Institute of Information Science, Academia Sinica

Scientometric research is an important aspect of research evaluation. It usually involves the quantitative and statistical analysis of scientific publications and citations. However, it should also consider practices of researchers, socio-organizational structures, research and development management, the role of science and technology in the national economy, etc. in its calculations. The first part of the talk will give an overview of the different research areas related to scientometrics: informetrics, bibliometrics and altmetrics and of course also introduce scientometrics itself. We will start with a short historic overview and then present the most important concepts of these research areas. In the second part of the talk, we will introduce our research endeavor at MMNet: Performance and aspiration of researchers in the context of social physics. Under the roof of this project, we will focus on three major research areas, which we will also explain in this talk: adoption of new research topics (comparison on country-level), metrics for scientific conferences and accuracy of citation analysis.

Dr. Marlies Olensky is a postdoctoral research fellow at the Institute of Information Science, Academia Sinica since October 2015, where she works on scientometric research topics and couples them with social physics. Marlies holds a diploma in Information Professions from the University of Applied Sciences, Eisenstadt, Austria. After graduating in 2003, she worked as Terminal Manager in the strategic purchase department of the leading mobile network provider in Austria. 2009 she moved to Berlin to pursue her doctoral studies in Library and Information Science at the Humboldt-Universitaet zu Berlin. At the same time she started working as a researcher in the European Digital Library project Europeana, focusing on semantic search, metadata enrichment and the Europeana Data Model. Her dissertation, which she completed in December 2014, investigated data quality in bibliometric data sources and its influence on citation matching.