research-article

Open access

The Craft and Coordination of Data Curation: Complicating Workflow Views of Data Science

Authors:

Andrea K. Thomer,

Jeremy J. York,

Allison R. B. Tyler,

Libby Hemphill,

Elizabeth YakelAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 6, Issue CSCW2

Article No.: 414, Pages 1 - 29

https://doi.org/10.1145/3555139

Published: 11 November 2022 Publication History

Abstract

Data curation is the process of making a dataset fit-for-use and archivable. It is critical to data-intensive science because it makes complex data pipelines possible, studies reproducible, and data reusable. Yet the complexities of the hands-on, technical, and intellectual work of data curation is frequently overlooked or downplayed. Obscuring the work of data curation not only renders the labor and contributions of data curators invisible but also hides the impact that curators' work has on the later usability, reliability, and reproducibility of data. To better understand the work and impact of data curation, we conducted a close examination of data curation at a large social science data repository, the Inter-university Consortium for Political and Social Research (ICPSR). We asked: What does curatorial work entail at ICPSR, and what work is more or less visible to different stakeholders and in different contexts? And, how is that curatorial work coordinated across the organization? We triangulated accounts of data curation from interviews and records of curation in Jira tickets to develop a rich and detailed account of curatorial work. While we identified numerous curatorial actions performed by ICPSR curators, we also found that curators rely on a number of craft practices to perform their jobs. The reality of their work practices defies the rote sequence of events implied by many life cycle or workflow models. Further, we show that craft practices are needed to enact data curation best practices and standards. The craft that goes into data curation is often invisible to end users, but it is well recognized by ICPSR curators and their supervisors. Explicitly acknowledging and supporting data curators as craftspeople is important in creating sustainable and successful curatorial infrastructures.

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Bhardwaj EGujral HWu SZogheib CMaharaj TBecker C(2024)Machine learning data practices through a data curation lens: An evaluation frameworkProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658955(1055-1067)Online publication date: 3-Jun-2024
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Fan LLafia SWofford MThomer AYakel EHemphill LKlein MBen-David AJäschke RKelly M(2024)Mining Semantic Relations in Data References to Understand the Roles of Research Data in Academic LiteratureProceedings of the 2023 ACM/IEEE Joint Conference on Digital Libraries10.1109/JCDL57899.2023.00039(215-227)Online publication date: 26-Jun-2024
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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 6, Issue CSCW2

CSCW

November 2022

8205 pages

EISSN:2573-0142

DOI:10.1145/3571154

Editor:
Jeff Nichols
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Association for Computing Machinery

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Published: 11 November 2022

Published in PACMHCI Volume 6, Issue CSCW2

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Bhardwaj EGujral HWu SZogheib CMaharaj TBecker C(2024)Machine learning data practices through a data curation lens: An evaluation frameworkProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658955(1055-1067)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3630106.3658955
Fan LLafia SWofford MThomer AYakel EHemphill LKlein MBen-David AJäschke RKelly M(2024)Mining Semantic Relations in Data References to Understand the Roles of Research Data in Academic LiteratureProceedings of the 2023 ACM/IEEE Joint Conference on Digital Libraries10.1109/JCDL57899.2023.00039(215-227)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1109/JCDL57899.2023.00039
Bhardwaj EKhaiter P(2024)Is the climate getting WARMer? A framework and tool for climate data comparisonEnvironmental Modelling & Software10.1016/j.envsoft.2023.105879171:COnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.envsoft.2023.105879
Yakel EFaniel IRobert L(2024)An empirical examination of data reuser trust in a digital repositoryJournal of the Association for Information Science and Technology10.1002/asi.24933Online publication date: 20-Jun-2024
https://doi.org/10.1002/asi.24933
Li WWang JWang F(2024)Curating the Chinese ancient book catalogs: Leveraging the dual roles of humanities scholars as experts and users in collaborative practiceJournal of the Association for Information Science and Technology10.1002/asi.24894Online publication date: 14-Apr-2024
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Plantin JThomer A(2023)Platforms, programmability, and precarity: The platformization of research repositories in academic librariesNew Media & Society10.1177/14614448231176758(146144482311767)Online publication date: 6-Jun-2023
https://doi.org/10.1177/14614448231176758
Thomer ARayburn A(2023)“A Patchwork of Data Systems”: Quilting as an Analytic Lens and Stabilizing Practice for Knowledge InfrastructuresScience, Technology, & Human Values10.1177/01622439231175535(016224392311755)Online publication date: 25-May-2023
https://doi.org/10.1177/01622439231175535
Mosconi Gde Carvalho ASyed HRandall DKarasti HPipek V(2023)Fostering Research Data Management in Collaborative Research Contexts: Lessons learnt from an ‘Embedded’ Evaluation of ‘Data Story’Computer Supported Cooperative Work10.1007/s10606-023-09467-632:4(911-949)Online publication date: 15-May-2023
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Adorjan A(2023)Towards a Researcher-in-the-loop Driven Curation Approach for Quantitative and Qualitative Research MethodsNew Trends in Database and Information Systems10.1007/978-3-031-42941-5_58(647-655)Online publication date: 31-Aug-2023
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Senagi KTonnang H(2022)A Novel Tightly Coupled Information System for Research Data ManagementElectronics10.3390/electronics1119319611:19(3196)Online publication date: 5-Oct-2022
https://doi.org/10.3390/electronics11193196
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