AbstractCommunity-developed minimum information checklists are designed to drive the rich and consistent reporting of metadata, underpinning the reproducibility and reuse of the data. These reporting guidelines, however, are usually in the form of narratives intended for human consumption. Modular and reusable machine-readable versions are also needed. Firstly, to provide the necessary quantitative and verifiable measures of the degree to which the metadata descriptors meet these community requirements, a requirement of the FAIR Principles. Secondly, to encourage the creation of standards-driven templates for metadata authoring, especially when describing complex experiments that require multiple reporting guidelines to be used in combination or extended. We present new functionalities to support the creation and improvements of machine-readable models. We apply the approach to an exemplar set of reporting guidelines in Life Science and discuss the challenges. Our work, targeted to developers of standards and those familiar with standards, promotes the concept of compositional metadata elements and encourages the creation of community-standards which are modular and interoperable from the onset.

DataCite have released the Data Citation Corpus, together with a dashboard that summarises the corpus. This is billed as: The goal is to build a citation database between scholarly articles and data, such as datasets in repositories, sequences in GenBank, protein structures in PDB, etc. Access to the corpus can be obtained by submitting a form, then having a (very pleasant) conversation with DataCite about the nature of the corpus.