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

Clémence Pinel¹, Barbara Prainsack^2,3, Christopher McKevitt⁴

¹Centre for Medical Science and Technology Studies, Department of Public Health, University of Copenhagen, Denmark.

Social Studies of Science

|February 14, 2020

Summary

This summary is machine-generated.

Researchers build affective relationships with data, termed "care," which is crucial for data production and valuation in research. This often-overlooked practice highlights the human element in data-intensive science.

Keywords:

care data data-intensive research relational ontology valuation ‘omics’ research

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Area of Science:

Sociology of Science and Technology
Informatics
Gender Studies

Background:

Critical data studies examine 'data work' in research.
Existing scholarship highlights the importance of care in scientific endeavors.
Data-intensive research relies heavily on the production and maintenance of databases.

Purpose of the Study:

To analyze the role of affective and attentive relationships in data production and maintenance.
To introduce and define 'care' as a specific form of data work.
To explore the institutional and hierarchical contexts of caring practices in research.

Main Methods:

Ethnographic observations of staff in a twin research laboratory.
Analysis of practices involved in producing and maintaining a research database.
Qualitative examination of human-data relationships and caring practices.

Main Results:

Staff engage in 'care' for data, involving affective and attentive relationships.
Caring practices foster long-term researcher-data relationships and a sense of responsibility.
These care practices contribute to data valuation and valorization within the institution.
Caring practices were found to be gendered and unequally valued in reward systems.

Conclusions:

Care for data is a vital, yet under-recognized, practice in data-intensive research.
Affective engagements with data are integral to its value and utility.
Understanding and valuing care practices can improve research environments and data quality.