Actionable data for precision oncology: Framing trustworthy evidence for exploratory research and clinical diagnostics
dc.contributor.author | Tempini, N | |
dc.contributor.author | Leonelli, S | |
dc.date.accessioned | 2021-02-18T15:59:55Z | |
dc.date.issued | 2021-02-11 | |
dc.description.abstract | Huge amounts of genomic data produced by researchers around the world undermine data-centred discovery and therapeutic development. This paper considers how researchers make decisions about the actionability of specific datasets and the conditions that allow such data to be trusted. We discuss the case of COSMIC, a leading cancer genomics database which aggregates a large amount of sources. We research what the actionability of cancer data means in different situations of use, contrasting exploratory and diagnostics research. They highlight different questions and concerns upon genomic data use in medical research. At the same time, strategies and justifications pursued to evaluate and re-use can also share important similarities. To explain differences and similarities, we argue for an understanding of actionability and trust in data that depends on the goals and resources within the situation of inquiry, and the social epistemology of standards. | en_GB |
dc.description.sponsorship | Alan Turing Institute | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.description.sponsorship | European Research Council (ERC) | en_GB |
dc.identifier.citation | Vol. 272, article 113760 | en_GB |
dc.identifier.doi | 10.1016/j.socscimed.2021.113760 | |
dc.identifier.grantnumber | EP/N510129/1 | en_GB |
dc.identifier.grantnumber | 335925 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/124805 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.rights | © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | en_GB |
dc.subject | Cancer genomics | en_GB |
dc.subject | Actionability | en_GB |
dc.subject | COSMIC | en_GB |
dc.subject | Data infrastructure | en_GB |
dc.subject | Precision medicine | en_GB |
dc.subject | Data trustworthiness | en_GB |
dc.subject | Big data | en_GB |
dc.subject | Data curation | en_GB |
dc.title | Actionable data for precision oncology: Framing trustworthy evidence for exploratory research and clinical diagnostics | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2021-02-18T15:59:55Z | |
dc.identifier.issn | 0277-9536 | |
dc.description | This is the final version. Available on open access from Elsevier via the DOI in this record | en_GB |
dc.identifier.journal | Social Science and Medicine | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2021-02-04 | |
exeter.funder | ::European Commission | en_GB |
exeter.funder | ::Alan Turing Institute | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2021-02-04 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2021-02-13T14:46:00Z | |
refterms.versionFCD | P | |
refterms.dateFOA | 2021-02-18T16:00:20Z | |
refterms.panel | C | en_GB |
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Except where otherwise noted, this item's licence is described as © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).