Edwin Horlings

Author disambiguation using multi-aspect similarity indicators

Key to accurate bibliometric analyses is the ability to correctly link individuals to their corpus of work, with an optimal balance between precision and recall. We have developed an algorithm that does this disambiguation task with a very high recall and precision. The method addresses the issues of discarded records due to null data fields and their resultant effect on recall, precision and F-measure results. We have implemented a dynamic approach to similarity calculations based on all available data fields. We have also included differences in author contribution and age difference between publications, both of which have meaningful effects on overall similarity measurements, resulting in significantly higher recall and precision of returned records. The results are presented from a test dataset of heterogeneous catalysis publications. Results demonstrate significantly high average F-measure scores and substantial improvements on previous and stand-alone techniques.

Search strategies along the academic lifecycle

Understanding how individual scientists build a personal portfolio of research is key to understanding outcomes on the level of scientific fields, institutions, and systems. We lack the scientometric and statistical instruments to examine the development over time of the involvement of researchers in different problem areas. In this paper we present a scientometric method to map, measure, and compare the entire corpus of individual scientists. We use this method to analyse the search strategies of 43 condensed matter physicists along their academic lifecycle. We formulate six propositions that summarise our theoretical expectations and are empirically testable: (1) a scientist’s work consists of multiple finite research trails; (2) a scientist will work in several parallel research trails; (3) a scientist’s role in research trail selection changes along the lifecycle; (4) a scientist’s portfolio will converge before it diverges; (5) the rise and fall of research trails is associated with career changes; and (6) the rise and fall of research trails is associated with the potential for reputational gain. Four propositions are confirmed, the fifth is rejected, and the sixth could not be confirmed or rejected. In combination, the results of the four confirmed propositions reveal specific search strategies along the academic lifecycle. In the PhD phase scientists work in one problem area that is often unconnected to the later portfolio. The postdoctoral phase is where scientists diversify their portfolio and their social network, entering various problem areas and abandoning low-yielding ones. A professor has a much more stable portfolio, leading the work of PhDs and postdoctoral researchers. We present an agenda for future research and discuss theoretical and policy implications.

How do dimensions of proximity relate to the outcomes of collaboration? A survey of knowledge-intensive networks in the Dutch water sector

There is a growing body of literature on the importance of proximity for innovation and other knowledge-related outcomes. We examine the impact of geographical, social, organisational, and cognitive proximity for a heterogeneous population, including people from academia, knowledge institutes, industry, and government. We analyse data on 1020 ego–alter relationships, derived from a survey among water professionals in the Netherlands. The use of survey data allows for more refined indicators of proximity and more diverse collaboration outcomes than those common in the literature. Social and cognitive proximity have a positive effect for all outcomes examined. Geographical and organisational proximity have a negative effect on hard (tangible) outcomes yet a weak positive (if any) effect on soft (intangible) outcomes. We do not find evidence for the suggestions in the conceptual literature that proximity follows an inverted U-curve where most outcomes are achieved in relations with some but not too much proximity.

Organizational factors influencing scholarly performance: a multivariate study of biomedical research groups

Bibliometric studies often measure and compare scholarly performance, but they rarely investigate why universities, departments, and research groups do have different performance. In this paper we try to explain differences in scholarly performance of research groups in terms of organizational variables. In order to do this, we extensively review the relevant literature, and develop a model using two theoretical approaches. A multivariate analysis shows which of the independent variables do play a role in the various scholarly performance dimensions. The study shows what organizational strategies may help in optimizing performance in various dimensions. Implications are discussed.

Mapping science through bibliometric triangulation: An experimental approach applied to water research

The idea of constructing science maps based on bibliographic data has intrigued researchers for decades, and various techniques have been developed to map the structure of research disciplines. Most science mapping studies use a single method. However, as research fields have various properties, a valid map of a field should actually be composed of a set of maps derived from a series of investigations using different methods. That leads to the question of what can be learned from a combination—triangulation—of these different science maps. In this paper we propose a method for triangulation, using the example of water science. We combine three different mapping approaches: journal–journal citation relations (JJCR), shared author keywords (SAK), and title word‐cited reference co‐occurrence (TWRC). Our results demonstrate that triangulation of JJCR, SAK, and TWRC produces a more comprehensive picture than each method applied individually. The outcomes from the three different approaches can be associated with each other and systematically interpreted to provide insights into the complex multidisciplinary structure of the field of water research.

Analysing knowledge capture mechanisms: Methods and a stylised bioventure case

Knowledge transfer between science and technology has been studied at micro- and macro-levels of analysis. This has contributed to the understanding of the mechanisms and drivers, but actual transfer mechanism and process, be they through codified or tacit sources, have very rarely been mapped and measured to completeness and remain, to a large extent, a black box. We develop a novel method for mapping science–technology flows and introduce ‘concept clusters’ as an instrument to do so. Using patent and publication data, we quantitatively and visually demonstrate the flows of knowledge between academia and industry. We examine the roles of exogenous and endogenous knowledge sources, and of co-inventors and co-authors in the application of university-generated knowledge. When applied to a stylised case, we show that the method is able to trace the linkages between base knowledge and skill sets and their application to a technology, which in some instances span over twenty-five years.

Convergence in science: Growth and structure of worldwide scientific output, 1993–2008

We examine if the globalisation of science is accompanied by convergence in the level and structure of scientific output. We use Web of Science data on the scientific output of 205 countries for 1993, 2000, and 2008, distinguished by subject area. We found evidence of absolute and conditional β-convergence and σ-convergence in levels of scientific output, particularly after 2000. The data also show that the portfolios of the majority of the worlds science systems are becoming more similar. This convergence of portfolios occurs in convergence clubs rather than as a global process. Exploratory factor analysis shows that countries cluster into eight discrete convergence clubs and perhaps only two: the ‘haves’ and ‘have-nots’. Dynamic shift-share analysis reveals that growth is a normal phenomenon, output composition is only really an issue in the former Soviet Republics (negative) and the LDCs (positive) after 2000, and comparative advantages is where convergence clubs differentiate strongest. The ability of countries to improve local conditions and escape the strictures of their portfolio depends on the interplay of forces along two dimensions. between short-term dynamics and long-term stability and between the complexity of science and the predominance of national policies and institutions. Understanding the design and functioning of a science system in all its complexity is crucial to survive in a world of different speeds with intense competition and persistent gaps between rich and poor. For scientists and policy makers alike, selecting the right science portfolio and knowing the competition are key issues.