Features for FAIR data
heiDATA enables the publication of research data according to the FAIR Data Principles
On this website you will learn which features and functions contribute to data publications on heiDATA being Findable, Accessible, Interoperable and Reusable. For heiDATA we use the open source software Dataverse. In the Dataverse User Guide you will find a detailed documentation of all functionalities.
Findable Data
- Citable data publication through the use of DOIs as persistent identifiers for datasets, allowing stable linking between research data and related publications.
- DOI assignment for entire datasets as well as for individual files enables exact referencing.
- Extensive metadata documentation and description of the published data.
- Published data are referenced in relevant catalogs and databases, e.g. Google Scholar, Google Dataset Search, gesisDataSearch, B2Find, Web of Science Data Citation Index.
- Data publications can be grouped into dataverses. Dataverses are collections for institutes, research groups or projects, for example.
Accessible Data
- Published files can be downloaded by interested parties both via the browser and via an API.
- “As open as possible, but as closed as necessary”: Individual files can be restricted so that they cannot be downloaded at all or only on request.
- Private URLs can be used to grant access to the datasets even before publication, for example for reviewers.
Interoperable Data
- heiDATA supports a variety of relevant metadata standards, including Data Cite, DDI (Data Documentation Initiative), Dublin Core, VOResource Schema, ISA-Tab and others.
- During the publishing process, you will receive advice on choosing appropriate file formats and, if necessary, assistance in converting them to suitable target formats.
- Files are also checked for technical validity during ingest.
Reusable Data
- The data is published under suitable open content licenses. Creative Commons licenses are recommended for data, especially CC0 and CC-BY, and special software licenses for software.
- Data records can be supplemented and modified after publication. Transparent versioning ensures the traceability of all changes.
- Provenance information in the metadata clarifies the origin of the respective datasets.
- ReadMe files can supplement the metadata with additional relevant documentation.
- Data can be integrated from heiDATA into external services. For example, published Jupyter notebooks can be run directly in Binder via the DOI.
