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Elsevier
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Research data

Introduction

Data sharing enables others to reuse the results of experiments and supports the creation of new science that is built on previous findings, making the research process more efficient. Data sharing also supports transparency and reproducibility, building trust in science. Elsevier plays a key role in supporting researchers who want to store, share, discover and reuse data, and we are committed to working with other stakeholders to address challenges in making data more effective.

Although much research data is disseminated as part of journal articles, a host of other data is not made available through article publication. This policy concerns research data that often underlies, but exists outside of research articles. Publishers can help make this hidden data discoverable and our research data policy provides the framework for our support and engagement in this important area. The precise notion of what constitutes research data will differ from field to field, but, broadly speaking, it refers to the result of observations or experimentations that validate research findings, and which are not already published as part of a journal article. Research data can include, but are not limited to: raw data, processed data, software, algorithms, protocols, methods, materials.

Read more about our research data policies

Principles

The following principles underpin Elsevier’s research data policy:

  • Research data should be made available free of charge to all researchers wherever possible and with minimal reuse restrictions

  • Researchers should remain in control of how and when their research data is accessed and used, and should be recognized and valued for the investments they make in creating their research data and making it available

  • Expectations and practices around research data vary between disciplines and discipline-specific requirements need to be taken into account

  • Enabling effective reuse of research data is a shared aim and all stakeholders should work together to pursue this collectively, to find efficiencies and avoid duplication of effort

  • Platforms, publications, tools and curation services can enhance research data by improving their discoverability, use, reuse and citation

  • Where others add value and/or incur significant cost in enhancing research data to enable its reuse, these contributions need to be recognized and valued

Our policy

In line with the principles set out above we will:

  • Encourage and support researchers to share research data where appropriate and at the earliest opportunity, for example, by enhancing our submission processes to make this easier

  • Standardize and align our author data guidelines where this is possible to make it easier for authors to understand how and where they can store and share their data, enabling optimal access and reuse

  • Make it easier for researchers to comply with data management requirements, for example, by supporting data availability statements to enhance transparency

  • Develop tools and services to support researchers to discover, use and reuse data to further their research, for example, by encouraging and enabling two-way linking of relevant datasets and publications using permanent standard identifiers

  • Ensure researchers can gain credit — and credit others — for sharing research data, by encouraging and supporting proper data citation practices

  • Work closely with the scientific community to establish data review practices to ensure that published research data is valid, properly documented and can be re-used

  • Support the publication of research data as a separate, peer-reviewed output, to support reusability and provide additional ways for authors to gain credit for their work

  • Support researchers, research institutions and funders by providing the structure, workflows and technology needed to manage data effectively and make researcher and institutional workflows more efficient, for example:

    • Providing Mendeley Data as a storage and preservation option for research data

    • Integrating HiveBench into the research workflow

    • Enabling the integration of these tools with other open standards and platforms

  • Continue to participate in industry initiatives and standards and policy bodies to support more effective discovery, use and reuse of research data, for example, through our co-chairmanship of, and participation in, Research Data Alliance working groups, our engagement with the Scholix initiative, our membership of WDS and Codata, and through our partnerships with DANS, Force11 and others

FAQs

For further information regarding Elsevier’s research data policy please visit the FAQs