Data Sharing Frames : How Scientists Understand the Work of Sharing Scientific Data

Kwame Amagyei, Nana and Engesmo, Jostein and Panteli, Niki (2023) Data Sharing Frames : How Scientists Understand the Work of Sharing Scientific Data. In: International Conference on Information Systems : ICIS 2023. Association for Information Systems, IND. ISBN 9781958200070

Abstract

The curation of data is fundamental to their wider dissemination and use. This paper investigates the frames of workers who perform data curation in scientific contexts. We view data curation as a sense-making practice, where workers collaborate to disseminate meaningful data to a broad set of prospective users. Previous Information Systems investigations have suggested that data-related activities are dependent on workers’ understanding of their local work context. We expand this with an evolving and long-term view. We use a stepwise-deductive induction method to examine how scientists understand the work involved in curating scientific data for public sharing. We draw on frames as the theoretical lens of the study that enables us to identify three data sharing frames – the object, curation, and aligning frames – as important frames that shape how scientists curate data for public sharing. Our analysis provides a deeper understanding of the nuances of managing scientific data for public access. Our main contribution is the articulation of an evolving and long-term view of how workers approach their tasks in getting data ready for long-term public use.