Mapping and classification of agriculture in Web of Science: other subject categories and research fields may benefit

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1 Mapping and classification of agriculture in Web of Science: other subject categories and research fields may benefit Tomaz Bartol 1, Gordana Budimir 2, Primoz Juznic 3, Karmen Stopar 1 Abstract Fields of science (FOS) can be used for the assessment of publishing patterns and scientific output. To this end, WOS JCR (Web of Science/Journal Citation Reports) subject categories are often mapped to Frascati-related OECD FOS (Organization for Economic Co-operation and Development). Although WOS categories are widely employed, they reflect agriculture (one of six major FOS) less comprehensively. Other fields may benefit from agricultural WOS mapping. The aim was to map all articles produced nationally (Slovenia) by agricultural research groups, over two decades, to their corresponding journals and categories in order to visualize the strength of links between the categories and scatter of articles, based on WOS-linked raw data in COBISS/SciMet portal (Co-operative Online Bibliographic System and Services/Science Metrics) and national CRIS - Slovenian Current Research Information System (SICRIS). Agricultural groups are mapped into four subfields: Forestry & Wood Science, Plant Production, Animal Production, and Veterinary Science. Food science is comprised as either plant- or animal-product-related. On average, 50% of relevant articles are published outside the scope of journals mapped to WOS agricultural categories. The other half are mapped mostly to OECD Natural-, Medical- and Health Sciences, and Engineering-and-Technology. A few selected journals and principal categories account for an important part of all relevant documents (core). Even many core journals/categories as ascertained with power laws (Bradford's law) are not mapped to agriculture. Research-evaluation based on these classifications may underestimate multidisciplinary dimensions of agriculture, affecting its position among scientific fields and also subsequent funding if established on such ranking. Keywords: classification, fields of science, research evaluation, power laws, agriculture, research groups Introduction Research Background and Motivation In national research evaluation schemes, research fields and subfields are often evaluated uniformly within each major field of science. Publication patterns, however, tend to be specific within each individual field, such as agriculture, medicine, the social sciences, etc. Because of different publishing practices it is thus often difficult to uniformly and consistently assess publication activity across these fields. In an attempt at more objective assessments, the citation database Web of Science (WOS) uses a principle of classifying journals into subject categories. WOS editors thus attempt to offer balanced coverage within each individual category (Testa 2003). The procedures have been developed by methods begun over 40 years ago. Categories were established, then new journals were assigned one at a time based upon all relevant citation data (Pudovkin and Garfield 2002) Self-archived authors' version of the paper: Bartol, T.; Budimir, G.; Juznic, P. & Stopar, K. (2016). Mapping and classification of agriculture in Web of Science: other subject categories and research fields may benefit. Scientometrics, 109(2), doi: /s The final paper is available at: 1 Agronomy Department, Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, 1000 Ljubljana, Slovenia 2 Institute of Information Science, Presernova 17, 2000 Maribor, Slovenia 3 Department of Library and Information Science and Book Studies, Faculty of Arts, University of Ljubljana, Askerceva 2, 1000 Ljubljana, Slovenia

2 Despite the fact that WOS journal classification system, as well as coverage (Larsen and von Ins 2010), is frequently questioned, much scientometric research has been conducted through this system. It offers the possibility of comparing experiments on similar principles over long periods of time and has been mapped to different international classification schemes such as the Fields of Science and Technology (FOS) classification (a.k.a Frascati classification) of the OECD (Organization for Economic Co-operation and Development). The aim of classification is to ensure international comparisons of R&D (Research and Development) expenditures in the public sector (OECD, 2007) in OECD member countries. This scheme is used in many countries and is employed for evaluation purposes in national current research information systems (CRIS). The appropriate mapping of OECD FOS to the corresponding WOS categories has been put into practice by WOS editors. All WOS categories are represented in the mapping (Thomson Reuters 2015). WOS is the most frequently employed database for the purposes of research evaluation, complemented in the last decade by Scopus. Both databases offer specific functionalities. Agriculture is often presented and subsequently assessed as a principal scientific field. It contains several subfields related to animal-, plant/crop-production & health, food & nutrition, and forestry, according to all three well-known principal international information systems CAB Abstracts, Agris, and Agricola. In national environments where most academic research is financed through publicly funded schemes, it is of utmost importance that each major research field and subfield receives its due share of attention according to its real scope, including a balanced allocation of resources in agricultural research (Vanloqueren & Baret 2009). Such decision-making should take into account different levels of national research, for example, output from different research groups (Jarneving 2009, Cova et al. 2015). Our aim in this paper is to gain a better insight into the published output in agriculture, with an emphasis on research groups that are active in the following major subfields within agriculture: Forestry & Wood Science, Plant Production, Animal Production, and Veterinary Science, according to the national categorization scheme in Slovenia, which is based on the aforementioned OECD/Frascati FOS. The research groups are not strictly linked to an institution but instead connect scientists who exhibit specific publishing characteristics in a given agricultural subfield. In this way, research-groupbased assessment can offset any bias of a particular agricultural institution. Agricultural institutions can and do employ researchers who are not active in agricultural research. Also, agricultural institutions range from mere teaching departments on one side or large research faculties on the other side, and also include small and specialized research institutes. Such differences could in principle hinder comparison. Even though agriculture is a well-established major field of science, we believe that a substantial part of its relevant research gets published outside its scope and that the current agriculture-related records do not reflect comprehensively the many facets of activities in this scientific area. The widely used WOS-related classification scheme and its generic categories may thus put agricultural sciences at a disadvantage in view of research evaluation - if based solely on scientific fields. To this end, we assess all articles (co)-authored by members of all Slovenian agricultural research groups, over almost two decades. We map these articles to the corresponding WOS journal-categories in order to visualize the strength of particular categories and to identify the links between these categories. In addition, we assume that the distribution of both the journals as well as subjects (categories) follows some characteristic principles of inverse relationship. Thus, we also aim to investigate how the core group of agriculture-related articles or journals is attributed to the existing agricultural classifications, or, perhaps, if the principal information resources are assigned to other major fields aside from agriculture. Review of Literature In our brief literature review here, we address articles that tackle agricultural and related mapping. For the purposes of consistency and in view of different terminology relating to WOS (for example, Science Citation Index Expanded, (SCI/SCIE), Web of Knowledge, Journal of Citation Reports (JCR), Thomson Reuters) we refer to all of these WOS-associated items as WOS. The WOS-based assessments are the most widely used method (Yan et al. 2013) which, although unreliable for individual papers, produce good results for large numbers. An additional advantage is that the

3 categories are defined at the subdiscipline (subfield) level (Rafols et al. 2012). This is important for the detection of specific publishing patterns. Namely, researchers belonging to a particular scientific (sub) field, within a broader field, also publish outside that field (Abramo et al. 2012). Such profiles are of primary importance in scientometric evaluation, since standards of scientometric indicators can be set only within subfields (Glänzel and Schubert 2003). Several studies have employed OECD-to-WOS classification mapping. Bornmann and Marx (2015) assessed broader fields such as medical, agricultural and social sciences. Further, in an assessment of South East Europe, Kutlaca et al. (2014) also addressed broader WOS-based areas according to this mapping, including agriculture. The authors reiterated the significance of these data in national R&D (Research and Development) policies. Both databases are sometimes used together to offset disciplinary bias (Klavans and Boyack 2009). Sometimes only Scopus is used in the evaluation of broad categories (Thelwall and Fairclough 2015). Besides the internationally standardized OECD-to-WOS classification mapping, some studies use several other ways of grouping categories in fields of science, each for specific purposes. For example, Chavarro et al. (2014) mapped WOS categories to 18 'disciplines', including agriculture. Acosta et al. (2014) mapped WOS categories to 12 broad disciplines, including agricultural and food sciences. The categories were arranged into 20 'mega-fields' by Schoeneck et al. (2011) and into 18 'macrodisciplines' by Gautam and Yanagiya (2012). On the other hand, instead of using broad database categories, some authors design special search queries to identify more specific fields, for example, agricultural and food science and technology (Borsi and Schubert 2011). All of these different approaches identify scientific fields in different ways, so such assessments cannot be directly compared. Our research also investigates some other specific patterns of information distribution within the subfields of agriculture. In informetric research, the distribution or scatter of items is frequently not linear and exhibits patterns of the so called "power laws" of scatter, with an inverse proportional relationship between the rank and frequency where a limited number of entities have high scientific productivity or impact while the majority have low scientific productivity or impact (Yan et al. 2013). Applying Bradford's law of scatter, Ren et al. (2013) found papers on water resources distributed in more than 98 subject categories. Siegmeier and Möller (2013) detected power laws in organic farming. Also using WOS classification, Toivanen (2014) tested power laws for 'hot-papers' and detected increase in agricultural sciences. We next provide some theoretical framework for the methods used in our research. For the purposes of visualization, Aleixandre et al. (2013) used a network analysis package Pajek (Batagelj and Mrvar 2012) in an experiment that was related to bibliometrics in agriculture (wine). Also using Pajek, Gautam and Yanagiya (2012) included agriculture along with other WOS macro-disciplines and complemented research by VOSviewer (developed by van Eck & Waltman, 2010) as another visualization tool. As ways of counting, since there is no universally accepted criteria, different methods can be applied, most notably fractional counting or whole counting is used. Also, some ranking systems offer both indicators, full as well as fractional (Waltman et al. 2012). Each method has strong and weak aspects, which have been discussed on many other occasions. In the system of Journal Citation Reports, each journal has its ranking according to a category, regardless of the number of categories to which it is assigned. Whole counting or multiple counting both avoid the arbitrariness of assigning a multi-assigned journal to just one subject category (Yan et al. 2013). Whole counting was also used by Jarneving (2009) in assessing national research. Material and Methods Our material was the published output of all research groups in the field of agricultural sciences in Slovenia between 1996 and 2014 based on articles indexed by Web of Science Core Collection (Science Citation Index Expanded (SCI- Expanded), Social Sciences Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI)) and its respective JCR (Journal Citation Reports) classification of journals by Research Areas and Science Categories. In Slovenia, research activities are organized into six major fields of science: (1) Natural Sciences and Mathematics, (2) Engineering Sciences and Technologies, (3) Medical Sciences, (4) Agricultural

4 sciences (Biotechnical sciences), (5) Social Sciences, and (6) Humanities. This classification is roughly based on the OECD Fields of Science as employed in the Slovenian Current Research Information System (Slovenian CRIS or SICRIS). These respective classification codes are assigned to individual researchers, research projects/programs, organizations as well as research groups. This classification is used by the Slovenian Research Agency (SRA) for the purposes of statistics and evaluation of publicly funded research through a nationally unified system of researcher bibliographies. It has been used, for example, in the selection of research project proposals (Juznic et al. 2010) and investigation of co-authorship network of Slovenian researchers (Ferligoj et al. 2015). Researcher bibliographies are collected in the national bibliographic system COBISS (Co-operative Online Bibliographic System and Services) and include scientific articles, proceedings papers, monograph chapters, etc. Special attention is paid to items indexed by WOS, as these are employed as an important criterion in the funding of grants. Records are linked to WOS through complex recordmatching algorithms. The records are controlled on several levels. Researchers are monitored through unique author identifiers (codes). Unique codes are also used for the monitoring of research groups, which are the subject of this analysis, and which are also classified according to the aforementioned six fields of science. The major fields (first-digit level) are further subdivided into subfields. We evaluated all WOS-indexed articles that were co-authored during by at least one Slovenian scientist registered in an agricultural research group in We matched the scientific output to the publishing activity in WOS according to OECD Category to Web of Science Category Mapping 2012 (Thomson Reuters 2015). Corresponding to this scheme, all WOS categories are included (Table 1). These particular agricultural categories were at the center of our study. Relations to other possible (non-agricultural) categories were also investigated, as the categories can be scattered across multiple fields of science. Table 1 OECD Category to Web of Science Category Mapping (WOS category) for Agricultural Sciences Code Description (WOS category) Code Description (WOS category) AF AGRICULTURAL ECONOMICS & POLICY JY FOOD SCIENCE & TECHNOLOGY AE AGRICULTURAL ENGINEERING KA FORESTRY AD AGRICULTURE, DAIRY & ANIMAL SCIENCE MU HORTICULTURE AH AGRICULTURE, MULTIDISCIPLINARY XE SOIL SCIENCE AM AGRONOMY ZC VETERINARY SCIENCES JU FISHERIES Agricultural groups self-classified their principal subject area according to one of the following principal agricultural subfields (second digit level): B01 Forestry, wood and paper technology, B02 Animal production, B03 Plant production, and B04 Veterinarian medicine. The letter B denotes 'agriculture' in the national decoder for the six major scientific fields. Based on the above Web of Science Category Mapping (Table 1) the four agricultural groups are comprehensively represented. Regarding the WOS category Food Science & Technology there exist no distinct 'food' research groups in the agricultural research scheme of Slovenia. Researchers active in food sciences designated their research as pertaining to either 'animal production'/b02 or 'plant production'/b03. This distinction is contingent upon the basic research materials: foods of animal origin, and foods of plant origin. In this sense, the WOS Food Science & Technology can be associated with research groups (Table 2) pertaining to either Plant Production or Animal Production. After the identification of agricultural groups we created an experimental database of articles that had been co-authored by at least one active member of each group. Computer specialists at IZUM (Slovenian Institute of Information Science) prepared a script which included all of the required data, for example, article's bibliographic data in separate columns (title, journal title, unique journal identifier ISSN (International Standard Serial Number), year, etc.), including two-digit WOS journal category code. These data were derived from the national portal COBISS/SciMet, which enabled viewing, analyzing and processing of the data as linked to Web of Science. Journal codes were verified for each particular year under study. Namely, it is possible that a journal, at a certain point in time, modifies or adds a category. Thus, we have identified all categories assigned to a journal, for each respective year under study, and conducted journal-to-category mapping. With the help of a decoder, which we developed for this purpose, we transposed all codes into full category names.

5 Based on this database of all unique articles, we then created four databases (one pertaining to each subfield). Table 2 presents the number of research groups in each of the four fields, number of researchers involved in each field, number of all articles in the subfield and the three most productive or principal groups in each subfield according to the number of articles. We identified 67 active groups. The research outcomes are dominated by a few highly productive groups. Owing to the fact that each researcher in Slovenia is affiliated (with a few minor exceptions) only to one research group, the numbers given represent unique researchers in each group. Table 2 Number of research groups in Slovenia, researchers, and number of all articles in the four respective research subfields, and the first three most productive groups by the number of articles in each respective subfield Research field Research Groups Researchers All Articles 1. group articles 2. group articles 3. group articles Forestry & Wood Science Plant Production Animal Production Veterinary Science For further processing of data in each of the four subfield databases shown in Table 2, we employed the toolbox Bibexcel (Persson 2011), followed by visualization using the program Pajek (Batagelj and Mrvar, 2012). First, we calculated frequency distributions and conducted a subsequent analysis of co-occurrences. In this routine, Bibexcel matched pairs of units from the same metadata field. As a similarity measure, we then used the frequency (raw counts) of co-occurrences of categories. We applied the whole counting method - also for the purposes of consistency. It has been used in previous evaluation of OECD-WOS harmonized research activities in Slovenia. Thus, if a journal was classified with more than one category, we mapped the journal to each category and counted each category once. For a detailed visualization, we selected only the more frequently occurring subject categories (40 such categories) in WOS, in each subfield (for example, animal production, plant production...). Some marginal categories occurred with such low frequency that they could not be reasonably represented. We prepared the visualization with the network analysis package Pajek. In the visualization maps, we represent the categories with circles (nodes or vertices) where the size of a circle depends on the number articles connected in each particular category. The distances between circles indicate the relatedness in the sense of co-occurrence. The tie lines represent the strength of ties between the pairs of categories. This visualization facilitates easy assessment of the strengths of the links (co-classification). In addition to investigating the relationships between subject categories and between the four agricultural subfields, we also explored additional patterns in the information, such as the relationship between rank and frequency (the "power-law"). In informetric distributions, these relationships are frequently inversely proportional. According to the well-known Bradford's law of scatter of articles in journals (Bradford 1934), the journals in a scientific field can be distributed into three groups or zones. Accordingly, the first zone (core or nucleus) of journal titles is usually very small, and the third group is the largest with, for example, only one or two articles pertaining to each distinctive journal title. Each zone contains, roughly, one-third of all articles in a field. The number of journals progresses geometrically and not linearly. Accordingly, the number of articles per journal falls. The total numbers in respective zones depend on a scientific field or specialty. In each of the four subfields, we tested this theoretical power law model on journals as well as respective categories. The results are represented by non-linear (geometrical) inversely-proportional curves which are consistent with such laws. In our Results section that follows, we first present the inverse-proportional patterns of journals - they provide an exploratory insight into the publication patterns in each respective field. This is followed by visualization of co-occurrences of categories in each subfield. The Results section finishes with the presentation of inverse-proportional distribution of categories as this gives and additional important elucidation of the co-occurrences of categories.

6 Results Inverse proportional distribution of principal journals in agricultural research fields In order to offer exploratory insight into the publishing patterns of Slovenian scientists involved in agricultural research groups between 1996 and 2014 we first present the cumulative results for the articles and the respective journals involved. Table 3 presents, for each research field, the five principal journals that published articles by the researchers in the corresponding groups. We identified between 660 and 1161 articles in the respective fields, published in between 248 and 391 different journals. We noticed that a substantial part of articles centers on only a few preferred journals. Table 3 Top five journals (WOS abbreviation (WOS Quartile in 2014)) with the highest number of articles in the four respective research field, all articles in the field, number of categories involved, and total number of different journal titles Forestry & Wood Science (B01) Plant Production (B03) DRVNA IND (Q3) 38 J AGR FOOD CHEM (Q1) 43 EUR J WOOD PROD (Q2) 25 FOOD CHEM (Q1) 38 WOOD RES-SLOVAKIA (Q4) 24 PLANT DIS (Q1) 31 SUMAR LIST (Q4) 21 SCI HORTIC (Q2) 31 FOREST ECOL MANAG (Q1) 19 EUR J HORTIC SCI (Q4) 25 All articles 779 All articles 1161 No. of different categories 97 No. of different categories 91 Different journal titles 286 Different journal titles 391 Animal Production (B02) Veterinary Science (B04) FOLIA MICROBIOL (Q4) 31 SLOV VET RES (Q4) 68 FOOD TECHNOL BIOTECH (Q3) 23 ACTA VET HUNG (Q3) 28 ITAL J ANIM SCI (Q3) 17 ACTA VET-BEOGRAD (Q4) 22 ACTA CHIM SLOV (Q4) 17 ACTA VET BRNO (Q3) 19 MEAT SCI (Q1) 14 VET MICROBIOL (Q1) 16 All articles 820 All articles 660 No. of different categories 105 No. of different categories 69 Different journal titles 361 Different journal titles 248 In each field, the article share of the first five journals is high, and also very similar: 16 % in Forestry & Wood Science, 14 % in Plant Production, and 12 % in Animal Production. In Veterinary Science it is even higher (23 %), which is attributed to abundant publishing in the national journal Slovenian Veterinary Research. This is in fact the only Slovenian WOS journal mapped to agricultural sciences (category Veterinary Sciences). Interestingly, if we disregarded this national journal, the counts for the first five journals in veterinary science would be 16 %, just as in the field of forestry. The distribution of articles in journals exhibits some noteworthy characteristics of the inverse proportional relationship between the rank and frequency, which is very similar in all four of the research fields that we study here.

7 Fig. 1 Scatter of articles per journal title (number of articles per journal-title and the rank of respective journals) in the four research fields We elucidate these characteristics by curves that clearly show that a substantial part of the total articles centers on only a few core journals in each field (Fig. 1). The specific journals that occupy the respective ranks are different in each field. The five principal journals are shown in Table 3 and these are all completely different. The long tails in Fig. 1 show that most journals published only one or two articles. These findings are in an agreement with the Bradford's law of scatter. All four fields under analysis exhibit these characteristics in a very similar way, although the journals are different. In fact, the curves overlap so strongly that it is even difficult to distinctly present, in the same figure, the curvature for each field. Only Veterinary sciences stand out, to some extent, on account of the aforementioned national journal that 'stretches' the Y axis. As shown in Table 1, only 11 different specific categories are provided for the classification of agricultural sciences in the WOS journal classification scheme. Table 3, however, shows that in Animal Production alone the articles were published in 361 different journals, which had been classified with as many as 104 different WOS categories. Even though many journals are classified with more than one category, sometimes pertaining to different major fields of science, it is clear that many articles get published in such journals that are not associated with agriculture. Assessment of the principal WOS categories and their links in each research field We visualized the strength of the particular categories in each field (subfield) as well as links between the categories. These categories are represented with circles (Figs. 2-5). Labels denote the original names of WOS categories. The labels written out in upper case (for example, FORESTRY) represent agricultural categories according to WOS (as harmonized with OECD FOS). The labels written out in lower case (for example, environmental sciences) represent non-agricultural categories. The size of a circle is contingent on the number of articles. Lines represent co-occurrence of categories. In each field, the journals had been classified with more than 90 different categories, except for the field of Veterinary Sciences, which was mapped to only 69 categories. The majority of rare categories occur only twice or even once according to the above-mentioned inverse proportional relationship between the rank and frequency.

8 Forestry and Wood Science Researchers who participated in the forestry groups (co)authored 779 articles published in 286 different journals. Articles were scattered in 97 different journal categories. The highest number of articles was published in journals mapped to WOS subject categories of Forestry and Materials science, paper & wood followed by Plant sciences. Environmental sciences and Ecology also play an important role. The category Forestry features as an agricultural category (upper-case in the Figs.) according to WOS classification scheme. Evidently, wood-related topics are central to forestry research even though the category Materials science, paper & wood is not a designated agricultural category but is assigned to OECD major field of Engineering and Technology. However, wood is a principal tree product linked to forest through technological processes. Strong links (co-occurrence) between Forestry and Materials science, paper & wood indicate that these two categories are frequently co-assigned to the same journal title. On the other hand, forests are composed of trees thus possessing strong connections with Plants sciences, as well as Ecology, and Environmental sciences. In WOS, these are assigned to OECD Natural Sciences. The journals classified with non-agricultural categories thus occupy an important share of forestry-related publishing. Some other agricultural categories are also involved indicating that scientists in forestry research groups in Slovenia are also active in other specialized research fields, for example agricultural chemistry. Fig. 2 Articles published in journals according to Web of Science categories (Forestry and Wood Science). Explanation for Fig. 2-5: Labels written out in upper case represent agricultural categories according to WOS classification. If written out in lower case they represent non-agricultural categories. Circlesize represents the number of articles in each particular category. The lines represent the links between the pairs of categories. Plant Production Researchers in plant production groups (co)authored 1161 articles published in 391 different journal titles. Articles were scattered across 91 different journal categories. Interestingly, the largest group of articles is represented by non-agricultural category Plant sciences (OECD Natural Sciences). As many as 260 articles were published in journals that had been mapped to this category. Even though many of those had been co-classified with Horticulture or Agronomy, more than half had not been co-classified with any of the agricultural categories. Environmental sciences also play an important role (OECD Natural Sciences). Another group emerged, namely the one revolving around the topics of Food science & technology in connection with Agriculture, multidisciplinary, and which is obviously also

9 linked to Chemistry, applied (OECD Natural Sciences) and related Nutrition & dietetics (OECD Medical and Health Sciences). In the scope of plant production research groups, it is possible to discern two major venues of research: one related to plants as an agricultural produce aimed at human consumption, and the one reflecting a more biological frame of plants, for example plant physiology or plant diseases and pests, and respective agricultural implications. Fig. 3 Articles published in journals according to Web of Science categories (Plant production); see Fig. 2 for explanation Animal Production Researchers who participated in animal production groups (co)authored 820 articles in 361 different journals. Articles were scattered across 104 different journal categories. The largest group of articles is mapped to agricultural category Agriculture, dairy & animal science, followed by Food Science & technology and Veterinary sciences. Veterinary topics play a significant role in this group given the strong relationships between animal production and animal health, and also the safety of products of animal origin. We also observed strong publishing in journals classified with non-agricultural Microbiology (OECD Natural Sciences) as well as Biotechnology & applied microbiology (OECD Engineering and Technology), the latter also being connected with Food Science & technology. Many categories are also mapped to OECD Medical and Health Sciences. As was explained in the Methods section, there are no distinctive 'food production' research groups in the agricultural research scheme of Slovenia. Researchers active in the fields of food processing and human nutrition most frequently designate their research groups as pertaining to either animal production or plant production. Consequently, in animal production the Food Science & technology is strongly connected with Agriculture, dairy & animal science.

10 Fig. 4 Articles published in journals according to Web of Science categories (Animal production); see Fig. 2 for explanation Veterinary Science Researchers active in veterinary science research groups (co)authored 660 articles in 248 different journals. Articles occur in 69 different journal categories. Veterinary sciences possess a very obvious central (agricultural) generic category of Veterinary sciences. This is visualized by the fairly obvious largest circle in Fig. 5. Among those, almost seventy were published in the journal Slovenian Veterinary Research, which accounts for 10 % of all articles. This national journal was included in WOS in 2008 and is the only 'agricultural' WOS-indexed journal in Slovenia. The researchers in animal production research groups also publish in this journal, although to a lesser extent. The category Veterinary sciences is strongly linked to agricultural category Agriculture, dairy & animal science, however, the links with a non-agricultural category Microbiology (OECD Natural Sciences) are even more pronounced. Researchers in veterinary sciences publish very frequently in categories which are mapped to OECD Medical and Health Sciences (Toxicology, Pharmacology & pharmacy, Endocrinology & metabolism...) which is expected given the essentially medical nature of veterinary sciences. Some important publishing is also conducted in the frame of other categories within the OECD Natural Sciences (Biotechnology & applied microbiology, Biochemical research methods, Biochemistry & molecular biology).

11 Fig. 5 Articles published in journals according to Web of Science categories (Veterinary Science); see Fig. 2 for explanation Inverse proportional distribution of WOS categories In the first subsection of the Results section, we investigated the patterns of the scatter of articles in different journals without regard to a particular journal category. We found well-expressed characteristics of the inverse proportional relationship between the rank and frequency (Fig. 1). In this final subsection we have also ascertained similar characteristics relative to WOS categories. This design is not completely matched to the aforementioned Bradford law, as each journal can be indexed by two or sometimes more categories. And yet, similar Bradford-like characteristics can be observed. We note again an inversely proportional relationship between the rank and frequency in all four fields under study (Fig. 6). Moreover, the categories that occupy rank 1 are different in each field. For example, in Veterinary sciences, the rank 1 is taken by the "generic" WOS category Veterinary Sciences since the core articles are published in a national and regional veterinary journals (shown in Table 3) which are all mapped to the Veterinary sciences. The prevalence of this principal category is best visible in Fig. 5 where that respective circle is the largest. On the other hand, in Plant production, the rank 1 is occupied by the WOS category Plant sciences, which is not a WOS agricultural category. In Fig. 3 this category is represented by the largest circle. In general, all four fields show essentially a similar inverse distribution: a few categories account for a high share of all documents, whereas most categories are assigned to very few documents each.

12 Fig. 6 Scatter of categories (number of articles per category and the rank of the respective category) in the four research fields: Forestry and Wood Science, Animal Production, Plant Production, and Veterinary Science Figs. 2, 3, 4, and 5 show only the more frequent and thus more representative categories, which are ranked higher, accordingly, in Fig. 6. As was explained with each Figure, the most frequent categories are not always mapped to agricultural sciences. Certain non-agricultural categories frequently co-occur with agricultural categories in the same journal. However, many journals (papers) are only mapped to non-agricultural categories. Note that the agricultural categories in Figs. 2, 3, 4, and 5 are spelled out in upper case, and non-agricultural categories in lower case. Finally, we ascertained the articles that would not be identified as such if based on WOS categorization scheme for agricultural sciences. An approximation of the share of such articles in each field follows: Forestry & Wood Science (65 %), Plant Production (50 %), Animal production (53 %), Veterinary sciences (41 %). For example, in the field of forestry, a significant portion of articles was mapped to journals mapped only to Materials science, paper & wood, Plant sciences, Environmental sciences and Ecology. Here we point out that the WOS category Materials science, paper & wood is mapped to WOS Research Area of Materials science and to the respective OECD Engineering and Technology. Wood technologies are invariably mapped to Forestry in all major agricultural classification schemes (CAB/Cabicodes, US National Agricultural Library Subject Category Codes, Agris/FAO Subject Categories) as pertaining to forest products and respective processing thereof. It seems that the WOS classification scheme aims at offsetting this challenge by frequently co-assigning both Materials science, paper & wood as well as Forestry to the same journal, sometimes only after a certain point in time as is, for example, the case with the European Journal of Wood and Wood Products (a.k.a. Holz als Roh und Werkstoff). Many generic wood-related journals, however, remain unmapped to Forestry. Some very essential categories are not classed as 'agricultural', most notably Plant sciences (OECD Natural sciences). We need to reiterate that the journals mapped to WOS category Plant sciences and which are not co-classified with an agricultural category play a crucial role in the dissemination of outcomes in agricultural plant production. Many are ranked in the first Quartile of the JCR Impact Factor. Some other essential WOS categories, of relevance to agriculture, and which are not coassigned with agricultural categories are mapped to OECD Engineering and Technology, or OECD Medical and Health Sciences. It is thus evident that an important part of legitimate agricultural research will evade detection if based solely on this classification. Let us restate here, in the case of the

13 Slovenian agriculture-related research as much as 50 % of research results are published outside the scope of agricultural sciences and are not detectable through these schemes. Discussion In many countries, database classification systems are regularly used to evaluate the productivity of scientific fields. Most of this sort of evaluation takes into account the given classification schemes provided by database managers. However, an obvious question arises here: which database or information system to choose. For many reasons, Google Scholar is not useful, also as the documents there are not indexed or classified according to scientific fields. On the other hand, in the case of agriculture, there exist major international bibliographic databases that are dedicated principally to agriculture, such as Agris (FAO/Food and Agriculture Organization), Agricola (US/National Agricultural Library), and CAB Abstracts (CABI - Centre for Agriculture and Biosciences International), the latter being the principal global resource for agriculture-related information. These three databases, however, catalog many different document types in many languages, on low restrictive principles, and are not usually used for evaluation purposes. Also, specialized databases cannot be used for a comparison of different scientific fields. Thus, the comprehensive citation databases (Web of Science in our case) remain the only reasonable choice. Despite frequently discussed limitations of schemes in such databases, they nevertheless form the basis for a "uniform" comparison of research outcomes. Our WOS-based results indicate limitations in the use of these schemes, which lies in a possible underrepresentation of some broader fields of science, agriculture in the specific case we studied here. While the documents retrieved within applicable categories will be relevant, many other possibly relevant documents will escape notice. In addition, agricultural research papers published outside the scope of agricultural categories will "boost" the counts in other areas of research. As some previous authors have remarked: "one field's loss will be another field's gain" (Aksnes et al. 2000). A similar research based on Scopus, however, would face other limitations. In this case, the field of agriculture would also include biology (Scopus category of 'Agricultural and Biological Sciences'). Such an assembly would then be too broad. As authors noted more in general, with a small granularity level the field is too heterogeneous (Ruiz- Castillo and Waltman 2015). In the WOS-based evaluations, the assessments frequently focus on categories that are mapped to OECD/Frascati fields of science which can be generated from WOS, but not from Scopus, as the latter is not sufficiently detailed (Kutlaca et al. 2014). Scopus also seems less robust in some other aspects, such as disambiguation of article titles (Valderrama-Zurián et al. 2015), although it does offer more coverage of social sciences and humanities and an enhanced coverage of more local or regional journals (Bartol et al. 2014) which, however, also implies a less restrictive coverage. Our study has thus been performed on WOS as this database still seems to offer a good possibility to uniformly assess the agricultural groups under study. Related scientometric research frequently focuses on institutions. However, in these cases the datadisambiguation (correct identification of relevant items) presents many challenges (Huang et al. 2014). In our study, these limitations were offset by the selection of research groups that was based on "raw data" derived from the portal COBISS/SciMet regulated through a rigorous authority-control of WOS data disambiguation. It is linked to the Slovenian national CRIS (SICRIS), which has been frequently used for the identification of national actors in various scientometric assessments (Vilar et al. 2012). The portal enables efficient downloading and subsequent mapping and visualization of all relevant records, and subsequent evaluation of all nationally established research groups - as active in the field of agriculture. The significance of research groups has also been pointed out, for example, by Albarrán et al. (2011). As has been observed by Bourke and Butler (1998), research activities organized around groups cut across boundaries established by academic structures. The "crossing of boundaries", in our case, was possible by the additional topical enrichment of data on the level of a broader field as well as a lower more specialized level (or subfield), the importance of which was also emphasized by Abramo et al. (2012) and Glänzel and Schubert (2003). The significance of other research fields for the dissemination of agriculture-related results has been detected by other authors. Rinia et al. (2002) noted that the number of agricultural contributions in articles in journals in basic life sciences are perhaps even more important than those in the discipline of agriculture. Plant Sciences were linked to agriculture by Gautam and Yanagiya (2012)

14 and Klavans and Boyack (2009), as well as Jonkers (2009). Relationships between agriculture and biology, environmental science, and biomedicine were noted by Zhang et al. (2010) and Morillo et al. (2003). In our study, we were able to establish such links fairly precisely. In Forestry and Wood Science, a crucial part is played by journals mapped to the major fields (OECD) of Engineering and Technology as well as Natural Sciences. In Animal Production, OECD Medical Sciences are also important. In Plant Production, many journals are mapped only to OECD Natural Sciences and respective "non-agricultural" plant sciences. Veterinary Sciences exhibit very strong publishing participation in OECD Natural Sciences as well as Medical Sciences. We also note that Slovenian agricultural scientists publish predominantly in non-domestic publications (Bartol 2010). WOS indexes only one Slovenian publication mapped to agricultural categories. We have assessed the records we use in line with power-laws, which in scientometric experiments frequently proceed from the Pareto model (Glänzel et al. 2014). We tested the scatter of information using the so-called Bradford type of inverse proportional distribution. All four agricultural fields in our study exhibit very similar non-linear curves. In all four fields, a few principal (core) journals account for roughly one third of all articles published. On the other hand, majority of journals published only one such article. This type of scatter is also evident in journal categories. What is more telling, however, is that the first core-zone also contains journals that have not been classified with any of the agricultural categories of the WOS categorization. To summarize: as much as 50 % of all agriculture-related articles can be found in journals which are not mapped to any of the agricultural categories. Natural Sciences seem to "profit" the most. The real participation of agriculture is thus probably not comprehensively reflected in experiments and such national "case-reports" which rely solely on simple schemes. Conclusions A few selected journals, as well as a few principal categories, account for an important part of all relevant documents in each of the agricultural subfields under study. This pattern conforms to the general principles of power laws of inverse proportional distribution of items. Even "core" journals as well as categories are frequently not mapped to the applicable agricultural categories, contrary to what one might expect. Half of relevant records scattered across hundreds of different journals and dozens of categories would have eluded detection if established on these schemes. This may have critical consequences in some national R&D evaluation systems where fields of science (agriculture in our case) receive their share of attention, and subsequent funding, according to their position in citation databases. The under-representation of agriculture we identify in simple ranking schemes, based on the given "standard" classifications, serves to illustrate a specific case in which the total output of that science is in fact much higher. References Abramo, G., D Angelo, C. A., & Cicero, T. (2012). What is the appropriate length of the publication period over which to assess research performance? Scientometrics, 93(3), doi: /s Acosta, M., Coronado, D., Ferrándiz, E., & León, M. D. (2014). Regional Scientific Production and Specialization in Europe: The Role of HERD. European Planning Studies, 22(5), doi.org/ / Aksnes, D., Olsen, T., & Seglen, P. (2000). Validation of Bibliometric Indicators in the Field of Microbiology: A Norwegian Case Study. Scientometrics, 49(1), doi.org/ /a: Albarrán, P., Ortuño, I., & Ruiz-Castillo, J. (2011). Average-based versus high- and low-impact indicators for the evaluation of scientific distributions. Research Evaluation, 20(4), doi.org/ / x Aleixandre, J. L., Aleixandre-Tudó, J. L., Bolaños-Pizzaro, M., & Aleixandre-Benavent, R. (2013). Mapping the scientific research on wine and health ( ). Journal of Agricultural and Food Chemistry, 61(49), doi.org/ /jf404394e Bartol, T. (2010). Scientometric assessment of publishing patterns and performance indicators in agriculture in the JCEA member countries. Journal of Central European Agriculture, 11(1), 1 9.

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