There is increasing interest by many different actors and organisations in ‘open data publishing’ and what this actually entails. Scholarly publishers, alongside repositories, bibliometrics experts, infrastructure providers, libraries and others, have an important role to play in contributing to and supporting the infrastructure for research data publishing so that the data underlying publications can be discovered, ‘validated’, cited and reused by others. Collaborating and moving forward together is key and, as this article sets out, kickstarting adoption is more important than achieving perfection in getting publishers started:

　　“The unique properties of data as a citable object have attracted much needed attention, although it has also created an unhelpful perception that data citation is a challenge and requires uniquely burdensome processes to implement. This perception of difficulty begins with defining a ‘citation’ for data. The reality is that all citations are relationships between scholarly objects. A ‘data citation’ can be as simple as a journal article or other dataset declaring that a dataset was important to the creation of that work. This is not a unique challenge.”

　　Data Citation: Let’s Choose Adoption Over Perfection

　　Lowenberg, Daniella, Lammey, Rachael, Jones, Matthew B, Chodacki, John, & Fenner, Martin

　　(2021, April 19)

　　The past decade saw an emphasis on supporting data availability statements at journals, but as the Open Research/Science agenda has evolved (not least because of the fundamental links between sharing data, scientific innovation and evidence-informed policy making during the COVID pandemic), it has become clear that there needs to be more robust ways for journals to support data publishing. A key part of this is the widespread adoption by publishers of implementing best practices for data citations. Standardised – and community agreed – practices resulting in machine-readable ways to show which articles cite which data and vice-versa helps build an open, sustainable source of this information for the community to use.

　　As leaders in the evolving open access publishing space, OASPA believes that developing and supporting best practices and broadly achievable standards for all aspects of open content is essential, including for research data. Because of this, OASPA endorses the Make Data Count initiative, and its goals of building for, and supporting, the inclusion of research data in responsible research assessment.

　　(from:https://oaspa.org/oaspa-endorses-make-data-count-join-our-webinar-to-find-out-more/)