VAriable Detection, Interlinking and Summarization (VADIS)

The key vision behind VADIS is to allow for searching und using survey variables in context and thereby help to increase the reproducibility of research results. We achieve this by combining text mining techniques and semantic web technologies that identify and exploit links between publications, their topics, and the specific variables that are covered in the surveys. These semantic links in scientific texts build the basis for the development of applications to give users better access to scientific literature such as passage search, summarization, and information retrieval.

Name: VAriable Detection, Interlinking and Summarization (VADIS)
Funding: Deutsche Forschungsgemeinschaft
Overall Budget: 900,000 Euro
Own Budget: 282,000 Euro
Duration: 2021 - 2023
Partners: Dr. Philipp Mayr-Schlegl, GESIS Leibniz Institute for Social Sciences
Prof. Dr. Simone Ponzetto, University of Mannheim
Dr. Henning Kroll, Fraunhofer Institute for Systems and Innovation Research (ISI)