Archived: Principles of Data Sharing in Neuroscience
Preface:
The goal of The Human Brain Project is the development of neuroscience informatics: the creation and federation of web-based databases, analytical tools, and computational models to facilitate the open sharing and utilization of primary research data for all of neuroscience. The Human Brain Project principal investigators in support of data sharing offer draft guidelines, designed to reduce technological and sociological barriers to effective data sharing. These opinions and proposals, based on the individual and collaborative experiences of those involved with this program and do not reflect official government policy
The basic considerations for sharing data are:
- Data produced with public funds should be shared for the public good
- Journals publish data, as summaries and in non-machine-readable and largely non-reanalyzable form, should be supplemented by open availability of the primary datasets themselves
- Understanding the dynamic complexity of the brain will require data integration between and among all levels of structure and function
- Research efficiency is greatly increased by making research data available for reanalysis and meta-analysis.
- Current NIH policy mandates a statement on data sharing for high-direct-cost grant applications
Draft Guidelines:
- The primary research data and metadata underlying a scientific report should be made available for sharing, consonant with appropriate privacy or proprietary restrictions, at the time they are published in a peer review journal.
- Both sharing and mining data should be universally recognized as an essential component of research and rewarded accordingly.
- Sharing should not imply relinquishing. Re-use of data should require clear and prominent attribution of the data and acknowledgement of the originator.
- Citation and acknowledgment of shared data should be required, either through inclusion of the data originator as a co-author (with their involvement and permission), as a separate byline in the header information, or as a citation in the publication references.
- Investigators and grantee institutions, not third-party repositories, should retain ownership of shareable data. Commercial exploitation of shared data without appropriate recognition, including possible compensation, may represent misuse of intellectual property.
- Expenses associated with data sharing and mining need to be supported.
- The scope of sharable data should be acknowledged as variable and dependent upon the standards and practices of different fields or techniques. Consequently, a variety of models for data sharing may be adopted, including both central databases and peer-to-peer solutions.
- Appropriate de-identification techniques should allow sharing of human data, while maintaining appropriate privacy required by both HIPAA and the Common Rule. In addition, informed consent documents should provide sufficient detail about the intent to archive, share and re-analyze data (and samples).
Rationale:
Sharing data has great potential to increase the efficiency of the rate of knowledge attainment. Sharing will both enhance the utility of existing data and promote competition in the marketplace of scientific ideas. It will permit reanalysis and meta-analyses beyond the focus or time constraints of the original data collectors. Informed by shared data new hypotheses can be advanced; current hypotheses can be re-tested on new and old data. Archived data can also be used to develop and validate new analytic methods or technology.
A fuller version of these Principles is available at http://datasharing.net
