Edgar Schiebel

Science and technology mapping: a new iteration model for representing multidimensional relationships

Much effort has been done to develop more objective quantitative methods to analyze and integrate survey information for understanding research trends and research structures. Co-word analysis is one class of techniques that exploits the use of co-occurrences of items in written information. However, there are some bottle-necks in using statistical methods to produce mappings of reduced information in a comfortable manner. On one hand, often used statistical software for PCs has restrictions for the amount for calculable data; on the other hand, the results of the multidimensional scaling routines are not quite satisfying. Therefore, this article introduces a new iteration model for the calculation of co-word maps that eases the problem. The iteration model is for positioning words in the two-dimensional plane due to their connections to each other, and it consists of a quick and stabile algorithm that has been implemented with software for personal computers. A graphic module represents the data in well-known “technology maps.”

An advanced diffusion model to identify emergent research issues: the case of optoelectronic devices

Scientific progress in technology oriented research fields is made by incremental or fundamental inventions concerning natural science effects, materials, methods, tools and applications. Therefore our approach focuses on research activities of such technological elements on the basis of keywords in published articles. In this paper we show how emerging topics in the field of optoelectronic devices based on scientific literature data from the PASCAL-database can be identified. We use Results from PROMTECH project, whose principal objective was to produce a methodology allowing the identification of promising emerging technologies. In this project, the study of the intersection of Applied Sciences as well as Life (Biological & Medical) Sciences domains and Physics with bibliometric methods produced 45 candidate technological fields and the validation by expert panels led to a final selection of 10 most promising ones. These 45 technologies were used as reference fields. In order to detect the emerging research, we combine two methodological approaches. The first one introduces a new modelling of field terminology evolution based on bibliometric indicators: the diffusion model and the second one is a diachronic cluster analysis. With the diffusion model we identified single keywords that represent a high dynamic of the mentioned technology elements. The cluster analysis was used to recombine articles, where the identified keywords were used to technological topics in the field of optoelectronic devices. This methodology allows us to answer the following questions: Which technological aspects within our considered field can be detected? Which of them are already established and which of them are new? How are the topics linked to each other?

Identification and characterisation of technological topics in the field of Molecular Biology

Following up the European project PromTech the aim of which was to detect emerging technologies by studying the scientific literature, we chose one field, Molecular Biology, to identify and characterize emerging topics within that domain. We combined two analytical approaches: the first one introduces a model of the terminological evolution of the field based on bibliometric indicators and the second one operates a diachronic clustering analysis. Our objective is to bring answers to questions such as: Which technological aspects can be detected? Which of them are already established and which of them are new? How are the topics linked to each other?

Visualization of research fronts and knowledge bases by three-dimensional areal densities of bibliographically coupled publications and co-citations

In this work the well known scientometric concepts of bibliographically coupled publications and co-cited references were applied to produce interactive maps of research fronts and knowledge bases of research fields. This article proposes a method and some standardization for the detection and visualization of research fronts and knowledge bases with two and three dimensional graphics inspired by geographical maps. Agglomerations of bibliographically coupled publications with a common knowledge base are identified and graphically represented by a density function of publications per area unit. The research fronts become visible if publications with similar vectors of common citations are associated and visualized as an ensemble in a three dimensional graphical representation as a mountain scenery measured with the help of a spatial density. Knowledge bases were calculated in the same way. Maps similar to the geographic representation of oceans and islands are used to visualize the two-dimensional spatial density function of references weighted by individual links. The proposed methodology is demonstrated by publications in the field of battery research.

Knowledge Maps of Knowledge Management Tools - Information Visualization with BibTechMon

Companies, R&D-departments or managers are confronted with an increasing amount of information which has to be analysed corresponding to their importance and applicability for the company and the current question. For this purpose information from internal or external sources like internal documents, patent information, literature quotations or internet information has to be identified, surveyed, read, distributed and used. Especially the search for relevant information and the decision about their applicability gets more and more time-consuming. In order to reduce the efforts for structuring and sorting information the Department of Technology Management of the ARC Seibersdorf research GmbH has developed the software tool BibTechMon for structuring, visualising and analysing large amounts of information. Several thousands of documents available from external or in-house databases or from internet can be worked up with the software BibTechMon. The advantage of this method is based on the possibility of content-based structuring of the information, the identification of subtopics, the visualisation of the contents, of structure and connections of the information and the subtopics. Application fields are wide-spread -- from patent management, technology monitoring or analysis of internal documents up to competitive analysis of companies and products and identification of co-operation behaviour of persons or institutions. Therefore BibTech-Mon allows the mapping of information to support internal communication, information retrieval and strategic decision support. Due to its different fields of application in the context of knowledge management, BibTechMon is part of a fast growing number of software tools designed to support knowledge management. The exploding amount of software products on that sector make it rather impossible to get a sufficient overview or to select the appropriate tool for a given question. In order to support the analysis and classification of software tools for knowledge management a survey was performed and analysed with BibTechMon. Using this example the possibilities of our method will be demonstrated as well as an overview over the results of our survey will be given.

Do second-order similarities provide added-value in a hybrid approach?

Recent studies on first- and second-order similarities have shown that the latter one outperforms the first one as input for document clustering or partitioning applications. First-order similarities based on bibliographic coupling or on lexical approaches come with specific methodological issues like sparse matrices, sensitive to spelling variances or context differences. Second-order similarities were proposed to tackle these problems and take the lexical context into account. But also a hybrid combination of both types of similarities proved an important improvement which integrates the strengths of the two approaches and diminishes their weaknesses. In this paper we extend the notion of second-order similarity by applying it in the context of the hybrid approach. We conclude that there is no added value for the clearly defined clusters but that the second-order similarity can provide an additional viewpoint for the more general clusters.

A concept for inferring `frontier research' in grant proposals

This paper discusses a concept for inferring attributes of ‘frontier research’ in peer-reviewed research proposals under the popular scheme of the European Research Council (ERC). The concept serves two purposes: firstly to conceptualize, define and operationalize in scientometric terms attributes of frontier research; and secondly to build and compare outcomes of a statistical model with the review decision in order to obtain further insight and reflect upon the influence of frontier research in the peer-review process. To this end, indicators across scientific disciplines and in accord with the strategic definition of frontier research by the ERC are elaborated, exploiting textual proposal information and other scientometric data of grant applicants. Subsequently, a suitable model is formulated to measure ex-post the influence of attributes of frontier research on the decision probability of a proposal to be accepted. We present first empirical data as proof of concept for inferring frontier research in grant proposals. Ultimately the concept is aiming at advancing the methodology to deliver signals for monitoring the effectiveness of peer-review processes.

International publication output and research impact in social sciences: comparison of the Universities of Vienna, Zurich and Oslo

In this study we carried out a bibliometric analysis of the social sciences at three European universities (Vienna, Zurich, Oslo). The data source for this investigation was the Web of Science SSCI and publications between 2000 and 2006 were included for retrieval. Apart from the analysis of the publication output, activity and impact, networks of co-authorships, disciplines and references were explored. In general the results reveal that overall Oslo outperformed the other two universities which show similar publication activities and outputs. Using the University of Oslo as a benchmark should help to outline different strategies (research, publication and cooperation) to enhance the international visibility of the output of the University of Vienna in different fields of the social sciences. Copyright , Beech Tree Publishing.

Exploring the bibliometric and semantic nature of negative results

Negative results are not popular to disseminate. However, their publication would help to save resources and foster scientific communication. This study analysed the bibliometric and semantic nature of negative results publications. The Journal of Negative Results in Biomedicine (JNRBM) was used as a role model. Its complete articles from 2002–2009 were extracted from SCOPUS and supplemented by related records. Complementary negative results records were retrieved from Web of Science in “Biochemistry” and “Telecommunications”. Applied bibliometrics comprised of co-author and co-affiliation analysis and a citation impact profile. Bibliometrics showed that authorship is widely spread. A specific community for the publication of negative results in devoted literature is non-existent. Neither co-author nor co-affiliation analysis indicated strong interconnectivities. JNRBM articles are cited by a broad spectrum of journals rather than by specific titles. Devoted negative results journals like JNRBM have a rather low impact measured by the number of received citations. On the other hand, only one-third of the publications remain uncited, corroborating their importance for the scientific community. The semantic analysis relies on negative expressions manually identified in JNRBM article titles and abstracts and extracted to syntactic patterns. By using a Natural Language Processing tool these patterns are then employed to detect their occurrences in the multidisciplinary bibliographical database PASCAL. The translation of manually identified negation patterns to syntactic patterns and their application to multidisciplinary bibliographic databases (PASCAL, Web of Science) proved to be a successful method to retrieve even hidden negative results. There is proof that negative results are not only restricted to the biomedical domain. Interestingly a high percentage of the so far identified negative results papers were funded and therefore needed to be published. Thus policies that explicitly encourage or even mandate the publication of negative results could probably bring about a shift in the current scientific communication behaviour.

Evaluating patterns of co-operation: application of a bibliometric visualisation tool to the Fourth Framework Programme and the Transport Research Programme

Networks of collaboration have been set up within the European Unions Fourth Framework Programme (FP4) by applying co-occurrence analysis and visualisation in two-dimensional knowledge maps. The focus of the analysis is on the patterns of co-operation and collaboration in research networks within FP4, involving the industrial, research and education sectors of all EU-Member States. The aggregate situation of FP4, and the Transport Research Programme in particular, are examined to identify features within patterns of co-operation of relevance to European research. The methodology is summarised, and potential for future research evaluation within the European Research Area is assessed. Copyright , Beech Tree Publishing.