Literature DB >> 31354073

Metadata accounts: Achieving data and evidence in scientific research.

Matthew S Mayernik1.   

Abstract

'Metadata' has received a fraction of the attention that 'data' has received in sociological studies of scientific research. A neglect of 'metadata' reduces the attention on a number of critical aspects of scientific work processes, including documentary work, accountability relations, and collaboration routines. Metadata processes and products are essential components of the work needed to practically accomplish day-to-day scientific research tasks, and are central to ensuring that research findings and products meet externally driven standards or requirements. This article is an attempt to open up the discussion on and conceptualization of metadata within the sociology of science and the sociology of data. It presents ethnographic research of metadata creation within everyday scientific practice, focusing on how researchers document, describe, annotate, organize and manage their data, both for their own use and the use of researchers outside of their project. In particular, this article argues that the role and significance of metadata within scientific research contexts are intimately tied to the nature of evidence and accountability within particular social situations. Studying metadata can (1) provide insight into the production of evidence, that is, how something we might call 'data' becomes able to serve an evidentiary role, and (2) provide a mechanism for revealing what people in research contexts are held accountable for, and what they achieve accountability with.

Entities:  

Keywords:  accountability; data; evidence; metadata

Year:  2019        PMID: 31354073     DOI: 10.1177/0306312719863494

Source DB:  PubMed          Journal:  Soc Stud Sci        ISSN: 0306-3127            Impact factor:   3.885


  4 in total

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

Authors:  Götz Hoeppe
Journal:  Comput Support Coop Work       Date:  2021-10-25       Impact factor: 1.825

2.  Caring for data: Value creation in a data-intensive research laboratory.

Authors:  Clémence Pinel; Barbara Prainsack; Christopher McKevitt
Journal:  Soc Stud Sci       Date:  2020-02-13       Impact factor: 3.885

Review 3.  Conceptualising fairness: three pillars for medical algorithms and health equity.

Authors:  Laura Sikstrom; Marta M Maslej; Katrina Hui; Zoe Findlay; Daniel Z Buchman; Sean L Hill
Journal:  BMJ Health Care Inform       Date:  2022-01

4.  Tabular strategies for metadata in ecology, evolution, and the environmental sciences.

Authors:  C J Lortie; Camila Vargas Poulsen; Julien Brun; Li Kui
Journal:  Ecol Evol       Date:  2022-08-25       Impact factor: 3.167

  4 in total

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