Research data is the foundation on which scientific, technical and medical knowledge is built, but there are challenges in making it accessible and shareable. Elsevier is addressing these challenges by creating solutions that support researchers to store, share, discover and use data. That way, authors receive credit for their work while the wider research community benefits from discovering and using research data. See our initiatives below:
We have developed our research data policy to reinforce our commitment to working with researchers to help support them in the storing, sharing and using of research data. We continue to actively support further industry development of technical solutions, best practices and guidelines. Elsevier participates in the Research Data Alliance and Force 11 and is an associate member of ICSU World Data Systems.
Elsevier is a signatory of:
- Joint Declaration of Data Citation Principles: In 2014, Elsevier endorsed the Force 11 Citation Principals to help make research data become an integral part of the scholarly record, properly preserved and easily accessible, while ensuring that researchers get proper credit for their work.
- STM Brussels Declaration: In 2007, Elsevier and other scientific publishers have signed the STM Brussels Declaration, which supports making raw research data freely available:
Raw research data should be made freely available to all researchers. Publishers encourage the public posting of the raw data outputs of research. Sets or sub-sets of data that are submitted with a paper to a journal should wherever possible be made freely accessible to other scholars
STM text and data mining for non-commercial scientific research: In 2013, Elsevier, along with other STM publishers committed to a roadmap to enable text and data mining for non-commercial scientific research in the European Union.
Supporting readers to interact with and use research data
- Data visualization: Through our Content Innovation program, we have developed a number of in-article interactive viewers for specific data formats. With these viewers, readers can explore and interact with data while reading articles online on ScienceDirect. Some examples include:
- Text and data mining: Since 2006, we have been collaborating with universities and researchers on various text mining projects and have created some clear guidelines about how researchers can gain access to mine through our 'self-service developers' portal. Read more.
Helping readers to discover data sets associated with published research
- Enhancing discoverability: We continuously expand the number of indexing agreements with search and discovery tools such as A&I databases, library discovery services, web search engines and other innovative search and discovery tools such as Mendeley, ScienceScape and PubChase. In addition, we are improving the discoverability of content from ScienceDirect on third party platforms. For example, we have a pilot initiative that allows MyScienceWork users to read, annotate and share articles, along with any supplementary data from ScienceDirect within the MyScienceWork interface among each other.
- Data search: Elsevier has developed the DataLink platform to lower the barriers that make it difficult for genomics researchers to promote and discover data. DataLink consists of a database search engine which facilitates genomic data discovery by retrieving results from all the major public databases and articles indexed in leading archives. These include data sets from GenBank, Gene Expression Ominbus and ArrayExpress as well as articles from ScienceDirect and PubMed. Read more
- Bi-directional linking with data repositories: To ensure that relevant data can be easily found, we are collaborating with a large number of data repositories to create bidirectional links between data repositories and online articles on ScienceDirect. We support various mechanisms to set up such links, including data DOI's and relevant data accession numbers from supported databases, which automatically link in text references to data deposited in public databases.
- Data visualization and integration applications: In close collaboration with selected data repositories, Elsevier has developed a number of data integration and visualization applications that are shown next to the article on ScienceDirect. These applications build further on tagged entities or banner links to visualize data and integrate it into the online reading experience. This provides readers with deeper insights through applications such as 3D models; some examples include the Protein Viewer (with PDB), the PANGAEA data visualization tool, and the Genome Viewer (with NCBI). Read more on supported databases.
- Supporting metrics of data citation and reuse: As researchers are increasingly required to submit their data sets to repositories, it has become important to track, record and report on data submissions and reuse in other research projects. Elsevier is engaged in various initiatives to see how to support this, which includes participation in the RDA metrics group and discussions in the Snowball metrics project.
Storing and sharing data
Supporting authors who wish to deposit data
Elsevier supports the principle that research data should be made freely available to all researchers, wherever possible and inline with the needs, expectations and practices of specific research communities. Some of the ways in which we are supporting authors who wish to share their research data includes:
- Data repositories: We encourage authors to post their data sets in relevant repositories or other available channels, by establishing bidirectional links between the data and the online article on ScienceDirect. Read more.
- Supplementary data: In addition to depositing data, or in cases where there isn't a relevant data repository, Elsevier journals enable authors to store and share supplementary data with their published article. Authors retain copyright of such supplemental data and the journals are able to store, publish, archive and link to the data as a supplementary data file.
- Data journals: Data journals, and data sections in existing journals, enable authors to have their research data peer-reviewed and cited. It will also make sure readers can find, use and analyze the data hosted in external databases or submitted as supplementary data. Examples of recently launched data journals are Genomics Data and Data in Brief.
- Data citations: To ensure that authors receive the appropriate credit for deposited data, we encourage proper data citation practices, as laid out by the Joint Declaration of Data Citation Principles which Elsevier has endorsed. Read more.
- Research data policy: Within our policy we are committed to encouraging and supporting researchers to share research data where appropriate and at the earliest opportunity. We also strive to provide guidance to authors regarding the deposit and sharing of data. Read more.