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dc.contributor.authorLeonelli, S
dc.date.accessioned2022-09-01T09:49:31Z
dc.date.issued2022-10-21
dc.date.updated2022-08-25T12:05:10Z
dc.description.abstractThis paper examines classification practices in the domain of plant data semantics, and particularly methods used to label plant traits to foster the collection, management, linkage and analysis of data about crops across locations – which crucially inform research and interventions on plants and agriculture. The efforts required to share data place in sharp relief the forms of diversity characterizing the systems used to capture the biological and environmental characteristics of plant variants: particularly the biological, cultural, scientific and semantic diversity affecting the identification and description of plant traits, the methods used to generate and process data, and the goals and skills of those with relevant expertise – including farmers and breeders. Through a study of the Crop Ontology (which explicitly recognizes and negotiates diversity) and its application to cassava breeding, I argue for a process-sensitive approach to the naming of plant traits that focuses on documenting environmental processes instead of biological products. I claim that this approach can foster reliable linkage and robust re-use of plant data, while at the same time facilitating dialogue between data scientists, plant researchers, breeders, and other relevant experts in ways that crucially inform agricultural interventions. I conclude that the study of data semantics and related descriptors constitutes a productive and underexplored way to think about the epistemic import of naming traits within plant science. The effort to articulate semantic differences among plant varieties and methods of data processing can generate newly inclusive ways to develop and communicate biological knowledge. In turn, such practices have the potential to defy existing understandings of systematisation and hierarchies of expertise in biology, thus bolstering the extent to which plant science can support biodiversity and sustainable agriculture.en_GB
dc.description.sponsorshipEuropean Research Council (ERC)en_GB
dc.description.sponsorshipAustralian Research Council (ARC)en_GB
dc.description.sponsorshipAlan Turing Instituteen_GB
dc.description.sponsorshipWissenschaftskolleg zu Berlinen_GB
dc.identifier.citationVol. 14, article 16en_GB
dc.identifier.doi10.3998/ptpbio.3364
dc.identifier.grantnumber335925en_GB
dc.identifier.grantnumber101001145en_GB
dc.identifier.grantnumberDP160102989en_GB
dc.identifier.grantnumberEP/N510129/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/130633
dc.identifierORCID: 0000-0002-7815-6609 (Leonelli, Sabina)
dc.language.isoenen_GB
dc.publisherMichigan Publishingen_GB
dc.rights© 2022 Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits anyone to download, copy, distribute, display, or adapt the text without asking for permission, provided that the creator(s) are given full credit.
dc.subjectdata scienceen_GB
dc.subjecthenomicsen_GB
dc.subjectdiversityen_GB
dc.subjectcomputational ontologiesen_GB
dc.subjectdatabasesen_GB
dc.subjectplant traitsen_GB
dc.subjectclassificationen_GB
dc.subjecttaxonomyen_GB
dc.subjectprecision agricultureen_GB
dc.titleProcess-Sensitive Naming: Trait Descriptors and the Shifting Semantics of Plant (Data) Scienceen_GB
dc.typeArticleen_GB
dc.date.available2022-09-01T09:49:31Z
dc.descriptionThis is the final version. Available on open access from Michigan Publishing via the DOI in this recorden_GB
dc.identifier.eissn2475-3025
dc.identifier.journalPhilosophy, Theory and Practice in Biologyen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-08-08
dcterms.dateSubmitted2022-01-25
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-08-08
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-08-25T12:05:13Z
refterms.versionFCDAM
refterms.dateFOA2022-11-23T15:07:10Z
refterms.panelCen_GB


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© 2022 Author(s).
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0
International license, which permits anyone to download, copy, distribute, display, or adapt the text
without asking for permission, provided that the creator(s) are given full credit.
Except where otherwise noted, this item's licence is described as © 2022 Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits anyone to download, copy, distribute, display, or adapt the text without asking for permission, provided that the creator(s) are given full credit.