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Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set

This article provides a novel perspective on the use and reuse of scientific data by providing a chronological ethnographic account and analysis of how a team of researchers prepared an astronomical catalogue (a table of measured properties of galaxies) for public release. Whereas much existing work...

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Autor principal: Hoeppe, Götz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8608782/
https://www.ncbi.nlm.nih.gov/pubmed/34840429
http://dx.doi.org/10.1007/s10606-021-09407-2
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author Hoeppe, Götz
author_facet Hoeppe, Götz
author_sort Hoeppe, Götz
collection PubMed
description This article provides a novel perspective on the use and reuse of scientific data by providing a chronological ethnographic account and analysis of how a team of researchers prepared an astronomical catalogue (a table of measured properties of galaxies) for public release. Whereas much existing work on data reuse has focused on information about data (such as metadata), whose form or lack has been described as a hurdle for reusing data successfully, I describe how data makers tried to instruct users through the processed data themselves. The fixation of this catalogue was a negotiation, resulting in what was acceptable to team members and coherent with the diverse data uses pertinent to their completed work. It was through preparing their catalogue as an ‘instructing data object’ that this team seeked to encode its members’ knowledge of how the data were processed and to make it consequential for users by devising methodical ways to structure anticipated uses. These methods included introducing redundancies that would help users to self-correct mistaken uses, selectively deleting data, and deflecting accountability through making notational choices. They dwell on an understanding of knowledge not as exclusively propositional (such as the belief in propositions), but as embedded in witnessable activities and the products of these activities. I discuss the implications of this account for philosophical notions of collective knowledge and for theorizing coordinative artifacts in CSCW. Eventually, I identify a tension between ‘using algorithms’ and ‘doing science’ in preparing data sets and show how it was resolved in this case.
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spelling pubmed-86087822021-11-24 Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set Hoeppe, Götz Comput Support Coop Work Research Article This article provides a novel perspective on the use and reuse of scientific data by providing a chronological ethnographic account and analysis of how a team of researchers prepared an astronomical catalogue (a table of measured properties of galaxies) for public release. Whereas much existing work on data reuse has focused on information about data (such as metadata), whose form or lack has been described as a hurdle for reusing data successfully, I describe how data makers tried to instruct users through the processed data themselves. The fixation of this catalogue was a negotiation, resulting in what was acceptable to team members and coherent with the diverse data uses pertinent to their completed work. It was through preparing their catalogue as an ‘instructing data object’ that this team seeked to encode its members’ knowledge of how the data were processed and to make it consequential for users by devising methodical ways to structure anticipated uses. These methods included introducing redundancies that would help users to self-correct mistaken uses, selectively deleting data, and deflecting accountability through making notational choices. They dwell on an understanding of knowledge not as exclusively propositional (such as the belief in propositions), but as embedded in witnessable activities and the products of these activities. I discuss the implications of this account for philosophical notions of collective knowledge and for theorizing coordinative artifacts in CSCW. Eventually, I identify a tension between ‘using algorithms’ and ‘doing science’ in preparing data sets and show how it was resolved in this case. Springer Netherlands 2021-10-25 2021 /pmc/articles/PMC8608782/ /pubmed/34840429 http://dx.doi.org/10.1007/s10606-021-09407-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and repr00oduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Hoeppe, Götz
Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set
title Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set
title_full Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set
title_fullStr Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set
title_full_unstemmed Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set
title_short Encoding Collective Knowledge, Instructing Data Reusers: The Collaborative Fixation of a Digital Scientific Data Set
title_sort encoding collective knowledge, instructing data reusers: the collaborative fixation of a digital scientific data set
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8608782/
https://www.ncbi.nlm.nih.gov/pubmed/34840429
http://dx.doi.org/10.1007/s10606-021-09407-2
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