Lost or found? Discovering data needed for research

Finding data is a necessary precursor to being able to reuse data, although relatively little large-scale empirical evidence exists about how researchers discover, make sense of and (re)use data for research. This study presents evidence from the largest known survey investigating how researchers discover and use data that they do not create themselves. We examine the data needs and discovery strategies of respondents, propose a typology for data reuse and probe the role of social interactions and literature search in data discovery. We consider how data communities can be conceptualized according to data uses and propose practical applications of our findings for designers of data discovery systems and repositories. Specifically, we consider how to design for a diversity of practices, how communities of use can serve as an entry point for design and the role of metadata in supporting both sensemaking and social interactions.Comment: Harvard Data Science Review (2020

Struktur und Funktion wissenschaftlicher Publikation im World Wide Web: Wissenschaftsforschung Jahrbuch 2015

Peer Reviewe

Editorial for the Proceedings of the Workshop Knowledge Maps and Information Retrieval (KMIR2014) at Digital Libraries 2014

Knowledge maps are promising tools for visualizing the structure of large - sc ale information spaces, but still far away from being applicable for searching. The first international workshop on ``Knowledge Maps and Information Retrieval (KMIR)'', held as part of the International Conference on Digital Libraries 2014 in London, aimed a t bringing together experts in Information Retrieval (IR) and knowledge mapping in order to discuss the potential of interactive knowledge maps for information seeking purposes