Document Type
Article
Publication Date
1-1-2019
Publication Title
Data Science Journal
Publication Title
Data Science Journal
Volume
18
Issue
1
Abstract
Addressing the most pressing contemporary social, environmental, and technological challenges will require integrating insights and sharing data across disciplines, geographies, and cultures. Strengthening international data sharing networks will not only demand advancing technical, legal, and logistical infrastructure for publishing data in open, accessible formats; it will also require recognizing, respecting, and learning to work across diverse data cultures. This essay introduces a heuristic for pursuing richer characterizations of the “data cultures” at play in international, interdisciplinary data sharing. The heuristic prompts cultural analysts to query the contexts of data sharing for a particular discipline, institution, geography, or project at seven scales – the meta, macro, meso, micro, techno, data, and nano. The essay articulates examples of the diverse cultural forces acting upon and interacting with researchers in different communities at each scale. The heuristic we introduce in this essay aims to elicit from researchers the beliefs, values, practices, incentives, and restrictions that impact how they think about and approach data sharing – not in an effort to iron out differences between disciplines, but instead to showcase and affirm the diversity of traditions and modes of analysis that have shaped how data gets collected, organized, and interpreted in diverse settings.
Recommended Citation
Poirier, Lindsay and Costelloe-Kuehn, Brandon, "Data Sharing at Scale: A Heuristic for Affirming Data Cultures" (2019). Statistical and Data Sciences: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/sds_facpubs/57
Digital Object Identifier (DOI)
10.5334/dsj-2019-048
Comments
Archived as published.