Research on the effects of collaboration in scientific research has been increasing in recent years. A variety of studies
have been done at the institution and country level, many with an eye toward policy implications. However, the question of
how to identify the most fruitful targets for future collaboration in high-performing areas of science has not been addressed.
This paper presents a method for identifying targets for future collaboration between two institutions. The utility of the
method is shown in two different applications: identifying specific potential collaborations at the author level between two
institutions, and generating an index that can be used for strategic planning purposes. Identification of these potential
collaborations is based on finding authors that belong to the same small paper-level community (or cluster of papers), using
a map of science and technology containing nearly 1 million papers organized into 117,435 communities. The map used here is
also unique in that it is the first map to combine the ISI Proceedings database with the Science and Social Science Indexes
at the paper level.
We compare a new method for measuring research leadership with the traditional method. Both methods are objective and reliable,
utilize standard citation databases, and are easily replicated. The traditional method uses partitions of science based on
journal categories, and has been extensively used to measure national leadership patterns in science, including those appearing
in the NSF Science & Engineering Indicators Reports and in prominent journals such as Science and Nature. Our new method is based on co-citation techniques at the paper level. It was developed with the specific intent of measuring
research leadership at a university, and was then extended to examine national patterns of research leadership. A comparison
of these two methods provides compelling evidence that the traditional method grossly underestimates research leadership in
most countries. The new method more accurately portrays the actual patterns of research leadership at the national level.
This paper introduces a new method for evaluating national publication activities. This new indicator, thought leadership, captures whether the nation is a thought leader (building on the more recently cited literature for that field) or follower
(building on the older cited literature for that field). Publication data for 2003 are used to illustrate which nations tend
to build on the more recent discoveries in chemistry and clinical medicine. Implications for national and laboratory policy
This article describes recent improvements in mapping the world-wide scientific literature. Existing research is extended
in three ways. First, a method for generating maps directly from the data on the relationships between hundreds of thousands
of documents is presented. Second, quantitative techniques for evaluating these large maps of science are introduced. Third,
these techniques are applied to data in order to evaluate eight different maps. The analyses suggest that accuracy can be
increased by using a modified cosine measure of relatedness. Disciplinary bias can be significantly reduced and accuracy can
be further increased by using much lower threshold levels. In short, much larger samples of papers can and should be used
to generate more accurate maps of science.
Authors:Kevin Boyack, Katy Börner, and Richard Klavans
How does our collective scholarly knowledge grow over time? What major areas of science exist and how are they interlinked?
Which areas are major knowledge producers; which ones are consumers? Computational scientometrics — the application of bibliometric/scientometric
methods to large-scale scholarly datasets — and the communication of results via maps of science might help us answer these
questions. This paper represents the results of a prototype study that aims to map the structure and evolution of chemistry
research over a 30 year time frame. Information from the combined Science (SCIE) and Social Science (SSCI) Citations Indexes
from 2002 was used to generate a disciplinary map of 7,227 journals and 671 journal clusters. Clusters relevant to study the
structure and evolution of chemistry were identified using JCR categories and were further clustered into 14 disciplines.
The changing scientific composition of these 14 disciplines and their knowledge exchange via citation linkages was computed.
Major changes on the dominance, influence, and role of Chemistry, Biology, Biochemistry, and Bioengineering over these 30
years are discussed. The paper concludes with suggestions for future work.
Authors:Kevin W. Boyack, Richard Klavans, and Katy Börner
Summary This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird’s eye view of today’s scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect,1 this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science.