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Related Experiment Video

Updated: Jun 10, 2026

Establishment of a Clinic-based Biorepository

Establishment of a Clinic-based Biorepository

Published on: May 29, 2017

Data sharing, small science and institutional repositories.

Melissa H Cragin¹, Carole L Palmer, Jacob R Carlson

¹Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign, Champaign, IL, USA. cragin@illinois.edu

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|August 4, 2010

Summary

This summary is machine-generated.

Scientists are willing to share research data, but practices vary widely. Understanding these diverse data characteristics and sharing needs is crucial for effective data curation services and institutional repositories.

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Area of Science:

Scientific data sharing practices
Research data management

Background:

Scientists' perspectives on data sharing are complex and varied.
Understanding these nuances is essential for developing effective data stewardship strategies.

Purpose of the Study:

To investigate scientists' willingness to share research data, including what, with whom, and when.
To identify the dimensions and variations in data sharing practices.
To understand scientists' views on 'sharable' data representations and reuse duration.

Main Methods:

Analysis of findings from the Data Curation Profiles project research.
Examination of scientists' discussions and reported sharing incidents.

Main Results:

Data sharing involves diverse interpretations and practices across subdisciplines.
Institutional repositories (IRs) can support data stewardship when data characteristics and practices are understood.
Scientists value specific data representations for reuse and anticipate varying reuse durations.
Barriers to sharing and concerns about data misuse were identified.

Conclusions:

Data curation services must accommodate a wide range of subdisciplinary data characteristics and sharing practices.
Institutional repositories play a role in the stewardship and mobilization of scientific research data.
Understanding scientists' views on data sharing is key to facilitating effective data reuse and management.