Sound, reproducible scholarship rests upon a foundation of robust, accessible data. For this to be so in practice as well as theory, data must be accorded due importance in the practice of scholarship and in the enduring scholarly record. In other words, data should be considered legitimate, citable products of research. Data citation, like the citation of other evidence and sources, is good research practice and is part of the scholarly ecosystem supporting data reuse. In support of this assertion, and to encourage good practice, we offer a set of guiding principles for data within scholarly literature, another dataset, or any other research object.

This document identifies gaps in existing PID infrastructures, with a focus on ORCID and DataCite Metadata and links between contributors, organizations and artefacts. What prevents us from establishing interoperability and overcoming barriers between PID platforms for contributors, artefacts and organisations, and research solutions for federated attribution, claiming, publishing and direct data access? It goes on to propose strategies to overcome these gaps.