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

Roche, Ivana; Besagni, Dominique; François, Claire; Hörlesberger, Marianne; Schiebel, Edgar

doi:10.1007/s11192-010-0178-8

Cited by 27 publications

(10 citation statements)

References 2 publications

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“…This network is then analysed in order to identify emerging trends. Schiebel et al (2010) and Roche et al (2010) proposed instead an approach to emergence that is based on a diffusion model (and diachronic cluster analysis to identify topics) that combines a modified tf-idf 11 with the Gini coefficient to identify three stages: "unusual terms", "established terms", and "cross section terms". Unusual terms are those that are rare in publications since they describe a research discovery at a very early stage.…”

Section: Relatively Fast Growthmentioning

confidence: 99%

What is an emerging technology?

2015

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There is considerable and growing interest in the emergence of novel technologies, especially from the policy-making perspective. Yet as an area of study, emerging technologies lacks key foundational elements, namely a consensus on what classifies a technology as 'emergent' and strong research designs that operationalize central theoretical concepts. The present paper aims to fill this gap by developing a definition of 'emerging technologies' and linking this conceptual effort with the development of a framework for the operationalisation of technological emergence. The definition is developed by combining a basic understanding of the term and in particular the concept of 'emergence' with a review of key innovation studies dealing with definitional issues of technological emergence. The resulting definition identifies five attributes that feature in the emergence of novel technologies. These are: (i) radical novelty, (ii) relatively fast growth, (iii) coherence, (iv) prominent impact, and (v) uncertainty and ambiguity. The framework for operationalising emerging technologies is then elaborated on the basis of the proposed attributes. To do so, we identify and review major empirical approaches (mainly in, although not limited to, the scientometric domain) for the detection and study of emerging technologies (these include indicators and trend analysis, citation analysis, co-word analysis, overlay mapping, and combinations thereof) and elaborate on how these can be used to operationalise the different attributes of emergence.

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Section: Relatively Fast Growthmentioning

confidence: 99%

What is an emerging technology?

2015

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“…Over the years, co-word analysis and co-citation analysis have been used extensively to map the structure of science in a given field of study (Courtial & Law, 1989), for example, in library and information science and women's studies (Marshakova-Shaikevich, 2005). Co-word analysis was used to determine intellectual coherence in artificial intelligence (Courtial & Law, 1989), diversity and coherence as indicators of interdisciplinarity in bionanoscience (Rafols & Meyer, 2010), and identification of technological topics in molecular biology (Roche, Besagni, François, Hörlesberger, & Schiebel, 2010).…”

Section: Previous Researchmentioning

confidence: 99%

A bibliometric mapping of the structure of STEM education using co‐word analysis

Assefa

Rorissa

2013

J Am Soc Inf Sci Tec

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STEM, a set of fields that includes science, technology, engineering, and mathematics; allied disciplines ranging from environmental, agricultural, and earth sciences to life science and computer science; and education and training in these fields, is clearly at the top of the list of priority funding areas for governments, including the United States government. The U.S. has 11 federal agencies dedicated to supporting programs and providing funding for research and curriculum development. The domain of STEM education has significant implications in preparing the desired workforce with the requisite knowledge, developing appropriate curricula, providing teachers the necessary professional development, focusing research dollars on areas that have maximum impact, and developing national educational policy and standards. A complex undertaking such as STEM education, which attracts interest and valuable resources from a number of stakeholders needs to be well understood. In light of this, we attempt to describe the underlying structure of STEM education, its core areas, and their relationships through co-word analyses of the titles, keywords, and abstracts of the relevant literature using visualization and bibliometric mapping tools. Implications are drawn with respect to the nature of STEM education as well as curriculum and policy development.

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“…We consider that, at a given level, two clusters are connected if the value of the cosine associated to them is within the range of values of this level. Finally, we analysed the evolution between the two cluster sets and the two maps by examining the vocabulary related to the clusters of each period using a comparison matrix (Roche et al 2008).…”

Section: Diachronic Cluster Analysismentioning

confidence: 99%

“…Studies in a large range of domains in society, economy, ecology, politics, etc. were performed (Kajikawa et al 2008;Noyons 2004;Roche et al 2008;Schiebel and Hörlesberger 2007).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2010

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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 PROM-TECH 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?

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

Cited by 27 publications

References 2 publications

What is an emerging technology?

What is an emerging technology?

A bibliometric mapping of the structure of STEM education using co‐word analysis

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

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