@article{ead95ed24b1149fa87cbaea1eb19d814,
title = "The puzzle of sharing scientific data",
abstract = "Government funding entities have placed data sharing at the centre of scientific policy. While there is widespread consensus that scientific data sharing benefits scientific progress, there are significant barriers to its wider adoption. We seek a deeper understanding of how researchers from different fields share their data and the barriers and facilitators of such sharing. We draw upon the notions of epistemic cultures and collective action theory to consider the enablers and deterrents that scientists encounter when contributing to the collective good of data sharing. Our study employs a mixed-methods design by combining survey data collected in 2016 and 2018 with qualitative data from two case studies sampled within two scientific communities: high-energy physics and molecular biology. We describe how scientific communities with different epistemic cultures can employ modularity, time delay, and boundary organisations to overcome barriers to data sharing.",
keywords = "Open science, collective action theory, data commons, epistemic cultures",
author = "{Pujol Priego}, Laia and Jonathan Wareham and Romasanta, {Angelo Kenneth S.}",
note = "Funding Information: The study of both cases relies on the diverse primary and secondary data sources described in . Numerous discussions with managers from Open Targets and Reana were an integral part of the Open Science Monitor, published by the European Commission in separate reports (Pujol Priego and Wareham , ). Primary data included 18 semi-structured interviews and direct observations from a study visit at the Wellcome Genome Campus for the OT open days (June 2019) and recurrent study visits at CERN from 2018–2020. As part of participation in the two additional EU H2020 funded projects, the authors benefited from extensive conversations with policymakers, research infrastructure managers, data architects, and programmers, in which they discussed data sharing practices and future open research data initiatives (CS3MESH4EOSC part of European Open Science Cloud and ATTRACT funded by Research Infrastructure Innovation H2020-INFRAINNOV). The interview process was concluded when no significant additional insights were obtained from the data, and theoretical saturation was achieved. Funding Information: This study was funded by the Open Science Monitor (2017- 2019), a service contract with European Commission- DG RTD (Contract number PP-05622-2017) and implemented in collaboration with Elsevier, ESADE, Leiden University, and Lisbon Council. Funding Information: The importance of sharing FAIR data comes as part of a more general {\textquoteleft}open{\textquoteright} movement, embracing greater transparency in science (Edwards ). Starting with open access publishing, the open movement extends to open scientific data, open standards, open repositories, open bibliography, open lab-notebooks, open-source software and hardware – a virtually endless list of {\textquoteleft}open{\textquoteright} qualifiers to all activities in the scientific realm (Friesike et al. ). The urgency of sharing FAIR data is not only based on concerns of reproducibility (Baker ) or scientific fraud (Kupferschmidt ), but also in recognition of the novel technological and scientific innovations that can result from data sharing (Borgman ). As such, government funding entities, particularly in Western Europe and the United States, have placed open data at the crux of scientific policy. As European Union Commissioner for Research, Science, and Innovation, Carlos Moedas made open research data one of the EU{\textquoteright}s priorities in 2015. This led to the formation of several expert working groups (e.g. High-level expert group on FAIR data, the Open Science Policy Platform, Expert group on altmetrics) to provide advice on how to foster and promote research data sharing in Europe. In 2016, the EU launched the Open Science Cloud initiative, which is a federated data infrastructure with cloud-based services to provide the scientific community with an open environment for storing, sharing, and reusing scientific data. In parallel, many funding agencies now require that scientific data be publicly available: for example, the US National Institutes of Health (NIH) has required this since 2003 for grants over $500,000 (NIH ), the National Science Foundation (NSF) since 2010 (Borgman ), and the European Commission for the Horizon 2020 programme since 2014 (European Commission ). Accompanying policy, new private and public entities have emerged to facilitate the aggregation and publication of research data. Examples include the Research Data Alliance and the National Data Service, as well as for-profit publishers who attempt to build on existing structures (e.g. Mendeley Data) (Borgman ). Platforms such as Dataverse (King ), FigShare (Thelwall and Kousha ), Zenodo (Peters et al. ), DataHub (Bhardwaj et al. ), EUDat (Lecarpentier et al. ), and other data repositories 3 Publisher Copyright: {\textcopyright} 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.",
year = "2022",
doi = "10.1080/13662716.2022.2033178",
language = "English",
volume = "29",
pages = "219--250",
journal = "Industry and Innovation",
issn = "1366-2716",
publisher = "Routledge",
number = "2",
}