# Journals ## expand\_more Publishing your authors’ research data on Dataverse repositories increases your journal’s impact: - Preserve data and make it citable, following best practices that improve “the robustness and reproducibility of science” ([Cousijn et al., 2017](https://doi.org/10.1101/097196); [Fenner et al., 2016](https://doi.org/10.1101/100784)) - Help authors meet funders’ data sharing mandates - Increase the credit authors receive for the reuse of their data. ([Data Citation Synthesis Group, 2014](https://www.force11.org/group/joint-declaration-data-citation-principles-final)) This guide recommends four ways journals can use Dataverse repositories. It applies to data repositories that help journals publish and archive their authors' data, including: - [Harvard Dataverse Repository](https://dataverse.harvard.edu/) - [Borealis: The Canadian Dataverse Repositiory](https://borealisdata.ca) - [UNC Dataverse Repository](https://dataverse.unc.edu/) [See our map of data repositories using the Dataverse Project software](/). Please review each repository's website for more information about who can publish data, fees and storage limits. **Have questions or need help using The Dataverse Project?** [Contact the Dataverse Project team or schedule a training](/contact). Our support team can lead trainings for you and your team virtually and in person. ### Use a Dataverse repository for publishing your authors’ data and making it citable We recommend **four ways** that journals can use Dataverse repositories to ensure that authors make data available and get credit for their research, with links to and from associated published articles. Please note that the Dataverse Project is a data sharing platform. If your journal is seeking an indexing service for distributing research articles, we recommend the Social Science Sharing Network. Dataverse repositories may reserve the right to remove files and Dataverse collections that do not contain research data. Embed /**/ @media (max-width: 573px) { .desktop-visible { display: none; } } /**/ ### **1. Set up a Journal Dataverse Collection** Within a Dataverse repository, your journal can create and customize its own space, making it easier to review, publish and track metrics for your authors' data. You can use this space to incorporate data publishing into common article publishing workflows: - When an article is accepted for publication, authors can be instructed to submit their data to your journal's customized space, called a Dataverse collection. - Once an author submits a dataset, the Dataverse repository sends a journal editor an email notification to review and publish the dataset . You can also embed your Dataverse Collection on your journal's website, so visitors can search for and download datasets related to published articles without leaving the site. For examples of how other journals are using their own Dataverse Collections to publish data, visit [Palgrave Communications](https://dataverse.harvard.edu/dataverse/palcomms), [Political Analysis](https://dataverse.harvard.edu/dataverse/pan), and [Quarterly Journal of Economics](https://dataverse.harvard.edu/dataverse/qje) on the Harvard Dataverse Repository, and [State Politics & Policy Quarterly](https://dataverse.unc.edu/dataverse/sppq) on the UNC Dataverse Repository. Open all sections Close all sections ### How to set up your Journal's Dataverse Collection expand\_more - Create an account (see [Create Account](http://guides.dataverse.org/en/latest/user/account.html)) or login to an existing account. If multiple journal staff members will be working in the journal's Dataverse collection, we recommend that each member uses an account under their own name so that it's easier to tell who makes changes to each dataset version. - Review [Terms of Service](/best-practices/harvard-dataverse-general-terms-use) - The Dataverse Project is a data sharing platform. If your journal is seeking a service to index research articles, we recommend the [Social Science Sharing Network](https://www.ssrn.com/en/). Some Dataverse repositories reserve the right to remove files and Dataverse collections that do not contain research data. - Sharing of sensitive research data (such as data with personally identifiable information) is not yet supported, but will be available with the planned [DataTags](http://datatags.org/) integration. - Create and customize your Dataverse collection using the options in the Edit dropdown menu (see [Dataverse Management](http://guides.dataverse.org/en/latest/user/dataverse-management.html) and [Dataset + File Management](http://guides.dataverse.org/en/latest/user/dataset-management.html)), including: - [General Information](http://guides.dataverse.org/en/latest/user/dataverse-management.html#general-information): Describe your Dataverse collection, specify how your authors will need to describe the research data they are depositing (e.g. which metadata), and how visitors can search for data in your Dataverse collection (e.g. which facets). We recommend choosing the Journal Metadata field and any additional discipline-specific metadata fields. - [Permissions](http://guides.dataverse.org/en/latest/user/dataverse-management.html#permissions): Use these options to control who is able to submit data to your Dataverse collection and whether or not your editors will have to approve submitted data before it is published on your Dataverse collection. - **More “Edit” options**: Consider configuring your Dataverse collection using the remaining "Edit" options, which can help streamline the process of reviewing and uploading data, and can improve discoverability: - Using [themes and widgets](http://guides.dataverse.org/en/latest/user/dataverse-management.html#theme), you can customize the look of your Dataverse collection and display it on your journals' website, so readers can access your authors’ data without leaving your journal’s website - [Private URLs](http://guides.dataverse.org/en/latest/user/dataset-management.html#private-url-to-review-unpublished-dataset) streamline the review process by making it easy for others to access unpublished datasets without creating a Dataverse repository account - [Dataset metadata templates](http://guides.dataverse.org/en/latest/user/dataverse-management.html#dataset-templates) are useful for creating multiple datasets with the same metadata - Revise editor and reviewer training material and author instructions for uploading and citing data - Pre-submission guidelines from "A Data Citation Roadmap for Scientific Publishers" ([Cousijn et al., 2017](https://doi.org/10.1101/100784)) - [Template for instructions to authors](https://docs.google.com/document/d/1mxdz0yMx3_598r5W_FW4Bjse4dpbeYtu8USTi4_qbEU/edit) ### **2. Set up a Journal Dataverse Collection with data curation & verification** Journals interested in ensuring that datasets associated with their articles are replicable can set up a Dataverse collection. A third party curates and verifies the reproducibility of datasets that authors deposit. This service is currently offered by the [UNC Odum Institute](http://odum.unc.edu/archive/managementcuration/). Journals using their services include the [American Journal of Political Science](https://dataverse.harvard.edu/dataverse/ajps), which is hosted on the Harvard Dataverse Repository, and [State Politics & Policy Quarterly](http://arc.irss.unc.edu/dvn/dv/sppq), hosted on the [UNC Dataverse Repository](https://dataverse.unc.edu). Contact the Odum Archive () for more information. ### **3. Integrate your journal's manuscript submission system with a Dataverse Repository** With a Dataverse repository integration, your authors can submit their manuscripts and research data at the same time, from the same platform, automatically creating persistent, bi-directional links between articles and their underlying data. - For journals that have data associated with their articles, any journal using the most common versions of [Open Journal Systems (OJS)](https://pkp.sfu.ca/ojs/) can use OJS's [Dataverse Plugin](https://projects.iq.harvard.edu/ojs-dvn/book/project-documentation) to upload data to a Dataverse repository through the OJS platform. - For all other publishers and journal publishing systems interested in letting allows submit data through their systems, please contact us at about using [Dataverse's SWORD API](http://guides.dataverse.org/en/latest/api/sword.html). ### **4. Recommend a Dataverse Repository to Authors** Include a Dataverse repository on your journal website as a recommended data repository for authors to deposit data and receive a formal scholarly data citation to include with their published article. See our [map of known Dataverse repositories](/), including the [Harvard Dataverse Repository](https://dataverse.harvard.edu), which researchers and journals from all disciplines can use to publish data. Examples of journals and publishers recommending the Harvard Dataverse Repository for authors to deposit data include [PLOS](http://journals.plos.org/plosone/s/data-availability), [American Heart Association Publications](https://professional.heart.org/professional/ResearchPrograms/UCM_461443_AHA-Approved-Data-Repositories.jsp), [Elsevier](https://www.elsevier.com/books-and-journals/content-innovation/data-base-linking/supported-data-repositories) and [Nature Scientific Data](http://www.nature.com/sdata/data-policies/repositories). ### Contact the Dataverse Project Team **Have questions or need help using the Dataverse Project?** [Contact the Dataverse Project team or schedule a training](/contact). Our support team can lead trainings for you and your team virtually and in person.