Data from: Data sharing by scientists: practices and perceptions

Background: Scientific research in the 21st century is more data intensive
and collaborative than in the past. It is important to study the data
practices of researchers –data accessibility, discovery, re-use,
preservation and, particularly, data sharing. Data sharing is a valuable
part of the scientific method allowing for verification of results and
extending research from prior results. Methodology/Principal Findings: A
total of 1329 scientists participated in this survey exploring current
data sharing practices and perceptions of the barriers and enablers of
data sharing. Scientists do not make their data electronically available
to others for various reasons, including insufficient time and lack of
funding. Most respondents are satisfied with their current processes for
the initial and short-term parts of the data or research lifecycle
(collecting their research data; searching for, describing or cataloging,
analyzing, and short-term storage of their data) but are not satisfied
with long-term data preservation. Many organizations do not provide
support to their researchers for data management both in the short- and
long-term. If certain conditions are met (such as formal citation and
sharing reprints) respondents agree they are willing to share their data.
There are also significant differences and approaches in data management
practices based on primary funding agency, subject discipline, age, work
focus, and world region. Conclusions/Significance: Barriers to effective
data sharing and preservation are deeply rooted in the practices and
culture of the research process as well as the researchers themselves. New
mandates for data management plans from NSF and other federal agencies and
world-wide attention to the need to share and preserve data could lead to
changes. Large scale programs, such as the NSF-sponsored DataNET
(including projects like DataONE) will both bring attention and resources
to the issue and make it easier for scientists to apply sound data
management principles.