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Data Sharing Toolkit: Lessons learned, resources and recommendations for sharing data

Data Sharing Toolkit: Lessons learned, resources and recommendations for sharing data
Data Sharing Toolkit: Lessons learned, resources and recommendations for sharing data
Data plays a major role in the European economy, and building a European data economy is one of the strategic goals of the European Commission. Through the increase of data science techniques, not least Machine Learning (ML) and Artificial Intelligence (AI), the value and role of data as an asset becomes ever more crucial. This has made it more important for data to be accessible. However, much of the data that many solutions require are held within private organisations - and are only available if they are shared. Data sharing in this sense means allowing third parties specifically permissioned access to datasets to generate value.
This toolkit has been developed to help organisations that want to generate value by sharing data or facilitating data sharing. We explain the concept, challenges, and processes to enable successful data sharing, and provide resources and recommendations. It is derived from experience collected in the Data Pitch programme and related national and international initiatives, such as the Smart Cities Innovation Framework Implementation (SciFi), the European Data Incubator (EDI), as well as several recent pilots for data trusts in the UK.
Data Pitch
Thuermer, Gefion
4d516dd0-840a-4ae0-a3f1-cda3d5614e03
Walker, Johanna, Catherine
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Simperl, Elena
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Thuermer, Gefion
4d516dd0-840a-4ae0-a3f1-cda3d5614e03
Walker, Johanna, Catherine
aef93dc8-1936-4dd8-9921-64bd811b4a01
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67

Thuermer, Gefion, Walker, Johanna, Catherine and Simperl, Elena (2019) Data Sharing Toolkit: Lessons learned, resources and recommendations for sharing data.

Record type: Other

Abstract

Data plays a major role in the European economy, and building a European data economy is one of the strategic goals of the European Commission. Through the increase of data science techniques, not least Machine Learning (ML) and Artificial Intelligence (AI), the value and role of data as an asset becomes ever more crucial. This has made it more important for data to be accessible. However, much of the data that many solutions require are held within private organisations - and are only available if they are shared. Data sharing in this sense means allowing third parties specifically permissioned access to datasets to generate value.
This toolkit has been developed to help organisations that want to generate value by sharing data or facilitating data sharing. We explain the concept, challenges, and processes to enable successful data sharing, and provide resources and recommendations. It is derived from experience collected in the Data Pitch programme and related national and international initiatives, such as the Smart Cities Innovation Framework Implementation (SciFi), the European Data Incubator (EDI), as well as several recent pilots for data trusts in the UK.

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Published date: 25 June 2019

Identifiers

Local EPrints ID: 436050
URI: http://eprints.soton.ac.uk/id/eprint/436050
PURE UUID: b9b24735-f8dd-43cd-9dab-f27ed5820904
ORCID for Gefion Thuermer: ORCID iD orcid.org/0000-0001-7345-0000
ORCID for Johanna, Catherine Walker: ORCID iD orcid.org/0000-0002-5498-8670
ORCID for Elena Simperl: ORCID iD orcid.org/0000-0003-1722-947X

Catalogue record

Date deposited: 27 Nov 2019 17:30
Last modified: 07 Oct 2020 08:23

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