Bibliometrics for technology forecasting and assessment - further results and future prospects

For present-day researchers and decision-makers not so much a lack but contrary a plethora of information forms a challenge. Bibliometric methods offer the chance to tackle this ever growing amount of scientific publications by assisting researchers and decision-makers in gaining insight into the structure of a specific scientific landscape. Bibliometrics is a collection of quantitative and statistical methods, which aim to analyse scientific literature. It relies on the bibliographic information of scientific papers stored in an appropriate data base. A typical bibliometric workflow comprises three different phases. The first phase covers the elaboration of a search query which aims to delineate the field of interest as accurately as possible. While the second phase deals with the acquisition and cleansing of the bibliometric data, the last phase covers the analysis and visualization of the data. Following the course of this workflow one can identify three different aspects, where bibliometric methods might be useful for technology analyses within the context of technology forecasting and assessment. First of all bibliometrics might proof useful for enhancing the process of information retrieval. Although one of the first of such approaches dates back to 2005 (Kostoff/ Shlesinger 2005), it was only recently, that a systematic investigation of this topic has been initiated (Mayr et al. 2014). The second aspect concerns the challenge of detecting emerging topics as early and correctly as possible, which might be addressed by bibliometric means. Admittedly any bibliometric approach to this task faces the major problem that bibliometrics is an inherently retrospective method. With this we mean that it is based on an analysis of previous publications and citations. Hence it remains an open question whether it is possible to detect trends for the future by eavesdropping into today's scientific communication. This contribution discusses this question by referring to the recently introduced approach named ""trend archaeology"" (John/Fritsche 2013), which examines historic scientific trends and looks for specific patterns within their temporal evolution. Finally, since bibliometrics is a quantitative method it offers the opportunity to visualize some facets and results of technology forecasting and technology assessment projects. This frequently underratedaspect might have a considerable impact on the process of knowledge transfer in such a project. In this contribution we will discuss the aforementioned aspects and demonstrate how bibliometrics might assist researches and decision-makers by gaining insight into the structure of a scientific landscape they are interested in.