Box 1. The Toronto statement

From the following article:

Prepublication data sharing

Toronto International Data Release Workshop Authors

Nature 461, 168-170(10 September 2009)

doi:10.1038/461168a

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Rapid prepublication data release should be encouraged for projects with the following attributes:

  • Large scale (requiring significant resources over time)
  • Broad utility
  • Creating reference data sets
  • Associated with community buy-in

Funding agencies should facilitate the specification of data-release policies for relevant projects by:

  • Explicitly informing applicants of data-release requirements, especially mandatory prepublication data release
  • Ensuring that evaluation of data release plans is part of the peer-review process
  • Proactively establishing analysis plans and timelines for projects releasing data prepublication
  • Fostering investigator-initiated prepublication data release
  • Helping to develop appropriate consent, security, access and governance mechanisms that protect research participants while encouraging prepublication data release
  • Providing long-term support of databases

Data producers should state their intentions and enable analyses of their data by:

  • Informing data users about the data being generated, data standards and quality, planned analyses, timelines, and relevant contact information, ideally through publication of a citable marker paper near the start of the project or by provision of a citable URL at the project or funding-agency website
  • Providing relevant metadata (e.g., questionnaires, phenotypes, environmental conditions, and laboratory methods) that will assist other researchers in reproducing and/or independently analysing the data, while protecting interests of individuals enrolled in studies focusing on humans
  • Ensuring that research participants are informed that their data will be shared with other scientists in the research community
  • Publishing their initial global analyses, as stated in the marker paper or citable URL, in a timely fashion
  • Creating databases designed to archive all data (including underlying raw data) in an easily retrievable form and facilitate usage of both pre-processed and processed data

Data analysts/users should freely analyse released prepublication data and act responsibly in publishing analyses of those data by:

  • Respecting the scientific etiquette that allows data producers to publish the first global analyses of their data set
  • Reading the citeable document associated with the project
  • Accurately and completely citing the source of prepublication data, including the version of the data set (if appropriate)
  • Being aware that released prepublication data may be associated with quality issues that will be later rectified by the data producers
  • Contacting the data producers to discuss publication plans in the case of overlap between planned analyses
  • Ensuring that use of data does not harm research participants and is in conformity with ethical approvals

Scientific journal editors should engage the research community about issues related to prepublication data release and provide guidance to authors and reviewers on the third-party use of prepublication data in manuscripts

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