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Data sharing by scientists: practices and perceptions.

Carol Tenopir¹, Suzie Allard, Kimberly Douglass

¹School of Information Sciences, University of Tennessee, Knoxville, Tennessee, United States of America. ctenopir@utk.edu

|July 9, 2011

Summary

This summary is machine-generated.

Scientists face barriers to data sharing due to time, funding, and organizational support. While willing to share under certain conditions, long-term data preservation remains a challenge, requiring cultural shifts and new initiatives.

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Area of Science:

Scientific research
Data management
Research lifecycle

Background:

21st-century research is increasingly data-intensive and collaborative.
Understanding researcher data practices (accessibility, discovery, re-use, preservation, sharing) is crucial.
Data sharing is vital for scientific verification and building upon prior results.

Purpose of the Study:

To explore current data sharing practices among scientists.
To identify barriers and enablers of data sharing.
To understand researcher satisfaction with different stages of the data lifecycle.

Main Methods:

Survey of 1329 scientists on data sharing practices and perceptions.
Exploration of reasons for not making data electronically available.
Analysis of satisfaction levels with data management processes.
Investigation of organizational support for data management.
Examination of conditions influencing willingness to share data.
Assessment of variations in data management based on demographics and funding.

Main Results:

Insufficient time and funding are key barriers to data sharing.
Scientists are satisfied with short-term data management but not long-term preservation.
Many organizations lack adequate data management support.
Willingness to share data increases with conditions like formal citation.
Data management practices vary significantly by funding, discipline, age, and region.

Conclusions:

Barriers to data sharing and preservation are embedded in research culture and practices.
New mandates for data management plans and global attention to data sharing can drive change.
Large-scale programs like DataNET can provide resources and facilitate sound data management principles.