Journals publishing and describing data

At the moment, two types of journals stand in the front line of promoting the opening and sharing of data: Journals that require data availability as a precondition for publishing, and scientific data journals that publish descriptions of research datasets.
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Journals that require data availability

Many journals have adopted data policies demanding data availability in conjunction with the article, for example Nature, PLOS and Science.

The main task in their policy is to provide an easy access to data for their readers. Linking research data directly with the published article helps to understand the claims and results. The direct link definitely generates surplus value to the wider academic community beyond the research group and helps readers to assess the benefit of the research.

Because of the diversity of data types and manifold ways to present data, the journals provide different methods to access data. The journals recommend storing data in an open data repository.If this is not possible, the data can be

  • given in the main text of the article
  • supplementary information
  • available from the owner upon request.

Scientific data journals

The key issue in scientific data journals is that the articles do not include analysis of data, but the journals provide a forum to describe and document research data sets. For the researchers that have a specific interest to produce or create data, the data journals may be a relevant publishing channel.  

Examples on general or multidisciplinary data journals

Data in Brief by Elsevier:

  • Promotes external, public repositories and recommends interlinking the data and the article.
  • Elsevier recommends to publish a data article via the journal, even in cases where the article has been published in another Elsevier journal.
  • Enables authors “enrich online article by uploading relevant computer code and data to the RunMyCode repository … “.

Scientific Data by Nature:

  • Publish descriptions of data from new or published studies; in latter case dataset must provide new content.
  • Covers a broad range of natural science disciplines and will consider descriptions of quantitative datasets from the social sciences, too.

Examples on research field specific data journals

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