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Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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), 979-996. doi:10.1007/s11192-016-2071-6
The final paper is available at: http://link.springer.com/article/10.1007/s11192-016-2071-6
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
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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-group-
based 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
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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 'macro-
disciplines' 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
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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 record-
matching 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 1996-2014 by at least one
Slovenian scientist registered in an agricultural research group in 2015. 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.
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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 11 163 779 374 181 95
Plant Production 25 236 1161 216 165 163
Animal Production 14 208 820 346 104 94
Veterinary Science 17 122 660 167 126 85
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.
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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.
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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.
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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. Circle-
size 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
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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.
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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).
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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.
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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 co-
assigned 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
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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 data-
disambiguation (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)
Scientometrics (2016) Volume 109, Issue 2, pp 979–996
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.
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