Dominique Besagni

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?

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.

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.

Identification of Emergent Research Issues: the Case of Optoelectronic Devices

The optoelectronic devices field is one of the last decades most promising technological fields. Light emitting diodes gain more applications in cars and housing lighting, OLED displays are introduced in electronic devices and consumer electronics. Optimization of lighting power and tuning of light spectrum are well known important research topics.

Meta-Data Extraction from Bibliographic Documents for the Digital Library

This chapter addresses the problem of automatic metadata extraction within digitized documents by retro-conversion techniques. The focus is on bibliographic documents as they are by nature a source of such metadata. They are strongly structuring for a digital library (DL), their automatic recognition presents an obvious interest. However as their origin is very different (references, citations, tables of content, index cards), a generic methodology is proposed for their structure. Based on a first morphological labeling of the text, it looks for syntactic elements (syntagmas) revealing the bibliographic field nature (title, authors, date, publication source, etc.). Depending on the case, the syntax is validated either by a given grammar or by occurrence analysis in the different document elements (i.e. several references in a bibliography, or articles in a table of content). In the later, the bottom-up procedure generates a structure model from the well-recognized elements and applies it on the rest. The modeling requires taking into consideration the interand intra-fields relationships. The experiments performed on different types of documents confirm the interest of this approach.

How to address the role of a Journal as a Knowledge Transfer Vector between disciplines? A Case Study Relying on Citation Analysis

Abstract In this study our aim was to characterize the role of a scientific journal as a vector for the transfer of knowledge between different research communities. To detect the size and extent of a journals readership, we used citation analysis of two scientific corpora constructed around the production of one journal. The first was made up of ex ante references or references cited in the bibliographies of all the articles published in the journal over a given year of publication while the second consisted of the articles’ ex post references - subsequent works which cite them. Both corpora underwent a stage of clustering which produced a theme-based representation of the contents made possible by automatic indexing. Computer-aided thematic categorization validated by an expert gave a representation of both corpora through a vector of categories each element which indicated the level of representativity of the category in the corpus. A role indicator was then defined based on a calculation of cosine similarity between the two vectors of categories associated with the journal. This indicator qualified the behaviour of the journal in terms of a transfer vector for knowledge. The case study involved two journals in the field of Information and Communication Sciences and Technologies.

From applicateness to potential applicability: An informetric approach based on researchers’ scientific productions

This work discusses a methodology for measuring the applied orientation, which we call “applicateness”, of the results published by a researcher in the scientific and technological literature, and applies this methodology to evaluate the potential applicability of a research project submitted for funding to a grant agency. Our methodology develops a content analysis approach operated with the help of text mining tools coming from the natural language processing (NLP) and clustering techniques. Its deployment aims at easing the workload of the final stage of expertise, which nevertheless remains necessary. We illustrate our approach by processing a real case coming from the grant applications of the main European funding agency that has established a selection process based on the identification of scientific excellence in frontier research as the sole evaluation criterion for funding decisions.

La rétroconversion de fonds bibliographiques pour des besoins de bibliométrie

Cet article decrit une methodologie de retroconversion de citations permettant de retrouver les champs composants a partir de leur texte reconnu par OCR. Cette methodologie se base a la fois sur la regularite et la redondance de certains champs ainsi que sur la localisation de parties de discours specifiques a certains champs. Le resultat de la retroconversion sert a des etudes de bibliometrie et de scientometrie. Si nous utilisons cette methodologie sur des documents recents dans un but de veille technologique, nous considerons qu’elle est suffisamment generique pour pouvoir s’appliquer sur des documents anciens et donc patrimoniaux.