R. K. Buter

Technological Relevance of Science: An Assessment of Citation Linkages between Patents and Research Papers

Patent citations to the research literature offer a way for identifying and comparing contributions of scientific and technical knowledge to technological development. This case study applies this approach through a series of analyses of citations to Dutch research papers listed on Dutch-invented and foreign patents granted in the US during the years 1987–1996.First, we examined the general validity and utility of these data as input for quantitative analyses of science-technology interactions. The findings provide new empirical evidence in support of the general view that these citations reflect genuine links between science and technology. The results of the various analyses reveal several important features of industrially relevant Dutch science: (1) the international scientific impact of research papers that are also highly cited by patents, (2) the marked rise in citations to Dutch papers on foreign-invented patents; (3) the large share of author-inventor self-citations in Dutch-invented patents; (4) the growing relevance of the life sciences, (5) an increase in the importance of scientific co-operation. We also find significant differences between industrial sectors as well as major contributions of large science-based multinational enterprises, such as Philips, in domestic science-technology linkages.The paper concludes by discussing general benefits and limitations of this bibliometric approach for macro-level analysis of science bases in advanced industrialised countries like the Netherlands.

How to identify research groups using publication analysis: an example in the field of nanotechnology

SummaryWe present a new bibliometric approach to identify research groups in a particular research field. With a combination of bibliometric mapping techniques and network analysis we identify and classify clusters of authors to represent research groups. In this paper we illustrate the application and potential of this approach and present two types of outcomes: actual research groups and potential research groups. The former enables us to define research groups beyond the organizational structure. The latter may be used to identify potential partners for collaboration. Our approach is a starting point to deal with the complex issue of research groups in a changing structure of scientific research.

Non-alphanumeric characters in titles of scientific publications: An analysis of their occurrence and correlation with citation impact

We investigated the occurrence of non-alphanumeric characters in a randomized subset of over almost 650,000 titles of scientific publications from the Web of Science database. Additionally, for almost 500,000 of these publications we correlated occurrence with impact, using the field-normalised citation metric CPP/FCSm. We compared occurrence and correlation with impact both at in general and for specific disciplines and took into account the variation within sets by (non-parametrically) bootstrapping the calculation of impact values. We also compared use and impact of individual characters in the 30 fields in which non-alphanumeric characters occur most frequently, by using heatmaps that clustered and reordered fields and characters. We conclude that the use of some non-alphanumeric characters, such as the hyphen and colon, is common in most titles and that not including such characters generally correlates negatively with impact. Specific disciplines on the other hand, may show either a negative, absent, or positive correlation. We also found that thematically related science fields use non-alphanumeric characters in comparable numbers, but that impact associated with such characters shows a less strong thematic relation. Overall, it appears that authors cannot influence success of publications by including non-alphanumeric characters in fields where this is not already commonplace.

Identification and analysis of the highly cited knowledge base of sustainability science

We investigated the interdisciplinary ‘pillars’ of scientific knowledge on which the emerging field of sustainability science is founded, using a bibliometric approach and data from the Web of Science database. To find this scientific basis, we first located publications that represent a relevant part of sustainability science and then extracted the set of best cited publications, which we called the highly cited knowledge base (HCKB). To find the research orientation in this set, we inspected the occurrence of fields and contrasted this with the occurrence of fields in other publication sets relevant to sustainability science. We also created a network of co-cited HCKB publications using the seed set citations, extracted communities or clusters in this network and visualised the result. Additionally, we inspected the most cited publications in these HCKB clusters. We found that themes related to the three pillars of sustainable development (environment, economy and sociology) are all present in the HCKB, although social science (not including economics) is less visible. Finally, we found increasing diversity of fields and clusters in the citations of the seed set, indicating that the field of sustainability science is not yet moving into a more transdisciplinary state.

Improving the functionality of interactive bibliometric science maps

The use of a map as a metaphor of a scientific field is an established idea and using it as aninterface to bibliometric data seems to have great potential. Nevertheless, our own implementationof such an interface came up with some limits inhibiting the user to comprehend as to what hewas looking at. As a result, the map was not used to its fullest potential. The implementationdescribed in this paper as a high-level (conceptual) design, addresses the problems noted by users.It combines both top-down and bottom-up access to the bibliometric data, something we see asvital to mapping internal knowledge onto the external depiction and vice versa. And as such, itbecomes a more complete tool to explore the mapped scientific field and to find and retrieverelevant information.

Combining concept maps and bibliometric maps : First explorations

SummaryBibliometric maps of science are a well-established research subject. But their adoption as a science policy support tool is lacking. We think this is because the user does not immediately comprehend a map and (as a result) is not enticed into using it. To help this comprehension, we propose the use of “qualitative maps”: an umbrella term for diverse tools such as concept maps and mental maps. We developed a tool that interfaces between a qualitative map and a bibliometric map which lets the user create a correspondence between the distinct vocabularies of the maps. We also conducted two user studies: the first explored the combined use of bibliometric and qualitative maps and the second the preferred format of the map and the word-usage in the description of its elements.

Bibliometric mapping as a science policy tool

Bibliometric mapping of science within a science policy context required a different approach to visualization than for IR purposes. The identification of sub-domains within a field and their unchanged definition over time is crucial. A combination of this structure with actor characteristics provides possible answers to policy related questions. A dedicated interface to enter a science map enables users to explore the field and its developments and to retrieve answers to user-defined questions from a policy perspective.

A combination of quantitative and qualitative maps in an evaluative bibliometric context

Maps of science provide visualizations of scientific knowledge domains by quantitatively grouping elements from scientific papers. In evaluative bibliometric studies these quantitative maps have proven a useful tool Representation schemes such as mental maps or cognitive maps provide a tool to structure qualitative reasoning about, for instance, strategies, learning and politics. A combination of bibliometric maps with these qualitative structures may provide new ways for attacking science-policy related problems using bibliometric data. A design is presented on how to create, visualize and use the correspondence between elements in both types of maps.