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Value of open data: A geoscience perspective
Author(s) -
Wildman Geraldine,
Lewis Edward
Publication year - 2022
Publication title -
geoscience data journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.125
H-Index - 11
ISSN - 2049-6060
DOI - 10.1002/gdj3.138
Subject(s) - open data , interoperability , data sharing , incentive , computer science , sustainability , data governance , data science , business , risk analysis (engineering) , knowledge management , data quality , world wide web , marketing , economics , medicine , ecology , metric (unit) , alternative medicine , pathology , biology , microeconomics
We are living in a data‐centric society, with governments and businesses increasingly looking at what they can do to gain insight and improve the flow of data. Encouraging the release of data as ‘open data’ is one measure that would remove barriers to access, increase use and facilitate downstream data innovation. Using examples from firstly the non‐geoscience and then geoscience sectors, this paper outlines three factors that can lead to a successful open data programme. These are (1) having a clear strategy with a well‐articulated vision; (2) ensuring that data are not only free but also technically accessible and delivered under an open licence; and (3) continued investment in the programme to ensure its long‐term success. However, not all data can or should be open, and organizations and governments must be careful that their interventions do not have unintended consequences that might reduce incentives to collect, maintain and share data. A primary concern is the financial sustainability of a dataset, but this also extends to other risks that would prevent the data being widely shared such as the inclusion of personal data or third‐party intellectual property. In these cases, use of a data‐sharing risk assessment framework, and the application of the FAIR principles of findable, accessible, interoperable and reusable can be used to increase data sharing and maximize the benefits that can be realized from geoscience data.

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