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Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences
Author(s) -
Rebecca Springer,
Danielle Cooper
Publication year - 1970
Publication title -
international journal of digital curation
Language(s) - English
Resource type - Journals
ISSN - 1746-8256
DOI - 10.2218/ijdc.v15i1.695
Subject(s) - data sharing , scholarly communication , relevance (law) , public relations , knowledge management , work (physics) , skepticism , discipline , knowledge sharing , open science , qualitative property , open data , sociology , data science , political science , computer science , world wide web , social science , engineering , epistemology , publishing , medicine , alternative medicine , pathology , mechanical engineering , philosophy , physics , astronomy , machine learning , law
There is a growing perception that science can progress more quickly, more innovatively, and more rigorously when researchers share data with each other. However many scientists are not engaging in data sharing and remain skeptical of its relevance to their work. As organizations and initiatives designed to promote STEM data sharing multiply – within, across, and outside academic institutions – there is a pressing need to decide strategically on the best ways to move forward. In this paper, we propose a new mechanism for conceptualizing and supporting STEM research data sharing.. Successful data sharing happens within data communities, formal or informal groups of scholars who share a certain type of data with each other, regardless of disciplinary boundaries. Drawing on the findings of four large-scale qualitative studies of research practices conducted by Ithaka S+R, as well as the scholarly literature, we identify what constitutes a data community and outline its most important features by studying three success stories, investigating the circumstances under which intensive data sharing is already happening. We contend that stakeholders who wish to promote data sharing – librarians, information technologists, scholarly communications professionals, and research funders, to name a few – should work to identify and empower emergent data communities. These are groups of scholars for whom a relatively straightforward technological intervention, usually the establishment of a data repository, could kickstart the growth of a more active data sharing culture. We conclude by offering recommendations for ways forward.

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