Literature DB >> 34840429

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

Götz Hoeppe1.   

Abstract

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.
© The Author(s) 2021.

Entities:  

Keywords:  Algorithms; Astronomy; Collaborative research practices; Collective knowledge; Coordinative artifacts; Data reuse; Data sharing; Ethnomethodology; Testing

Year:  2021        PMID: 34840429      PMCID: PMC8608782          DOI: 10.1007/s10606-021-09407-2

Source DB:  PubMed          Journal:  Comput Support Coop Work        ISSN: 0925-9724            Impact factor:   1.825


  11 in total

1.  Science friction: data, metadata, and collaboration.

Authors:  Paul N Edwards; Matthew S Mayernik; Archer L Batcheller; Geoffrey C Bowker; Christine L Borgman
Journal:  Soc Stud Sci       Date:  2011-10       Impact factor: 3.885

Review 2.  Algorithmic accountability.

Authors:  Hetan Shah
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2018-09-13       Impact factor: 4.226

3.  Working data together: the accountability and reflexivity of digital astronomical practice.

Authors:  Götz Hoeppe
Journal:  Soc Stud Sci       Date:  2014-04       Impact factor: 3.885

4.  Data sharing by scientists: practices and perceptions.

Authors:  Carol Tenopir; Suzie Allard; Kimberly Douglass; Arsev Umur Aydinoglu; Lei Wu; Eleanor Read; Maribeth Manoff; Mike Frame
Journal:  PLoS One       Date:  2011-06-29       Impact factor: 3.240

5.  Researcher perspectives on publication and peer review of data.

Authors:  John Ernest Kratz; Carly Strasser
Journal:  PLoS One       Date:  2015-02-23       Impact factor: 3.240

6.  Attitudes and norms affecting scientists' data reuse.

Authors:  Renata Gonçalves Curty; Kevin Crowston; Alison Specht; Bruce W Grant; Elizabeth D Dalton
Journal:  PLoS One       Date:  2017-12-27       Impact factor: 3.240

7.  Metadata accounts: Achieving data and evidence in scientific research.

Authors:  Matthew S Mayernik
Journal:  Soc Stud Sci       Date:  2019-07-27       Impact factor: 3.885

8.  Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide.

Authors:  Carol Tenopir; Elizabeth D Dalton; Suzie Allard; Mike Frame; Ivanka Pjesivac; Ben Birch; Danielle Pollock; Kristina Dorsett
Journal:  PLoS One       Date:  2015-08-26       Impact factor: 3.240

9.  How do astronomers share data? Reliability and persistence of datasets linked in AAS publications and a qualitative study of data practices among US astronomers.

Authors:  Alberto Pepe; Alyssa Goodman; August Muench; Merce Crosas; Christopher Erdmann
Journal:  PLoS One       Date:  2014-08-28       Impact factor: 3.240

10.  The FAIR Guiding Principles for scientific data management and stewardship.

Authors:  Mark D Wilkinson; Michel Dumontier; I Jsbrand Jan Aalbersberg; Gabrielle Appleton; Myles Axton; Arie Baak; Niklas Blomberg; Jan-Willem Boiten; Luiz Bonino da Silva Santos; Philip E Bourne; Jildau Bouwman; Anthony J Brookes; Tim Clark; Mercè Crosas; Ingrid Dillo; Olivier Dumon; Scott Edmunds; Chris T Evelo; Richard Finkers; Alejandra Gonzalez-Beltran; Alasdair J G Gray; Paul Groth; Carole Goble; Jeffrey S Grethe; Jaap Heringa; Peter A C 't Hoen; Rob Hooft; Tobias Kuhn; Ruben Kok; Joost Kok; Scott J Lusher; Maryann E Martone; Albert Mons; Abel L Packer; Bengt Persson; Philippe Rocca-Serra; Marco Roos; Rene van Schaik; Susanna-Assunta Sansone; Erik Schultes; Thierry Sengstag; Ted Slater; George Strawn; Morris A Swertz; Mark Thompson; Johan van der Lei; Erik van Mulligen; Jan Velterop; Andra Waagmeester; Peter Wittenburg; Katherine Wolstencroft; Jun Zhao; Barend Mons
Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

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