ENA Source Attribute Helper: An Application Programming Interface to facilitate accurate reference to biological source data

Background: Metadata attributes of sequences that accurately reference their biological sources, as specimens or other materials of origin, and link with natural history collections, are essential to facilitate the connections between different fields in life sciences and promote reusability of data. However, metadata used to reference the biological source of sequences available within the molecular data repositories are not always well structured or comprehensive.

Methods: Within the scope of the Horizon 2020 project Biodiversity Community Integrated Knowledge Library (BiCIKL), we have developed a tool, the European Nucleotide Archive (ENA) Source Attribute Helper Application Programming Interface (API), to help users accurately report biological source-related sequence and sample attributes. This tool currently focuses on the attributes in which specimens, cultures or other materials are identified, from which the sequence data were derived, and uses curated data to obtain the unique codes for the institutions and collections holding the vouchers. The API's main functions include the presentation of metadata associated with queried institutions or collections, validation of institution and collection codes in the attribute strings  provided by the user, and the construction of an attribute string based on userentered data. The API does not however support the search of voucher specimen codes, as these need to be obtained directly from the voucher institutions. We describe the API and discuss use cases for its different endpoints. The API is available at https://www.ebi.ac.uk/ena/sah/api/.

Conclusions: We expect the API to promote and support the initial submission and any subsequent curation of biological source attributes, and hereby contribute to better links between sequence data and natural history collections, and hence on to taxonomy and biodiversity research, towards increasing the discoverability, reusability and impact of data.