giving the investigator a defined period of exclusive use of the data, with the exclusivity ending upon the publication of results, after a particular length of time, or when data are deposited in a data center or archive.

There is great variation among research fields in their data-sharing norms, to such an extent that different fields can be said to have different data cultures. (Box 3-3 describes aspects of the data culture in economics.) A recent report commissioned by the Research Information Network of the United Kingdom examined data-sharing practices and expectations across a number of fields (Table 3-1).6 The report highlights the global importance and relevance of data accessibility in research, as well as the fact that differences between fields are often more important than national differences in determining data-sharing practices. The international aspects of data access and sharing are discussed in more detail below.

Observational astronomy offers a good example of the data-sharing norms that can characterize a field of research. Astronomical data often can be used for multiple purposes and are usually made public, but proprietary periods in which only the members of a research team have access to data are common. The European Southern Observatory (Europe’s large optical observatory) and the National Aeronautics and Space Administration have 12-month proprietary periods. The U.S. National Optical Astronomy Observatory has an 18-month proprietary time. These periods provide researchers with an opportunity to make discoveries as a reward for dedicating significant periods of their careers to creating new facilities and developing new techniques. They also provide an opportunity for critical evaluation of the data before they are released.

In the high-energy physics community, collaborations are so large and the experiments so complex—with hundreds of scientists involved with the operation of a single detector—that it could take years for an independent scientist to learn enough to reanalyze the data. The data of each collaboration are treated as proprietary. Other groups that want to undertake the same measurement must form their own large collaboration and repeat the experiment. As explained in Box 2-1, large collaborations in high-energy physics involve elaborate procedures for internal scrutiny of and validation of data.

Cultural norms and expectations in research fields regarding data can change over time. For example, as data sharing has proven increasingly valuable to the advancement of research in many areas of the life sciences, researchers, sponsors, research institutions, and other stakeholders have built new infrastructure and established guidelines to facilitate data sharing. A 2003 National Research Council study (Box 3-4) recommended guidelines for the sharing of


Alma Swan and Sheridan Brown. 2008. To Share or not to Share: Publication and Quality Assurance of Research Data Outputs. Report Commissioned by the Research Information Network. June. Available at:

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