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Nowadays there is a growing trend in many scientific disciplines to supportresearchers by providing enhanced information access through linking ofpublications and underlying datasets, so as to support research withinfrastructure to enhance reproducibility and reusability of research results.In this research note, we present an overview of an ongoing research project,named VADIS (VAriable Detection, Interlinking and Summarization), that aims atdeveloping technology and infrastructure for enhanced information access in theSocial Sciences via search and summarization of publications on the basis ofautomatic identification and indexing of survey variables in text. We providean overview of the overarching vision underlying our project, its maincomponents, and related challenges, as well as a thorough discussion of howthese are meant to address the limitations of current information accesssystems for publications in the Social Sciences. We show how this goal can beconcretely implemented in an end-user system by presenting a search prototype,which is based on user requirements collected from qualitative interviews withempirical Social Science researchers.

Towards Automated Survey Variable Search and Summarization in Social Science Publications