M K K, & Gupta, B M (2013) have aimed to study and analyse the global research output related to date palm based on a fact of its large consumption and production in Middle East. We analysed 1,376 papers obtained from SCOPUS database for Source: http://www.doksinet the period of 2000-11. The study examines major productive countries and their citation impact. We have also analysed inter-collaborative linkages, national priorities of date palm research, besides analysing the characteristics of its high productivity institutions, authors and journal. 2013 Akadémiai Kiadó, Budapest, Hungary

Date palm (Phoenix dactylifera) is one of the commonly used polyphenolic rich fruits attributing also to various therapeutic effect in different diseases and disorders. Shao, H., Yu, Q, Bo, X, & Duan, Z (2013) Over the past half-century, the incidence of tumours has increased, resulting in cancer becoming one of the most lethal diseases in humans. In the present study, we elucidated the status of oncology research from 2001 to 2010 Studies published in 30 representative oncology journals were retrieved from the Web of Science (2001-2010) to compose our dataset. Knowledge domain visualisation, co-citation analysis and social network analysis methods were used. By mapping the oncology research performed from 2001 to 2010, we identified the primary research centres, including the top 20 institutions and countries and the 4 major oncology research fronts: i) the mechanism of abnormal oncogene expression; ii) tumour metastasis and angiogenesis; iii) the relationship between cancer

cells and apoptosis; and iv) tumour vaccines. We also identified the 36 most collaborative academic communities, and multiple myeloma, angiogenesis and acute lymphocytic leukaemia were found to be the focuses of collaborative research in oncology from 2001 to 2010. Over the past 10 years, America has led oncology research, while China is the sole developing country to be ranked in the top 10. Analyses of the main research centres and forefronts may assist researchers in addressing these forefronts and ascertaining the developing trends in oncology. Analysis of the academic communities performing oncology research may Source: http://www.doksinet provide scientific evidence and suggestions for policymakers to select the most prolific academic groups and leaders and to effectively manage and finance future oncology research. Gupta, B. M, Kaur, H, & Kshitig, A (2012) have analysed the dementia research output from India during 2002-11 on different parameters including the growth,

global publications share, citation impact, share of international collaborative papers, contribution of major collaborative partner countries, contribution of various subject fields and by type of dementia, productivity and impact of most productive institutions and authors and patterns of research communication in most productive journals. SCOPUS Citation Database has been used to retrieve the data for 10 years (2002-11) by searching different relevant keywords in its combined title, abstract and keywords fields. Among the top 20 most productive countries in dementia research, India ranks 16th (with 1109 papers) with a global publication share of 1.24% and an annual average publication growth rate of 25.58% during 2002-11 Its global publication share has increased over the years, rising from 0.54% in 2002 to 220% during 2011 Its citation impact per paper was 5.11 during 2002-11, which decreased from 729 during 2002-06 to 433 during 2007-11. Its international collaborative

publications share was 2454% during 2002-11, which decreased from 28.57% during 2002-06 to 2307% during 2007-11 Indias publications efforts are quiet low considering that to 3.7 million people suffering from dementia in India It, therefore, needs to increase its output and bring about improvement in the quality of its research efforts. Indian medical and social research funding agencies must establish a more ambitious funding program into the causes, prevention, cure and care of dementia. At the national level, there is a need to have a consultation for evolving research strategies and for delineating specific directions to investigate the etiology, treatment and care provisions for persons involved in dementia. Source: http://www.doksinet Mulla (2012) has described the bibliometric analysis of 998 articles of on information science and scientometrics (ISS) that appeared in different journals during the period of 20052009. The study reveals that, most researchers preferred to

publish their research results in journals; as such 91.98% of articles were published in journals More numbers (329, 3297%) of articles were published in 2009. The authorship trend shows that, out of 1703 authors who contributed a total of 998 articles, out of which more number of (376, 40.96% ) articles were two authored papers. The degree of collaboration in ISS was 078, and the country wise contribution of articles, India would contribute more documents i.e, 8399% of the total publications. It also further examines year wise distribution of articles, distribution of types of documents, length of the papers, authorship pattern, degree of collaboration among authors, degree of collaboration among co-authors, degree of collaboration among different category of authors, rank wise distribution of collaborators, institution wise distribution of articles, country wise distribution of contributions, state wise distribution of contributions, journal wise distribution of articles.

Abolghassemi Fakhree. MA, and JouybanA (2011) described, scientometrics has become an important field of study to monitor the progresses in scientific performance of a research group, a department, a university etc. A number of scientometrical studies have been done about Iranian scientific outcome in recent years. But there is no comparison between major Iranian medical universities. In this study, by using Scopus as search engine, the scientific outcomes of the Iran University of Medical Sciences, Isfahan University of Medical Sciences, Mashhad University of Medical Sciences, Shahid Beheshti University of Medical Sciences, Shiraz University of Medical Sciences, Tabriz University of Medical Sciences, and Source: http://www.doksinet Tehran University of Medical Sciences have been compared with each other. These universities were compared by the number of published articles per year, number of citations received per year, number of citations received per year per article, total

H-indices, top ten authors, and top ten journals. The results of this study show that the order of the studied universities in research performance is as follow: Tehran > Shiraz = Shahid Beheshti > Isfahan = Iran > Tabriz = Mashhad universities of medical sciences. In addition, the data of Tehran University of Medical Sciences as the top medical university of Iran was compared with some of top medical universities around the world Cocosila M. Serenko, and A Turel (2011) examined the identity and development of the management information systems (MIS) field through a scientometric lens applied to three major global, regional and national conferences: International Conference on Information Systems (ICIS), Pacific Asia Conference on Information Systems (PACIS) and Administrative Sciences Association of Canada Annual Conference (ASAC). It adapts the conference stakeholder approach to the construction of the identity of the MIS discipline and analyzes the proceedings of these

three conferences. The findings suggest that the MIS field has been evolving in terms of collaborative research and scholarly output and has been gradually moving towards academic maturity. The leading MIS conference contributors tend to establish loyalty to a limited number of academic meetings. At the same time, relatively low levels of repeat publication in the proceedings of ICIS, PACIS and ASAC were observed. It was suggested that Lotkas and Yule-Simons bibliometric laws may be applied to measure and predict the degree of conference delegate loyalty. Source: http://www.doksinet Mahbuba. D, Rousseau R, and Srivastava D (2010) analysed a scientometric comparison between two health and population research organizations, namely the International Centre for Diarrhoeal Disease Research in Bangladesh (ICDDR,B) and the National Institute of Cholera and Enteric Diseases (NICED) in India, during the period 1979-2008. We study these two institutes because they conduct similar research and

because of their collaboration ties. Data are collected from the Web of Science (WoS) as well as from official records of these two organizations. The analysis presents the evolution of publication activities Special attention is given to research impact through time series of the institutional h- and R-indices, as well as to the trend in yearly citations received. Types of publications, international collaboration with other countries, top scientists and most cited articles co-authored by scientists from these institutions are highlighted. It is observed that female scientists play a minor role in these two institutes Varaprasad, S.JD Sahoo, S. and Madhusudhan, S. (2010) highlighted quantitatively the growth and development of chemical science research by J.S Yadav during the period from 1986-2009. During this period he has published 722 papers (702 research articles) in various domains. The data used was from Thomson/ISI Web of Science This study attempts to evaluate the

publications of J.S Yadav in relation to his contribution to the knowledge domain of chemical science and his role for the advancement of chemical science in India and elsewhere in a span of about two and half decades. His papers have been scattered in 56 high impact factor scientific journals. The percentage of collaborative work (997) was very high. His highest degree of collaboration 01925, was found during 2002-2003The h index of 41 after 24 years of scientific activity is a clear indication of his consistent publication productivity behaviour. Source: http://www.doksinet Alijani. R and Karman (2010) examined this survey is to identify the number of scientific papers written about stem cells by Iranian researchers. In this regard, to use the results for future stem cell research by Iranian scientists. In this survey we have used scientometric method as a single quantitative method. The statistical population of this article includes all articles published by Iranian researchers

from the earliest records until the end of 2007 as cited in the ISI database, which is the web based version of science citation index (SCI). The results show that Ghavamzadeh with 19 articles is the most productive Iranian researcher in the ISI database. More than one author has written the majority of published articles A review of the findings shows that Iranian researchers have been successful in stem cell production. Arbesman. Sa b, and Laughlin, G (2010) reviewed the search for a habitable extra solar planet has long interested scientists, but only recently have the tools become available to search for such planets. In the past decades, the number of known extra solar planets has ballooned into the hundreds, and with it, the expectation that the discovery of the first Earthlike extra solar planet is not far off. Here, we develop a novel metric of habitability for discovered planets and use this to arrive at a prediction for when the first habitable planet will be discovered.

Using a bootstrap analysis of currently discovered exoplanets, we predict the discovery of the first Earth-like planet to be announced in the first half of 2011, with the likeliest date being early May 2011. Our predictions, using only the properties of previously discovered exoplanets, accord well with external estimates for the discovery of the first potentially habitable extrasolar planet and highlight the usefulness of predictive scientometric techniques to understand the pace of scientific discovery in many fields. Arbesman, Laughlin The search for a habitable extrasolar planet has long interested scientists, but only recently have Source: http://www.doksinet the tools become available to search for such planets. In the past decades, the number of known extrasolar planets has ballooned into the hundreds, and with it, the expectation that the discovery of the first Earth-like extrasolar planet is not far off. Here, we develop a novel metric of habitability for discovered planets

and use this to arrive at a prediction for when the first habitable planet will be discovered. Using a bootstrap analysis of currently discovered exoplanets, we predict the discovery of the first Earth-like planet to be announced in the first half of 2011, with the likeliest date being early May 2011. Our predictions, using only the properties of previously discovered exoplanets, accord well with external estimates for the discovery of the first potentially habitable extrasolar planet and highlight the usefulness of predictive scientometric techniques to understand the pace of scientific discovery in many fields. Davarpanah, M.R (2010) constructed a model for measuring the strength and weakness of individual disciplines. The model is developed based on the balanced approach The model is tested on Iranian and Malaysian social sciences publications between 1991 - 2008 as a case study. The result indicates that the differences in rankings for measures of publication output, citation

distribution, and mean observed citation rate are large, which justifies the use of the scientific power index, which is introduced in this paper. Scientific power index proposes an objective mode of measuring performance at an aggregate level that will allow a comparison of individual fields within different disciplinary areas like technological sciences, medicine, natural science, social sciences, and humanities at national or global levels. The disciplinary characterization of national research efforts identifies the mainstream and dominant scientific fields, thus the developed index can be important tool for science policy. Source: http://www.doksinet Sun, J.a b, Ni, Ja b, and Ho, YSc d (2010) reported on the field of coastal eutrophication research by using bibliometrics. The objective of this study was to evaluate the coastal eutrophication research performance based on all the related articles in Science Citation Index databases from 1993 to 2008. Document type, publication

output, authorship, keywords, publication pattern, country, and institute of publication were analyzed. The USA contributed 35.0% of total articles where the ten major industrial countries accounted for the majority of the total production. An indicator citation per publication was presented in this study to evaluate the impact of number of authors, institutes, countries, and journals. The mean value of citation per publication of collaborative papers was higher than that of single country or institute publications. Collaboration trend was toward multi-authors, multi-institutes and multi-countries papers. This was coincident with the research trends of coastal eutrophication, which was thought to be a component of global change. Additionally, keywords analysis was used to indicate the formation and shift of hot research. Raghuraman, K.P, Chander, R, and Madras, G (2010) carried out a three-part study comparing the research performance of Indian institutions with that of other

international institutions. In the first part, the publication profiles of various Indian institutions were examined and ranked based on the h-index and p-index. We found that the institutions of national importance contributed the highest in terms of publications and citations per institution. In the second part of the study, we looked at the publication profiles of various Indian institutions in the high-impact journals and compared these profiles against that of the top Asian and US universities. We found that the number of papers in these journals from India was miniscule compared to the US universities. Recognizing that the publication profiles of various institutions depend on the field/departments, we studied the publication profiles of Source: http://www.doksinet many science and engineering departments at the Indian Institute of Science (IISc), Bangalore, the Indian Institutes of Technology, as well as top Indian universities. Because the number of faculty in each

department varies widely, we have computed the publications and citations per faculty per year for each department. We have also compared this with other departments in various Asian and US universities. We found that the top Indian institution based on various parameters in various disciplines was IISc, but overall even the top Indian institutions do not compare favourably with the top US or Asian universities. Annibaldi, A., et al (2010) highlighted Italian academic performance in analytical chemistry is evaluated by scrutinizing all the Institute for Scientific Information (ISI) publications produced during the professional lifetimes by the 80 Italian university professors in February 2009, providing a method for judging the scientific results of other countries in the same or other disciplines. The research was carried out through the Finder bibliographic search engine, which sifts through two databases. For completeness of information, the study finds that recent papers report

higher impact factor (IF) values, and in that case only a very limited number of journals that focused exclusively on the field of analytical chemistry for the time period 2000 2007 are considered. It is also found that a more careful selection of the journals invited to publish the results of scientific research, together with improvement in the quality of the research, could explain the significant increase in the impact factor for junior professors compared with senior professors. Vitzthum, K.a b et al (2010) has described that the passive exposure to environmental tobacco smoke (ETS) is estimated to exert a major burden of disease. Currently, numerous countries have taken legal actions to protect the population against ETS. Numerous studies Source: http://www.doksinet have been conducted in this field. Therefore, scientometric methods should be used to analyze the accumulated data since there is no such approach available so far. A combination of scientometric methods and novel

visualizing procedures were used, including densityequalizing mapping and radar charting techniques. 6,580 ETS-related studies published between 1900 and 2008 were identified in the ISI database. Using different scientometric approaches, a continuous increase of both quantitative and qualitative parameters was found. The combination with density-equalizing calculations demonstrated a leading position of the United States (2,959 items published) in terms of quantitative research activities. Charting techniques demonstrated that there are numerous bi- and multilateral networks between different countries and institutions in this field. Again, a leading position of American institutions was found. Conclusions: This is the first comprehensive scientometric analysis of data on global scientific activities in the field of environmental tobacco smoke research. The present findings can be used as a benchmark for funding allocation processes. Bartol, T. (2010) assessed selected characteristics

of documents published in national journals and other publications in the countries which participate on the editorial board of an international journal JCEA (Journal of Central European Agriculture). Bibliographic citations from the CAB Abstracts database were employed. Search syntax along with some cataloging characteristics of the database was addressed. In total more than 89000 agriculture-related documents were identified in the period 2000-2008 with journal articles predominating, followed by proceedings (conference papers). The two document types can overlap English plays a role of the principal language, accounting for more than half of all records (48.000) Poland is the major contributor of documents, being by far the largest country. Croatian publications show the highest level of international participation in domestic publications, Source: http://www.doksinet whereas the Slovenian authors show the highest level of publishing in non-domestic publications. Altogether some

378 different agricultural and related life- and environmental sciences journals have been active in the region in this period. The results can serve as an indicator of regional publishing activities and behavior of authors. Glanzel, W. (2010) revealed the overview over the opportunities of probabilistic models in scientometrics. Four examples from different topics are used to shed light on some important aspects of reliability and robustness of indicators based on stochastic models. Limitations and future tasks are discussed as well. Meneghini, R.a b c, and Packer, ALb d (2010) described the publications in scientometrics and bibliometrics with Brazilian authorship expanded exponentially in the 19902006 period, reaching 13 times in the Web of Science database and 19.5 times in the Google Scholar database. This increase is rather superior to that of the total Brazilian scientific production in the same time period (5.6 times in the Web of Science) Some characteristics to be noticed in

this rise are: 1) The total number of articles during this period was 197; in that, 78% were published in 57 Brazilian journals and 22% in 13 international journals. 2) The national and international articles averaged 4.3 and 59 citations/article, respectively; two journals stood out among these, the national Ciência da Informação (44 articles averaging 6.7 citations/article) and the international Scientometrics (32 articles averaging 6.2 citations/article). 3) The articles encompass an impressive participation of authors from areas other than information science; only one-fourth of the authors are bound to the information science field, the remaining ones being distributed among the areas of humanities/business administration, biology/biomedicine, health and hard sciences. The occurrence of adventitious authors at this level of multidisciplinarity is uncommon in science. However, the possible Source: http://www.doksinet benefits of such patterns are not clear in view of

a fragmented intercommunication among the authors, as noticed through the citations. The advantages of changing this trend and of using other scientometric and bibliometric databases, such as SciELO, to avoid an almost exclusive use of the Web of Science database, are discussed. Arbesman, S.a b, Laughlin, Gc (2010) searched for a habitable extrasolar planet has long interested scientists, but only recently have the tools become available to search for such planets. In the past decades, the number of known extrasolar planets has ballooned into the hundreds, and with it, the expectation that the discovery of the first Earth-like extrasolar planet is not far off. Here, we develop a novel metric of habitability for discovered planets and use this to arrive at a prediction for when the first habitable planet will be discovered. Using a bootstrap analysis of currently discovered exoplanets, we predict the discovery of the first Earth-like planet to be announced in the first half of 2011,

with the likeliest date being early May 2011. Our predictions, using only the properties of previously discovered exoplanets, accord well with external estimates for the discovery of the first potentially habitable extrasolar planet and highlight the usefulness of predictive scientometric techniques to understand the pace of scientific discovery in many fields Annibaldi, A., Truzzi, C, Illuminati, S, and Scarponi, G (2010) examined Italian academic performance in analytical chemistry is evaluated by scrutinizing all the Institute for Scientific Information (ISI) publications produced during the professional lifetimes by the 80 Italian university professors in February 2009, providing a method for judging the scientific results of other countries in the same or other disciplines. The research was carried out through the SciFinder bibliographic search engine, which sifts through two databases. For completeness Source: http://www.doksinet of information, the study finds that recent

papers report higher impact factor (IF) values, and in that case only a very limited number of journals that focused exclusively on the field of analytical chemistry for the time period 2000 2007 are considered. It is also found that a more careful selection of the journals invited to publish the results of scientific research, together with improvement in the quality of the research, could explain the significant increase in the impact factor for junior professors compared with senior professors. Raghuraman. K P, Chander R, and Madras G (2010) described a three-part study comparing the research performance of Indian institutions with that of other international institutions. In the first part, the publication profiles of various Indian institutions were examined and ranked based on the h-index and p-index. We found that the institutions of national importance contributed the highest in terms of publications and citations per institution. In the second part of the study, we looked at

the publication profiles of various Indian institutions in the high-impact journals and compared these profiles against that of the top Asian and US universities. We found that the number of papers in these journals from India was miniscule compared to the US universities. Recognizing that the publication profiles of various institutions depend on the field/departments, we studied the publication profiles of many science and engineering departments at the Indian Institute of Science (IISc), Bangalore, the Indian Institutes of Technology, as well as top Indian universities. Because the number of faculty in each department varies widely, we have computed the publications and citations per faculty per year for each department. We have also compared this with other departments in various Asian and US universities. We found that the top Indian institution based on various parameters in various disciplines was IISc, but overall even the top Indian institutions do not compare favorably with

the top US or Asian universities. Source: http://www.doksinet Loet Leydesdorff and Élaine Gauthier (1999) examined effectively can emerge science-based technologies be coupled to national R&D systems? Dutch and Canadian priority programs in biotechnology and advanced materials are analyzed in terms of differential increases in scientific output by using scientometric indicators and mappings. Methodological issues about using scientometric methods for science policy evaluations in the case of interdisciplinary and rapidly changing areas of ‘techno-science’ are discussed. The major finding of the paper is that Canadian researchers seem to have used the priority programs as an alternative source of funding, while their Dutch colleagues were able to use these programs to help their specialties grow above the national average, and in accordance with selected priorities. Thus, the results suggest that the national dimension has been more important for explaining differences in

performance than the substantive specificity of the two priority areas. John A. Stewart (1994) described the Poisson-lognormal model assumes that the intensity parameter of a Poisson process has a lognormal distribution in a sample of observations. This model can yield highly skewed, discrete distributions, but must be estimated by numerical methods. When applied to many of the empirical data sets related to the ‘laws’ of Lotka, Bradford, and Zipf, this compound Poisson model produces good to excellent fits. Discussion includes possible ‘causal’ processes and some implications for future bibliometric and scientometric studies. Zhang Haiqi and Zhang Yuhua (1997) explained the research performance in China has increased appreciably during the past few years, both in regard to relative output of publications and in their impact on the international research productivity. The purpose of this survey, based on the data recorded in the Science Citation Index (SCI) database between

1987 Source: http://www.doksinet and 1993, is to study the research performance in the Peoples Republic of China. The 35,087 papers published in domestic or foreign periodicals were selected for analysis and evaluation of the distribution of publications and citations, for the numerical characterization of research performance in China. The findings indicate that 17,687 papers covered by the Source Indexes of the SCI in the period 1990–1992 had received 7944 citations in the year 1993 and that the mean citation rate is 0.45 The number of cited papers is 4491 and the proportion of cited papers to the total is 0.25 Bruce G. Charlton (1997) described in most research is ‘normal science’ using Thomas Kuhn’s term: checking, trial-and-error improvement and incremental extrapolation of already existing paradigms. By contrast, ‘revolutionary science’ changes the fundamental structures of science by making new theories, discoveries or technologies. Science Nobel prizes (in

Physics, Chemistry, Physiology/Medicine and Economics) have the potential to be used as a new metric for measuring revolutionary science. Nobel laureates’ nations and research institutions were measured between 1947 and 2006 in 20-year segments. The minimum threshold for inclusion was 3 Nobel prizes. Credit was allocated to each laureate’s institution and nation of residence at the time of award. Over 60 years, the USA has 19 institutions, which won three-plus Nobel prizes in 20 years, the UK has 4, and France has 2 and Sweden and USSR 1 each. Four US institutions won 3 or more prizes in all 20-year segments: Harvard, Stanford, Berkeley and CalTech. The most successful institution in the past 20 years was MIT, with 11 prizes followed by Stanford (9), Columbia and Chicago (7). But the Western United States has recently become the world dominant region for revolutionary science, generating a new generation of elite public universities: University of Colorado at Boulder; University of

Washington at Seattle; and the University of California institutions of Santa Barbara, Irvine, UCSF, and UCLA; also Source: http://www.doksinet the Fred Hutchinson CRC in Seattle. Since 1986 the USA has 16 institutions, which have won 3 plus prizes, but elsewhere in the world only the College de France has achieved this. In the UK Cambridge University, Cambridge MRC unit, Oxford and Imperial College have declined from 17 prizes in 1967–86 to only 3 since then. Harvard has also declined as a revolutionary science university from being the top Nobel-prize-winning institution for 40 years, to currently joint sixth position. Although Nobel science prizes are sporadically won by numerous nations and institutions, it seems that long-term national strength in revolutionary science is mainly a result of sustaining and newly-generating multi-Nobel-winning research centres. At present these elite institutions are found almost exclusively in the USA. The USA is apparently the only nation

with a research system that nurtures revolutionary science on a large scale. Loet Leydesdorff, Susan Cozzens and Peter Van den Besselaar (1994) reviewed in science policy, it is often important to track emerging developments: new fields, fast-changing areas that are the focus of special funding efforts, or areas of growth or decline. This article presents methods to produce literature-based indicators for such areas using journal-to-journal citations. Using case studies of AIDS, superconductivity, and oncogenes, we posit that the inclusion of a new journal can be used as an indicator of structural change if the addition indicates the emergence of a new journal category. Using the cases of robotics and artificial intelligence, we illustrate the development of areas chosen for priority funding. Again using artificial intelligence, we demonstrate the importance of constructing even such simple measures of scientific performance as publication counts using dynamic rather than constant

journal sets. Change in performance within a subfield can be systematically distinguished from change in the delineations Outline among subfields over time. Source: http://www.doksinet REFERENCES • Bajwa, R. S, Yaldram, K, & Rafique, S (2013) A scientometric assessment of research output in nanoscience and nanotechnology: Pakistan perspective. Scientometrics, 94(1), 333-342 • Alhaider, I., Ahmed, M K K, & Gupta, B M (2013) Global research output on date palm (pheonix dactylifera): A 12 years scientometric perspective. Scientometrics, , 1-15 • Shao, H., Yu, Q, Bo, X, & Duan, Z (2013) Analysis of oncology research from 2001 to 2010: A scientometric perspective. Oncology Reports, 29(4), 1441-1452 • Gupta, B. M, Kaur, H, & Kshitig, A (2012) Dementia research in india: A scientometric analysis of research output during 2002-11. Annals of Library and Information Studies, 59(4), 280-288. • Mulla, K. R (2012) Identifying and mapping the information

science and scientometrics analysis studies in India (2005-2009): A bibliometric study. Library Philosophy and Practice, 2012(JUNE), 1-18. • Abolghassemi Fakhree. MA, Jouyban A (2011), “Scientometric analysis of the major Iranian medical universities”. Volume 87, Issue 1, January 2011, Pages 205-220 • Cocosila, M.Ser ATurel (2011), “Exploring the management information systems discipline: A scientometric study of ICIS, PACIS and ASAC” Volume 87, Issue 1, January 2011, Pages 1-16 • Mahbuba. D, Rousseau R, SrivastavaD (2010), “A scientometric analysis of health and population research in South Asia: Focus on two research organizations” ISSN: 13946234Volume 15, Issue 3, 2010, Pages 135-147 Source: http://www.doksinet • Varaprasad, S.JD Sahoo, SMadhusudhan, S (2010), “Research contributions of J.S Yadav to chemical sciences: A scientometric study” ISSN: 13946234 Volume 15, Issue 2, 2010, Pages 41-55 • Alijani, R.a, Karami, Nb (2010), “A review of scientific

publications by Iranian researchers on stem cells in the ISI database” ISSN: 15614921 Volume 11, Issue 4, December 2010, Pages 456-458 • Arbesman, S.a b, Laughlin, G (2010), “A scientometric prediction of the discovery of the first potentially habitable planet with a mass similar to earth” ISSN: 19326203 DOI: 10.1371/journalpone0013061 Volume 5, Issue 10, 2010, Article number e13061 • Davarpanah, M.R (2010), “A scientometric model for the assessment of strength and weakness of scientific disciplines: A domain-based analysis” ISSN: 00242535 DOI: 10.1108/00242531011073128 Volume 59, Issue 8, 2010, Pages 596 • Sun, J.a b, Ni, Ja b, Ho, YSc d (2010), “Scientometric analysis of coastal eutrophication research during the period of 1993 to 2008” ISSN: 1387585X CODEN: EDSNB DOI: 10.1007/s10668-010-9265-5 • Raghuraman, K.P, Chander, R, Madras, G (2010), “Scientometric analysis of some disciplines: Comparison of Indian institutions with other international

institutions” ISSN: 00113891 Volume 99, Issue 5, September 2010, Pages 577-587 • Annibaldi, A., Truzzi, C, Illuminati, S, Scarponi, G (2010), “Scientometric analysis of national university research performance in analytical chemistry on the basis of Source: http://www.doksinet academic publications: Italy as case study” ISSN: 16182642 CODEN: ABCNB DOI: 10.1007/s00216-010-3804-7 Volume 398, Issue 1, September 2010, Pages 17-26 • Vitzthum, K.a b, Scutaru, Ca b, et al, (2010), “Scientometric analysis and combined density-equalizing mapping of environmental tobacco smoke (ETS) research” ISSN: 19326203 DOI: 10.1371/journalpone0011254C Volume 5, Issue 6, 2010, Article number e11254 • Bartol, T. (2010), “Scientometric assessment of publishing patterns and performance indicators in agriculture in the JCEA member countries” ISSN: 13329049 Volume 11, Issue 1, 2010, Pages 1-10 • Glänzel, W. (2010), “On reliability and robustness of scientometrics indicators based on

stochastic models. An evidence-based opinion paper” ISSN: 17511577 DOI: 10.1016/jjoi201001005 Volume 4, Issue 3, July 2010, Pages 313-319 • Meneghini, R.a b c, Packer, ALb d (2010), “The extent of multidisciplinary authorship of articles on scientometrics and bibliometrics in Brazil” ISSN: 03781844 Volume 35, Issue 7, July 2010, Pages 510-514 • Arbesman, S.a b, Laughlin, Gc (2010), “A scientometric prediction of the discovery of the first potentially habitable planet with a mass similar to earth” SSN: 19326203 DOI: 10.1371/journalpone0013061 • Annibaldi, A., Truzzi, C, Illuminati, S, Scarponi, G (2010), “Scientometric analysis of national university research performance in analytical chemistry on the basis of academic publications: Italy as case study” ISSN: 16182642 DOI: 10.1007/s00216-0103804-7 Source: http://www.doksinet • Raghuraman, K.P, Chander, R, Madras, G (2010), “Scientometric analysis of some disciplines: Comparison of Indian institutions with

other international institutions” ISSN: 00113891 Volume 99, Issue 5, September 2010, Pages 577-587 • Loet Leydesdorff and Élaine Gauthier (1999), “The evaluation of national performance in selected priority areas using scientometric methods” Volume 25, Issue 3, May 1996, Pages 431-450 • John A. Stewart (1994), “The poisson-lognormal model for bibliometric/scientometric distributions” Volume 30, Issue 2, March-April 1994, Pages 239-251 • Loet Leydesdorffa, Susan Cozzensb and Peter Van den Besselaarc (1994), “Tracking areas of strategic importance using scientometric journal mappings” Volume 23, Issue 2, March 1994, Pages 217-229 • Zhang Haiqia and Zhang Yuhuab (1997), “Scientometric study on research performance in China” Volume 33, Issue 1, January 1997, Pages 81-89 • Bruce G. Charlton (1997), “Scientometric identification of elite ‘revolutionary science’ research institutions by analysis of trends in Nobel prizes” 1947–2006Volume 68, Issue 5,

2007, Pages 931-93 Source: http://www.doksinet CHAPTER – III RESEARCH DESIGN This chapter deals with contents and meaning of undertaking the study in terms of objectives, methodology, data collection, statistical tools and techniques used, operational definition of key concepts and limitations of the study. STATEMENT OF THE PROBLEM The present study aims at analysing the research output performance of virology. In academic and scientific work, publication is the chief means of research output. Therefore, it is through publication the scientists receive professional recognition and esteem as well as promotion, advancement, and funding for future research. Publication is so central to productivity in research that the work becomes ‘a work’ only when it takes a conventional, physical (that is published) form, which can be received, assessed and acknowledged by the scientific community. Hence publication is a social norm in a public sense and serves as a tool for the betterment

of the individuals. After publication only, it can be called as research and can be fixed or judged and acknowledged by the scientists in the society.It could be seen clearly from the above discussion that Scientometric analysis is an important tool in analyzing any Source: http://www.doksinet science discipline. By keeping this view in mind, the researcher intends to undertake the study on “Scientometric mapping of Virology Research: A Global Perspective of virology: A Scientometric Analysis”. This study attempts to analyse the performance of Researchers working in the field of virology in terms of growth rate, areas of research concentration, author productivity and authorship pattern. OBJECTIVES The main objective of this study was to use Scientometric mapping and analyze the key features of virology research activities at global level: • To identify and analyse the rate of growth of research productivity; • To examine the Year wise distribution of publications;

• To note the Document wise distribution of publications; • To analyse the authorship pattern and examine the extent of research collaboration and ranking of authors based on publications; • To identify journal wise distribution of publications; • To identify word wise distribution of publications; • To assess the Institution wise research concentration; • To identify Country – wise Collaborative Distribution of Publications; • To identify the Funding Agencies for virology; • To identify Global Citation Scores; • To apprehend and test the applicability of Lotka’s Law of Scientific Productivity of Authors; • To test the Bradford’s Law of Scattering in virology research output; Source: http://www.doksinet METHODOLOGY The study entitled “Scientometric mapping of Virology Research: A Global Perspective Scientometric Study” is a study encompassing records output on Science from Science Citation Index (SCI) available on online (Web of

Science). The present study aims at analysing the research output of Researchers in the field of virology. The growth rates of output in terms of research productivity is analysed from 1998 to 2010. The authorship pattern and author productivity are examined to identify the pattern of research contribution in the field of virology. It is also analytical in nature in strengthening the empirical validity due to application of suitable statistical tools. Source: http://www.doksinet CHAPTER – IV ANALYSIS AND INTERPRETATIONS Grand Totals: LCS 632, GCS 31793, CR 92047 Collection span: 2001 - 2012 List of All Records Records: 2025, Authors: 8056, Journals: 758, Cited References: 72513, Words: 4830 Yearly output | Document Type | Language | Institution | Institution with Subdivision | Country Year wise distribution of publications To analyse the year wise publication of research on Virology, the data has been presented in Table-1. The table depicts the research output in the global

level From the below table, we could clearly see that during the period 2001 - 2012 a total of 2025 publications were published. In the present study the research output on Virology publication is taken as a tool to evaluate the performance at various levels. Table 1 could clearly see that during the period 2001- 2012 a total of 2025 publications were published at global level. The highest publication is 220 in 2011 with 1272 Global Citation Scores followed by 214 papers in 2012 with 297Global Citation Score and 200 papers in 2010 with 1695 Global Citation Scores. It shows that even minimum numbers of records were scored higher global citations. The study also reveals all these 2025 publications have Source: http://www.doksinet 72513 cited references it shows that there is a healthy trend in citing reference is found among the global Scientists belongs to virology. Table 1- shows Year wise Distribution of Publications Sl.no Publication Year Records % TLCS TGCS 1 2001 132

6.5 64 3063 2 2002 160 7.9 103 4315 3 2003 150 7.4 83 4177 4 2004 158 7.8 92 4009 5 2005 147 7.3 43 3151 6 2006 163 8.0 63 2857 7 2007 148 7.3 48 2725 8 2008 144 7.1 44 2151 9 2009 189 9.3 31 2081 10 2010 200 9.9 32 1695 11 2011 220 10.9 28 1272 12 2012 214 10.6 1 297 Source: http://www.doksinet Document wise distribution of Publications The study reveals that the major source of publications covered by Web of Science on Virology research in journal articles (63.5%), while reviews comprises (185%) and editorial materials comprises (6.6%) of the remaining literature Table 2 shows Document wise distribution of Publications Recs Percent TLCS TGCS 1 Article 1285 63.5 338 19262 2 Review 375 18.5 202 9057 3 Editorial Material 133 6.6 25 959 97 4.8 50 1844 5 News Item 44 2.2 8 122 6 Meeting Abstract 37 1.8 1 33 7 Letter 18 0.9 1 146 Review; Book Chapter 14 0.7 4 324 9

Biographical-Item 6 0.3 1 6 10 Book Review 6 0.3 0 1 11 Correction 6 0.3 0 2 sl.no 4 8 Document Type Article; Proceedings Paper Source: http://www.doksinet 12 Article; Book Chapter 3 0.1 2 19 13 Software Review 1 0 0 18 Journal wise Distribution of Publications The study found that the total research output of the virology for the study period (20012012) published in 758 journals. As the major portion of the research productivity (55%) covered by 100 journals that is coincide with the theory of Bradford’s Law of scattering of journals in research productivity. Top ten produced mostly 237% of the research output The journal “JOURNAL OF VIROLOGY” topped with 110 publications with the Global Citation Score of 2910, next “VIROLOGY” has 76 publications with the Global Citation Score of 1446 and “JOURNAL OF CLINICAL VIROLOGY” with 73publications with the Global Citation Score of 1083 respectively. “JOURNAL OF VIROLOGICAL METHODS” has scored

the highest Global Citation Score of 457 with 44 publications while “JOURNAL OF INFECTIOUD DISEASES” has scored a Global Citation Score of 381 with just 7 records. Source: http://www.doksinet Journal wise distribution of Publications - 758 # Journal Recs Percent TLCS TGCS 1 Journal of virology 110 5.4 52 2910 2 Virology 76 3.8 25 1446 3 Journal of clinical virology 73 3.6 64 1083 4 Journal of virological methods 44 2.2 11 457 5 Science 37 1.8 17 773 6 Journal of clinical microbiology 36 1.8 35 1199 7 Journal of medical virology 28 1.4 9 414 8 Vaccine 26 1.3 3 376 9 Gastroenterology 25 1.2 2 366 10 Journal of neurovirology 25 1.2 1 173 11 Future virology 18 0.9 0 34 12 Medycyna weterynaryjna 18 0.9 5 8 13 Nature 18 0.9 6 260 14 Virus research 18 0.9 5 270 15 Journal of general virology 17 0.8 4 265 16 Plos one 17 0.8 0 152 17 Reviews in medical virology 17 0.8 10 324 18 Proceedings of the

national academy of sciences 16 0.8 6 954 Source: http://www.doksinet of the united states of america 19 Virology journal 16 0.8 0 175 20 Antiviral research 14 0.7 2 296 21 Nature reviews microbiology 14 0.7 4 123 22 Pediatric infectious disease journal 14 0.7 2 210 23 European journal of immunology 13 0.6 0 220 24 Veterinary microbiology 13 0.6 0 123 25 Cochrane database of systematic reviews 12 0.6 0 49 26 Epidemiology and infection 12 0.6 0 109 27 Enfermedades infecciosas y microbiologia clinica 11 2 19 28 Nucleic acids research 11 0.5 44 782 29 Aids 10 0.5 3 276 30 Current opinion in virology 10 0.5 2 47 31 Retrovirology 10 0.5 0 68 32 Virologie 10 0.5 0 0 33 Clinical microbiology and infection 9 0.4 13 81 34 Hepatology 9 0.4 3 234 35 Jaids-journal of acquired immune deficiency syndromes 9 1 94 36 Seminars in liver disease 9 0.4 9 207 37 Avian diseases 8 0.4 3 136 38 Journal of

biological chemistry 8 0.4 3 229 39 Journal of hepatology 8 0.4 8 207 40 Mikrobiyoloji bulteni 8 0.4 0 11 41 Virus genes 8 0.4 0 58 42 Annales de biologie clinique 7 0.3 0 4 43 Annals of pharmacotherapy 7 0.3 0 130 44 Antiviral therapy 7 0.3 1 85 45 Archives of virology 7 0.3 3 223 46 Bulletin of the world health organization 7 0.3 2 101 47 Journal of infectious diseases 7 0.3 13 381 48 Viruses-basel 7 0.3 0 19 49 Biofutur 6 0.3 0 0 50 Journal of gene medicine 6 0.3 0 54 51 Mayo clinic proceedings 6 0.3 2 173 0.5 0.4 Source: http://www.doksinet 52 World journal of gastroenterology 6 0.3 2 182 53 Acta virologica 5 0.2 0 11 54 Aids research and human retroviruses 5 0.2 0 77 55 Australian veterinary journal 5 0.2 0 16 56 Bmc infectious diseases 5 0.2 0 52 57 Clinical chemistry 5 0.2 4 60 58 Clinical infectious diseases 5 0.2 0 161 59 Clinics in laboratory medicine 5 0.2 6 52

60 Gene therapy 5 0.2 1 83 61 International journal of cancer 5 0.2 0 43 62 Journal of viral hepatitis 5 0.2 0 26 63 Lancet 5 0.2 9 905 64 Microbiologica 5 0.2 4 17 65 Molecular therapy 5 0.2 7 234 66 Pathologie biologie 5 0.2 0 8 67 Philosophical transactions of the royal society of london series b-biological sciences 5 3 220 68 Phytopathology 5 1 15 69 Revue scientifique et technique-office international des epizooties 5 0 37 70 Rivista di biologia-biology forum 5 0.2 2 12 71 Sexually transmitted infections 5 0.2 4 103 72 Veterinary pathology 5 0.2 4 83 73 American journal of clinical pathology 4 0.2 0 38 74 American journal of transplantation 4 0.2 1 143 75 Annales de dermatologie et de venereologie 4 0.2 0 6 76 Annual review of phytopathology 4 0.2 4 448 77 Archives de pediatrie 4 0.2 0 5 78 Berliner und munchener tierarztliche wochenschrift 4 0 4 79 Emerging infectious diseases 4 0.2 8

451 80 Eurosurveillance 4 0.2 0 6 81 Expert review of anti-infective therapy 4 0.2 1 18 82 Indian journal of medical research 4 0.2 2 27 83 Infection control and hospital epidemiology 4 0.2 0 12 84 International journal of infectious diseases 4 0.2 0 18 0.2 0.2 0.2 0.2 Source: http://www.doksinet 85 Journal of acquired immune deficiency syndromes 4 3 295 86 Journal of gastroenterology and hepatology 4 0.2 0 6 87 Journal of theoretical biology 4 0.2 14 75 88 Journal of wildlife diseases 4 0.2 0 68 89 Journal of zoo and wildlife medicine 4 0.2 0 14 90 Labmedicine 4 0.2 0 2 91 Magyar allatorvosok lapja 4 0.2 0 2 92 Microbes and infection 4 0.2 1 75 93 Plos pathogens 4 0.2 0 169 94 Presse medicale 4 0.2 0 16 95 Texas heart institute journal 4 0.2 1 61 96 Veterinary clinics of north america-small animal practice 4 0 14 97 Veterinary record 4 0.2 0 1 98 Accreditation and quality assurance 3 0.1 0

3 99 African journal of microbiology research 3 0.1 0 3 100 Angewandte chemie-international edition 3 0.1 0 19 0.2 0.2 Distribution Journals in Various Zone Bradford in his study analyzed articles in Virology. He has listed the journals containing to that field in descending order of productivity and then divided the list into three “Zones” each containing roughly the same number of journals. Bradford observed that the number of journals contributing articles to each zone increased by the multiplication of about five. The distribution of journals in various zones is as follows: Source: http://www.doksinet Table 4.25 – Shows Bradford’s Distribution of Journals Zone Journals Number of Records Zone 1 22 677 Zone 2 160 675 Zone 3 576 673 Total 1091 3324 The table 4.25 above shows the observation of small groups of twenty six journals identified to the nuclear or core zone representing 2.38 percent of journals covered 1110 (3339 %) of articles. The

second larger group of 219(2007 %) journals provides 1218 (3664 %) articles and the third largest zone of 845 (77.45 %) of periodicals yield the next 996 (2996 %) articles. The Bradford multiplier between the number of references in zone 1 and zone 2 is 842 while it is 3.85 between zone 2 and zone 3 The average multiplier value is 613 According to Bradfords distribution, the relationship between the zone is 1: a: n2. In contrast is the relationship in each of the present study i.e 26:219:845 which do not fit into Bradfords distribution. This shows that core contributions are given by 26 journals, ie less than Bradford formulated and the final zones contain a very large number of journals, i.e much more than the Bradfords formula. This is a clear indication that core zone is more concentrated and the other zone is much extended showing the scattering of journals on Green Computing research literature. When this analysis is done for a wider range of periods, the extent of scattering can

increase. It is evident from the above analysis the third hypothesis is not clearly proved. (The distribution of Green Computing research output journals and articles confirms the implications of Bradford’s law) Source: http://www.doksinet It observed from the above analysis each zone (core, zone 2 = z2 and zone 3 = z3) consists of approximately 3324 articles. The documents are scattered over 1091 journals: the highest concentration is in the core with 29 journals, z2 consists of 219 journals and the 996 articles in z3 are scattered across 845 journals. Language Wise Distribution of Publications So far as language of publication is concerned English with 1870 (92.3 %) articles tops the list. During the study period French language 56(28%) occupied second position, followed by German, Spanish and polish. It could be identified from the analysis above, most of the scientists’ prefer the English language for their sharing of knowledge and using communication channel in their

products. It is commonly know that the English language is researcher accepted and research friendly communication language. Remaining 49 percent of articles were in other language format Language sl.no 1 English Recs Percent TLCS TGCS 1870 92.3 617 31554 Source: http://www.doksinet 2 French 56 2.8 2 72 3 Spanish 26 1.3 3 44 4 German 25 1.2 4 65 5 Polish 18 0.9 5 8 6 Turkish 9 0.4 0 11 7 Portuguese 8 0.4 1 32 8 Hungarian 4 0.2 0 2 9 Czech 3 0.1 0 2 10 Serbian 2 0.1 0 0 11 Chinese 1 0 0 0 12 Croatian 1 0 0 0 13 Italian 1 0 0 0 14 Russian 1 0 0 3 Institution wise Distribution of Publications Source: http://www.doksinet The below table analysis indicates Institution-wise research productivity. It is noted that 101 institutions were contributed 2025 of the total research productivity. It is noted that Unknown Research Institute contributed the highest number of research publications 99 (4.9%) at

the same time it ranks first in terms of Global Citation Score 232. University of Washington is second highest number of research publication 33 (1.6%) and Global citation score is 545 Institution wise 2207 Institution sl.no 1 Unknown Recs Percent TLCS TGCS 99 4.9 10 232 Source: http://www.doksinet 2 University of Washington 33 1.6 12 545 3 Harvard University 30 1.5 4 1021 4 Scripps Res Inst 22 1.1 11 421 5 University of Florida 22 1.1 11 401 6 Baylor Coll Med 20 1 12 477 7 Ctr Dis Control & Prevent 20 1 13 633 8 Inst Pasteur 20 1 6 252 9 NIAID 20 1 8 613 10 University Texas 19 0.9 18 684 11 Stanford University 18 0.9 7 396 12 UCL 18 0.9 6 290 13 Cornell University 17 0.8 4 699 14 University N Carolina 17 0.8 3 299 15 Johns Hopkins University 16 0.8 2 770 16 Chinese Academic Science 15 0.7 0 247 17 University California Los Angeles 15 0.7 14 540 18 University of Pittsburgh

15 0.7 5 283 19 WHO 15 0.7 4 557 20 University of Hong Kong 14 0.7 10 1074 21 Oxford University 14 0.7 7 291 22 University of Wisconsin 14 0.7 4 241 23 Fred Hutchinson Cancer Research Centre 13 0.6 3 257 24 INSERM 13 0.6 5 215 Source: http://www.doksinet 25 University California Davis 13 0.6 2 150 26 University California San Francisco 13 0.6 2 255 27 Duke University 12 0.6 0 298 28 Emory University 12 0.6 13 802 29 University Kentucky 12 0.6 7 399 30 University of London Imperial Coll Sci Technol & Med 12 0.6 5 262 31 University Penn 12 0.6 2 229 32 University Sao Paulo 12 0.6 2 78 33 CNRS 11 0.5 2 163 34 Natl Institute of Virology 11 0.5 1 84 35 University California San Diego 11 0.5 4 182 36 University Maryland 11 0.5 0 225 37 University Nebraska 11 0.5 1 151 38 CNR 10 0.5 5 40 39 Inst Anim Health 10 0.5 1 190 40 Karolinska Institute 10 0.5 6

141 41 Mayo Clinics 10 0.5 3 195 42 McGill University 10 0.5 0 162 43 N Carolina State University 10 0.5 4 221 44 Robert Koch Inst 10 0.5 5 87 45 Texas A&M University 10 0.5 5 167 46 University British Columbia 10 0.5 0 86 47 University of Edinburgh 10 0.5 15 345 Source: http://www.doksinet 48 University of Freiburg 10 0.5 9 253 49 University of Lyon 1 10 0.5 4 201 50 University of Munich 10 0.5 2 179 51 USDA ARS 10 0.5 4 196 52 Chang Gung University 9 0.4 7 304 53 Leiden University 9 0.4 0 59 54 Natl University of Singapore 9 0.4 1 96 55 NCI 9 0.4 3 202 56 University Med & Dent New Jersey 9 0.4 1 196 57 University Miami 9 0.4 2 223 58 University Utah 9 0.4 1 144 59 Washington University 9 0.4 7 251 60 Chinese University Hong Kong 8 0.4 0 61 61 Ecole Normale Super Lyon 8 0.4 0 165 62 Erasmus MC 8 0.4 1 91 63 Free University of Berlin 8 0.4 0

53 64 Gartnavel Royal Hosp 8 0.4 14 97 65 Hannover Med School 8 0.4 2 197 66 Health Protect Agcy 8 0.4 2 221 67 Kyoto University 8 0.4 2 74 68 Massachusetts Gen Hosp 8 0.4 2 193 69 Natl Institute Infectious Diseases 8 0.4 3 347 70 Ohio State University 8 0.4 1 245 Source: http://www.doksinet 71 Royal Infirm Edinburgh NHS Trust 8 0.4 8 220 72 Thomas Jefferson University 8 0.4 1 101 73 University Alberta 8 0.4 3 194 74 University Colorado 8 0.4 3 85 75 University Glasgow 8 0.4 2 218 76 University Manitoba 8 0.4 1 135 77 University Michigan 8 0.4 1 110 78 University Milan 8 0.4 6 95 79 University Tokyo 8 0.4 1 69 80 University Toronto 8 0.4 1 131 81 Victorian Infectious Disease Reference Lab 8 0.4 8 200 82 INRA 7 0.3 3 149 83 Institute Super Sanita 7 0.3 7 262 84 Lund University 7 0.3 0 76 85 Ministry Health 7 0.3 1 77 86 Natl Taiwan University 7 0.3

1 62 87 NIH 7 0.3 0 65 88 Rockefeller University 7 0.3 2 199 89 Swedish Inst Infect Disease Control 7 0.3 4 106 90 Tufts University 7 0.3 1 138 91 Ul Puszkina 8-10 7 0.3 1 1 92 University Aix Marseille 2 7 0.3 1 44 93 University Amsterdam 7 0.3 0 275 Source: http://www.doksinet 94 University Bonn 7 0.3 0 77 95 University Helsinki 7 0.3 2 99 96 University Hosp 7 0.3 0 110 97 University Kansas 7 0.3 4 202 98 University Minnesota 7 0.3 1 130 99 University Utrecht 7 0.3 5 140 100 University York 7 0.3 7 37 101 Vanderbilt University 7 0.3 10 323 COUNTRY WISE Distribution of Publications: Source: http://www.doksinet The below table indicates that among the country wise distribution of VIROLOGY covered by the study tops United States of America with 690(34.1%) publications followed by UNKNOWN with 217(10.7%), United Kingdom with 210(104%), FRANCE with 163(80%) and GERMANY with 157(7.8%) research

publications respectively First place goes to United States of America having total Global Citation Score of 14343 with 690 publications. UNKNOWN secured second rank in terms of GCS with 1958 but with only 217 publications and also collaboration with more than 80 Countries. Country wise Country sl,no Recs Percent TLCS TGCS 1 USA 690 34.1 228 14343 2 Unknown 217 10.7 35 1958 3 UK 210 10.4 125 3634 4 France 163 8 44 2335 5 Germany 157 7.8 54 2437 6 Canada 90 4.4 39 1760 7 Italy 89 4.4 30 1198 8 Peoples R China 82 4 15 1665 9 Netherlands 70 3.5 47 1402 10 Australia 66 3.3 46 1286 11 Japan 57 2.8 21 1306 12 Spain 47 2.3 10 965 13 India 42 2.1 8 412 14 Brazil 37 1.8 5 349 15 Sweden 34 1.7 9 452 16 Belgium 30 1.5 4 553 Source: http://www.doksinet 17 Switzerland 30 1.5 11 850 18 Taiwan 25 1.2 11 460 19 Israel 22 1.1 2 166 20 Poland 21 1 6 35 21 Turkey 16 0.8 0

42 22 Singapore 15 0.7 3 159 23 Finland 14 0.7 2 172 24 South Korea 14 0.7 1 203 25 Austria 13 0.6 5 160 26 South Africa 13 0.6 1 89 27 Argentina 12 0.6 2 109 28 Hungary 12 0.6 2 255 29 Iran 11 0.5 0 12 30 Greece 10 0.5 3 278 31 Denmark 9 0.4 7 152 32 Nigeria 9 0.4 1 50 33 Russia 9 0.4 0 18 34 Czech Republic 8 0.4 2 129 35 Ireland 8 0.4 2 113 36 Malaysia 8 0.4 1 171 37 Norway 8 0.4 0 73 38 Bulgaria 6 0.3 0 45 39 New Zealand 6 0.3 1 123 40 Pakistan 6 0.3 0 19 41 Portugal 6 0.3 1 51 Source: http://www.doksinet 42 Slovenia 6 0.3 0 81 43 Colombia 5 0.2 1 4 44 Egypt 5 0.2 2 82 45 Mexico 5 0.2 0 32 46 Thailand 5 0.2 1 121 47 Saudi Arabia 4 0.2 0 53 48 Uganda 4 0.2 1 213 49 Croatia 3 0.1 0 8 50 Serbia 3 0.1 0 0 51 Bangladesh 2 0.1 1 178 52 Cote Ivoire 2 0.1 0 31 53 Cuba 2 0.1 0 76 54 Iraq 2 0.1 1

3 55 Kazakhstan 2 0.1 1 25 56 Lithuania 2 0.1 1 33 57 Slovakia 2 0.1 0 1 58 Trinid & Tobago 2 0.1 0 17 59 Venezuela 2 0.1 0 16 60 Zimbabwe 2 0.1 0 8 61 Azerbaijan 1 0 1 25 62 Burkina Faso 1 0 0 0 63 Cambodia 1 0 0 13 64 Cameroon 1 0 0 0 65 Chile 1 0 0 7 66 Congo 1 0 0 3 Source: http://www.doksinet 67 Cyprus 1 0 0 11 68 Ethiopia 1 0 0 0 69 French Guiana 1 0 0 0 70 Indonesia 1 0 1 35 71 Jamaica 1 0 0 1 72 Jordan 1 0 0 0 73 Lebanon 1 0 0 2 74 Libya 1 0 0 1 75 Luxembourg 1 0 0 33 76 Martinique 1 0 0 2 77 Mongol Peo Rep 1 0 0 2 78 Peru 1 0 0 7 79 Philippines 1 0 0 13 80 Rep of Georgia 1 0 0 34 81 Tunisia 1 0 0 0 82 U Arab Emirates 1 0 0 9 83 Ukraine 1 0 0 1 84 Vietnam 1 0 0 106 85 Yemen 1 0 0 38 86 Yugoslavia 1 0 0 41 87 Zambia 1 0 0 8 Source: http://www.doksinet Author wise Distribution

of publications - 8056 Ranking of Authors based on Publications Table 4 indicates ranking of authors by number of publications. Authors “[Anonymous]” published highest number of articles for the study period with 20 records, next consecutive author Larski Z are published next highest number of articles for the study period with 14 records. PeirisJSM having highest Global Citation Scores of 537with just 6 publications followed by McFadden G is having Global Citation Score of 404 with just 5 publications, Thus the most-cited authors are distinguished from the most-published ones. It is found from the analysis that Lotka’s law may not be applicable with regard to author productivity in proliferation of research in Virology as the research papers equally distributed by a large number of authors. sl.no Author Recs Percent TLCS TLCS/t TLCSx TGCS TGCS/t TLCR TLCSb TLCSe 1 [Anonymous] 20 1 0 0 0 0 0 1 0 2 Larski Z 14 0.7 5 0.52 4 5 0.52 6 4 3 Enserink

M 10 0.5 2 0.36 2 27 3.69 0 0 4 Pennazio S 9 0.4 5 0.47 0 21 2.77 5 1 5 Carman WF 8 0.4 15 2.51 11 98 18.19 9 3 6 Doerr HW 8 0.4 5 0.45 2 90 11.36 3 1 7 Katze MG 8 0.4 2 1 2 54 21.64 1 0 8 Brooks CL 7 0.3 9 2.19 3 229 47.4 12 3 9 Corey L 7 0.3 1 0.11 1 189 42.46 3 1 1 Source: http://www.doksinet 10 de Lamballerie X 7 0.3 2 0.42 1 71 19.36 2 0 11 Wald A 7 0.3 4 0.71 1 144 36.69 3 1 12 De Meyer S 6 0.3 1 0.5 0 11 5.83 0 13 Enquist LW 6 0.3 2 0.18 1 131 15.6 1 14 Kieffer TL 6 0.3 1 0.5 0 13 7.83 1 15 Niesters HGM 6 0.3 20 2.12 19 124 12.58 4 8 16 Peiris JSM 6 0.3 4 0.87 3 537 94.46 2 2 17 Picchio G 6 0.3 1 0.5 0 11 4.83 0 18 Twarock R 6 0.3 19 2.33 11 95 13.45 8 19 Adda N 5 0.2 1 0.5 0 9 3.83 0 20 Allwinn R 5 0.2 4 0.34 1 38 5.66 2 21 Bartels DJ 5 0.2 1 0.5 0 9 3.83 0 22 Bartenschlager R

5 0.2 2 0.33 1 136 31.55 1 0 23 Cohen J 5 0.2 1 0.13 1 16 2.53 0 1 24 Dillner J 5 0.2 1 0.08 1 71 8.4 0 1 25 Fouchier RAM 5 0.2 1 0.33 1 81 25.67 0 0 26 Gunson RN 5 0.2 13 2.14 9 78 14.59 7 2 2 27 Johnson JE 5 0.2 6 0.86 2 151 29.3 1 2 1 28 King DJ 5 0.2 4 0.38 1 76 8.2 3 1 1 29 Kuiken T 5 0.2 2 0.48 2 68 16.57 0 1 0 6 1 5 1 0 Source: http://www.doksinet 30 Leveque N 5 0.2 11 2.75 7 95 26.17 5 1 31 Locarnini S 5 0.2 7 0.82 6 157 18.96 1 3 0 32 McFadden G 5 0.2 4 0.4 2 404 41.28 5 3 0 33 Moradpour D 5 0.2 9 1 6 144 18.31 6 3 3 34 Nagy PD 5 0.2 5 0.5 1 171 17.97 7 5 35 Osterhaus ADME 5 0.2 2 0.48 2 94 23.24 0 1 36 Pawlotsky JM 5 0.2 4 0.62 3 93 17.31 2 2 37 Preiser W 5 0.2 2 0.2 2 93 9.88 1 0 38 Seal BS 5 0.2 4 0.38 1 81 8.44 3 1 39 Taubenberger JK 5 0.2 1 0.17 0 115 31.49 3 1 40

Uyar Y 5 0.2 0 0 0 11 3.2 1 41 Zandotti C 5 0.2 1 0.33 1 106 18 1 0 42 Zhang J 5 0.2 1 0.2 1 32 9.34 1 0 43 Andreoletti L 4 0.2 7 2.08 4 49 18.5 5 44 Berger A 4 0.2 2 0.28 2 98 13.97 0 0 0 45 Blum HE 4 0.2 7 0.67 5 79 7.47 6 3 1 46 Brown CC 4 0.2 4 0.38 1 70 7.34 3 1 1 47 Charrel RN 4 0.2 1 0.33 1 22 8.67 1 48 Francis J 4 0.2 8 0.88 4 121 13.07 2 5 0 49 Gazin C 4 0.2 1 0.33 1 22 8.67 1 0 1 Source: http://www.doksinet 50 Gould EA 4 0.2 0 0 0 30 9.33 1 0 51 Henquell C 4 0.2 1 0.17 0 92 10.73 2 0 52 Izopet J 4 0.2 0 0 0 91 11.05 3 0 53 Jacobson IM 4 0.2 1 0.11 1 155 21.67 1 0 54 Kapczynski DR 4 0.2 1 0.1 0 94 10.51 1 1 0 55 Kauffman RS 4 0.2 1 0.5 0 6 5 1 56 Kirn D 4 0.2 7 0.78 3 131 14.38 4 4 0 57 Korth MJ 4 0.2 2 1 2 47 21 1 0 58 Li J 4 0.2 1 0.17 0 91 16.42 2 1 59 Li Y 4

0.2 0 0 0 39 15.28 3 0 60 Lina B 4 0.2 5 1 4 65 11.5 1 1 1 61 Liu TC 4 0.2 7 0.78 3 131 14.38 4 4 0 62 Liu Y 4 0.2 1 0.14 0 47 7.92 1 1 63 Masliah E 4 0.2 0 0 0 43 9.85 0 0 64 Molloy S 4 0.2 0 0 0 0 0 0 0 65 Moyer SA 4 0.2 6 0.63 0 83 9.63 6 3 66 Neyts J 4 0.2 1 0.09 0 63 15.2 3 0 67 Ninove L 4 0.2 1 0.33 1 22 8.67 1 68 Nougairede A 4 0.2 1 0.33 1 22 8.67 1 69 Pietschmann T 4 0.2 1 0.33 1 58 20.5 1 0 Source: http://www.doksinet 70 Pillay D 4 0.2 1 0.13 1 156 24.49 0 0 71 Rabenau HF 4 0.2 1 0.17 1 29 4.67 0 0 72 Reddy VS 4 0.2 8 1.19 3 204 38 3 3 3 73 Rice CM 4 0.2 2 0.33 1 113 31.63 0 0 0 74 Scholthof KBG 4 0.2 3 0.37 0 41 11.59 4 1 1 75 Shih SR 4 0.2 3 0.34 3 53 7.29 1 2 0 76 Simmonds P 4 0.2 7 1 6 172 26.33 1 0 5 77 Smallwood S 4 0.2 6 0.63 0 83 9.63 6 3 0 78 Stoll-Keller

F 4 0.2 1 0.13 1 21 6.22 1 0 79 van Loon AM 4 0.2 14 1.31 13 90 8.44 0 2 80 Wang HL 4 0.2 0 0 0 103 15.98 3 0 81 Watanabe M 4 0.2 0 0 0 47 10.67 3 0 82 Wedemeyer H 4 0.2 1 0.5 1 49 26.67 3 0 83 Adiwijaya BS 3 0.1 0 0 0 8 5.33 1 84 Arvin AM 3 0.1 1 0.14 1 86 9.17 0 85 Ashfaq UA 3 0.1 0 0 0 19 9.5 1 86 Bailly JL 3 0.1 1 0.17 0 8 1.4 2 0 87 Balazs E 3 0.1 1 0.14 0 30 3.78 1 1 0 88 Barrett JW 3 0.1 4 0.4 2 365 36.95 0 3 0 89 Beer M 3 0.1 0 0 0 67 14.63 4 0 0 0 1 Source: http://www.doksinet 90 Billaud G 3 0.1 1 0.33 1 19 3.83 1 0 91 Block TM 3 0.1 0 0 0 25 3.89 1 0 92 Brister JR 3 0.1 0 0 0 15 5.67 0 93 Busch M 3 0.1 2 0.2 0 14 1.65 2 94 Caglayik DY 3 0.1 0 0 0 6 2 1 95 Calvez V 3 0.1 1 0.13 1 94 10.3 96 Canard B 3 0.1 0 0 0 90 97 Casper C 3 0.1 0 0 0 98 Cevik B 3 0.1 4 0.41 99

Chan HLY 3 0.1 0 100 Chan KP 3 0.1 101 Chayama K 3 0.1 2 0 0 1 0 14.13 1 0 50 10.7 0 0 55 6.52 5 2 0 0 0 33 3.34 0 0 0 1 0.11 1 53 7.99 1 1 2 0.33 1 68 10.59 3 0 • Authorship pattern Table 7 shows that authorship pattern S. No Authorship Pattern Publications % No. of Authors Source: http://www.doksinet 1 Single Author 400 2 Double Authors 311 3 Three Authors 272 4 Four Authors 220 5 Five Authors 179 6 Six Authors 170 7 Seven Authors 126 8 Eight Authors 110 9 Nine Authors 71 10 Ten & Above Authors 166 Total Single Vs. Multiple Authors 2025 19.75 15.36 13.43 10.86 8.84 8.40 6.22 5.43 3.51 8.20 100 400 622 816 880 895 1020 882 880 639 1022 8056 Source: http://www.doksinet It is found from the study that multiple authors’ research is ensured between the authors in Virology research as 80.25% of publications made by multiple authors Table 8 shows that Single Vs Multiple authors

Authorship Patterns Publications % Cum % Single Author 400 19.75 19.75 Multiple Authors Total 1625 2025 80.25 100 100 It is found from the study that collaborative research is ensured between the authors in Virology research as 19.75% of publications made by single authors It is also found that the papers published by more than 10 authors. Highly Cited Papers Top 50 Highly Cited Papers The below table reveal the articles are having highest Global Citation Score and also highlight the cited references appended by these research papers. The research paper titled “Electrical detection of single viruses” scored GCS of 510 while the 50th ranked paper “Comparative genomics reveals mechanism for short-term and long-term clonal transitions in pandemic Vibrio cholerae,” having a GCS of 86. Source: http://www.doksinet sl.no Date / Author / Journal LCS GCS LCR CR 0 510 1 23 33 478 0 209 2 474 2 34 2 340 0 25 563 Patolsky F, Zheng GF, Hayden O,

Lakadamyali M, Zhuang XW, et al. Electrical detection of single viruses 1 Proceedings of the national academy of sciences of the united states of america. 2004 sep 28; 101 (39): 14017-14022 178 Mackay IM, Arden KE, Nitsche A 2 Real-time PCR in virology Nucleic acids research. 2002 mar 15; 30 (6): 1292-1305 696 Longini IM, Nizam A, Xu SF, Ungchusak K, Hanshaoworakul W, et al. 3 Containing pandemic influenza at the source Science. 2005 AUG 12; 309 (5737): 1083-1087 356 Nicholls JM, Poon LLM, Lee KC, Ng WF, Lai ST, et al. 4 Lung pathology of fatal severe acute respiratory syndrome Source: http://www.doksinet Lancet. 2003 may 24; 361 (9371): 17731778 441 Lai CL, Ratziu V, Yuen MF, Poynard T 5 Viral hepatitis B 3 334 1 65 4 312 0 274 0 253 0 188 2 243 0 33 2 224 0 29 Lancet. 2003 DEC 20; 362 (9401): 2089-2094 295 Seet BT, Johnston JB, Brunetti CR, Barrett JW, Everett H, et al. 6 Poxviruses and immune evasion Annual review of immunology. 2003; 21: 377-423

4 Garcia-Arenal F, Fraile A, Malpica JM 7 Variability and genetic structure of plant virus populations Annual review of phytopathology. 2001; 39: 157-186 538 Kageyama T, Shinohara M, Uchida K, Fukushi S, Hoshino FB, et al. 8 Coexistence of multiple genotypes, including newly identified genotypes, in outbreaks of gastroenteritis due to Norovirus in Japan Journal of clinical microbiology. 2004 jul; 42 (7): 2988-2995 9 763 Kilbourne ED Source: http://www.doksinet Influenza pandemics of the 20th century Emerging infectious diseases. 2006 jan; 12 (1): 9-14 169 Osmanov S, Pattou C, Walker N, Schwardlander B, Esparza J 10 Estimated global distribution and regional spread of HIV-1 genetic subtypes in the year 2000 2 221 0 20 7 206 0 30 0 203 0 43 3 187 1 131 Journal of acquired immune deficiency syndromes. 2002 feb 1; 29 (2): 184-190 318 Griffin SDC, Beales LP, Clarke DS, Worsfold O, Evans SD, et al. 11 The p7 protein of hepatitis C virus forms an ion channel

that is blocked by the antiviral drug, Amantadine FEBS LETTERS. 2003 JAN 30; 535 (13): 34-38 647 Cilibrasi R, Vitanyi PMB 12 Clustering by compression Ieee transactions on information theory. 2005 apr; 51 (4): 1523-1545 1243 Liaw YF, Chu CM 13 Hepatitis B virus infection Lancet. 2009 FEB 14; 373 (9663): 582592 Source: http://www.doksinet 95 Dechecchi MC, Melotti P, Bonizzato A, Santacatterina M, Chilosi M, et al. 14 Heparan sulfate glycosaminoglycans are receptors sufficient to mediate the initial binding of adenovirus types 2 and 5 2 186 0 45 1 178 0 43 9 151 0 10 0 145 0 49 4 142 1 46 Journal of virology. 2001 sep; 75 (18): 8772-8780 1147 Matthijnssens J, Ciarlet M, Rahman M, Attoui H, Banyai K, et al. 15 Recommendations for the classification of group A rotaviruses using all 11 genomic RNA segments archives of virology. 2008 aug; 153 (8): 1621-1629 1022 Mahony J, Chong S, Merante F, Yaghoubian S, Sinha T, et al. 16 Development of a respiratory

virus panel test for detection of twenty human respiratory viruses by use of multiplex PCR and a fluid microbead-based assay Journal of clinical microbiology. 2007 sep; 45 (9): 2965-2970 388 Cullen BR 17 Nuclear mRNA export: insights from virology trends in biochemical sciences. 2003 aug; 28 (8): 419-424 686 Hayes EB, Sejvar JJ, Zaki SR, Lanciotti RS, Bode AV, et al. 18 Virology, pathology, and clinical manifestations of West Nile virus disease Source: http://www.doksinet Emerging infectious diseases. 2005 aug; 11 (8): 1174-1179 895 Manning A, Russell V, Eastick K, Leadbetter GH, Hallam N, et al. 19 Epidemiological profile and clinical associations of human bocavirus and other human parvoviruses 7 140 0 15 1 138 0 124 1 137 0 288 2 134 1 139 3 134 2 242 Journal of infectious diseases. 2006 nov 1; 194 (9): 1283-1290 484 Keeffe EB, Dieterich DT, Han SHB, Jacobson IM, Martin P, et al. 20 A Treatment Algorithm for the Management of Chronic Hepatitis B Virus

Infection in the United States Clinical gastroenterology and hepatology. 2004 feb; 2 (2): 87-106 221 Ablashi DV, Chatlynne LG, Whitman JE, Cesarman E 21 Spectrum of Kaposis sarcomaassociated herpesvirus, or human herpesvirus 8, diseases Clinical microbiology reviews. 2002 jul; 15 (3): 439-+ 108 Rosenberg S 22 Recent advances in the molecular biology of Hepatitis C virus Journal of molecular biology. 2001 oct 26; 313 (3): 451-464 23 749 Condit RC, Moussatche N, Traktman P Source: http://www.doksinet In a nutshell: Structure and assembly of the vaccinia virion Advances in virus research, vol 66. 2006; 66: 31-+ 14 Sobrino F, Saiz M, Jimenez-Clavero MA, Nunez JI, Rosas MF 24 Foot-and-mouth disease virus: a long known virus, but a current threat 0 129 0 254 3 129 0 52 0 126 0 93 2 125 1 38 VETERINARY RESEARCH. 2001 JAN-FEB; 32 (1): 1-30 522 Guirakhoo F, Pugachev K, Zhang Z, Myers G, Levenbook I, et al. 25 Safety and efficacy of chimeric yellow fever-dengue

virus tetravalent vaccine formulations in nonhuman primates JOURNAL OF VIROLOGY. 2004 MAY; 78 (9): 4761-4775 760 Wong SSY, Yuen K 26 Avian influenza virus infections in humans CHEST. 2006 JAN; 129 (1): 156-168 1491 Cowling BJ, Chan KH, Fang VJ, Lau LLH, So HC, et al. 27 Comparative Epidemiology of Pandemic and Seasonal Influenza A in Households. New england journal of medicine. 2010 jun 10; 362 (23): 2175-2184 Source: http://www.doksinet 188 Lopman BA, Brown DW, Koopmans M 28 Human caliciviruses in Europe 1 124 0 179 3 115 2 19 1 114 0 36 1 113 0 23 4 110 0 94 Journal of clinical virology. 2002 apr; 24 (3): 137-160 493 Weinberg GA, Erdman DD, Edwards KM, Hall CB, Walker FJ, et al. 29 Superiority of reverse-transcription polymerase chain reaction to conventional viral culture in the diagnosis of acute respiratory tract infections in children Journal of infectious diseases. 2004 feb 15; 189 (4): 706-710 373 Westland CE, Yang HL, Delaney WE, Gibbs CS,

Miller MD, et al. 30 Week 48 resistance surveillance in two phase 3 clinical studies of adefovir dipivoxil for chronic hepatitis B Hepatology. 2003 jul; 38 (1): 96-103 747 Cane P, Chrystie I, Dunn D, Evans B, Geretti AM, et al. 31 Time trends in primary resistance to HIV drugs in the United Kingdom: multicentre observational study British medical journal. 2005 dec 10; 331 (7529): 1368-1371 32 138 McCormick JB, Fisher-Hoch SP Source: http://www.doksinet Lassa fever Arenaviruses i. 2002; 262: 75-109 137 Pogue GP, Lindbo JA, Garger SJ, Fitzmaurice WP 33 Making an ally from an enemy: Plant virology and the new agriculture 2 108 1 144 0 108 0 38 0 106 1 98 0 101 0 60 Annual review of phytopathology. 2002; 40: 45-74 391 Conwell CC, Vilfan ID, Hud NV 34 Controlling the size of nanoscale toroidal DNA condensates with static curvature and ionic strength Proceedings of the national academy of sciences of the united states of america. 2003 aug 5; 100 (16):

9296-9301 765 de Jong MD, Hien TT 35 Avian influenza A (H5N1) Journal of clinical virology. 2006 jan; 35 (1): 2-13 128 Emerson BC, Paradis E, Thebaud C 36 Revealing the demographic histories of species using DNA sequences Source: http://www.doksinet Trends in ecology & evolution. 2001 dec; 16 (12): 707-716 381 Kazmierski W, Bifulco N, Yang HB, Boone L, DeAnda F, et al. 37 Recent progress in discovery of smallmolecule CCR5 chemokine receptor ligands as HIV-1 inhibitors 2 101 0 154 2 99 0 134 1 97 0 64 1 96 0 111 1 96 0 44 Bioorganic & medicinal chemistry. 2003 jul 3; 11 (13): 2663-2676 134 Smith GA, Enquist LW 38 Break ins and break outs: Viral interactions with the cytoskeleton of mammalian cells Annual review of cell and developmental biology. 2002; 18: 135161 617 Stern CD 39 The chick: A great model system becomes even greater Developmental cell. 2005 jan; 8 (1): 917 136 Gandhi RT, Walker BD 40 Immunologic control of HIV-1 Annual review

of medicine. 2002; 53: 149-172 41 680 Beasley DWC, Whiteman MC, Zhang SL, Huang CYH, Schneider BS, et al. Source: http://www.doksinet Envelope protein glycosylation status influences mouse neuroinvasion phenotype of genetic lineage 1 West Nile Virus strains Journal of virology. 2005 jul; 79 (13): 8339-8347 425 Isken O, Grassmann CW, Sarisky RT, Kann M, Zhang S, et al. 42 Members of the NF90/NFAR protein group are involved in the life cycle of a positive-strand RNA virus 4 94 0 28 0 94 1 38 1 93 0 38 0 92 1 41 EMBO JOURNAL. 2003 NOV 3; 22 (21): 5655-5665 480 Wallis RS, Kyambadde P, Johnson JL, Horter L, Kittle R, et al. 43 A study of the safety, immunology, virology, and microbiology of adjunctive etanercept in HIV-1-associated tuberculosis AIDS. 2004 JAN 23; 18 (2): 257-264 305 Li HJ, Dummer JS, Estes WR, Meng SF, Wright PF, et al. 44 Measurement of human cytomegalovirus loads by quantitative real-time PCR for monitoring clinical intervention in transplant

recipients Journal of clinical microbiology. 2003 jan; 41 (1): 187-191 959 Pugach P, Marozsan AJ, Ketas TJ, Landes EL, Moore JP, et al. 45 HIV-1 clones resistant to a small molecule CCR5 inhibitor use the inhibitor-bound form of CCR5 for entry Source: http://www.doksinet VIROLOGY. 2007 APR 25; 361 (1): 212-228 209 Varaklioti A, Vassilaki N, Georgopoulou U, Mavromara P 46 Alternate translation occurs within the core coding region of the hepatitis C viral genome 2 91 0 36 0 90 1 25 0 88 0 26 1 86 1 48 Journal of biological chemistry. 2002 may 17; 277 (20): 17713-17721 1431 van Kuppeveld FJM, de Jong AS, Lanke KH, Verhaegh GW, Melchers WJG, et al. 47 Prevalence of xenotropic murine leukaemia virus-related virus in patients with chronic fatigue syndrome in the Netherlands: retrospective analysis of samples from an established cohort British medical journal. 2010 feb 25; 340: art. No C1018 236 Pilcher CD, McPherson JT, Leone PA, Smurzynski M, Owen-ODowd J, et al.

48 Real-time, universal screening for acute HIV infection in a routine HIV counseling and testing population Jama-journal of the american medical association. 2002 jul 10; 288 (2): 216221 379 Fauci AS 49 HIV and AIDS: 20 years of science Nature medicine. 2003 jul; 9 (7): 839843 Source: http://www.doksinet 1342 Chun J, Grim CJ, Hasan NA, Lee JH, Choi SY, et al. 50 Comparative genomics reveals mechanism for short-term and long-term clonal transitions in pandemic Vibrio cholerae 0 86 0 37 proceedings of the national academy of sciences of the united states of america. 2009 sep 8; 106 (36): 15442-15447 Among the Top 50 Cited research papers, the article “Electrical detection of single viruses of” by Patolsky F, Zheng GF, Hayden O, Lakadamyali M, Zhuang XW, et al. though the paper scored 510 Global Citation Scores and 0 Local Citation Scores. CHAPTER – IV FINDINGS AND CONCLUSION Scientometric research has developed a body of theoretical knowledge and a group of

techniques and applications based on the distribution of bibliographic data. The wider application of Scientometric techniques is leading to the development of a new and more Source: http://www.doksinet precise technique. Hopefully, the on-going theoretical work will point the way to more innovative techniques. Scientometric data provide precise and accurate observation. A major to the Scientometrician is to continue to develop the techniques which will be more reliable and useful for evaluation and prediction, because Scientometric data mirror the actual published results of the work of researchers. Based on the analysis undertaken the present study, the following findings are drawn.  The findings of global research productivity in virology has the highest publication as 220 in the year 2011 with 1272 Global Citation Scores followed by 214 papers in 2012 with 297 Global Citation Score and 200 papers in 2010 with 1695 Global Citation Scores. The lowest publication is 132 in

2001 with 3063 Global Citation Scores  The authorship pattern of global research productivity on virology has identified that majority of papers are multi-authored. It is found from the analysis that Lotka’s law may not be applicable with regard to author productivity in proliferation of research in virology as the research papers equally distributed by a large number of authors.  Authors “Anonymous” published highest number of articles for the study period with 20 records, next author Larski.Z published next highest number of articles for the study period with 14 records. PeirisJSM having highest Global Citation Scores of 537 with just 6 publications next McFadden having Global Citation Score of 404 with just 5 publications, while Molloy S having lowest Global Citation Score of 0 with just 4 Source: http://www.doksinet publications. Thus the most-cited authors are distinguished from the most-published ones.  The study found that the total research output of the

virology for the study period (2001 – 2012) published in 758 journals. As the major portion of the research productivity (55%) covered by 100 journals that is coincide with the theory of Bradford’s Law of scattering of journals in research productivity.Top 101 institutions were contributed 2025(57.7%) articles of the total research productivity  The trend towards collaborative research is gaining day-by-day. Every work of researchers depends purely on the library because it contains more springs forth information. This study has highlighted quantitatively the contributions made by the global researchers during 2001-2012 as reflected in Web of Science database. During 12 years period (2001– 2012) global contributions in terms of number of publications is significant. A comparison of Global output in relation to the Indian output may help in understanding the contribution in a better angle. Though the records available in the Web of Science database reveal a large number, it is

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