International research data networks are critical for progress in many scientific domains and underpin efforts to promote Open Science. At the same time, many of these networks are fragile and the responsibilities for their support and performance are frequently distributed across a variety of different actors. This working group explores the challenges and enablers for the effective functioning of international research data networks. It analyses the diversity and complexity of these networks, and issues such as governance and funding, in a selection of 32 cases. The published report includes a set of policy recommendations as a basis for building the shared understanding that is necessary to develop effective and sustainable international research data networks.
In the empirical sciences, data has traditionally been an integral part of scholarly publishing. However, rapid technical developments—such as digital data and high-throughput techniques—changed the scholarly publishing paradigm dramatically in the last decades, which requires new approaches to ensure availability and usability of science data. Existing approaches to address this issue are mostly technically dominated and lack success because they do not supply the necessary benefit for data producers, the wider community, and society. The concept of Data Publication is undergoing a renaissance as part of scholarly communication and on the base of new and proven technologies. Publishing data is a new and strong incentive for scientist to share their data and has positive effects on the data quality. The impact on citation rates can be seen in recent bibliometric studies on science articles providing access to underlying data.
There is a clear indication that data policies, best practices, information systems, and domain techniques are now beginning to emerge for citizen science, crowdsourcing, and VGI projects to support more inclusive and collaborative scientific works. However, whilst some communities are already developing citizen science protocols in their subdomains, these are often highly domain specific. It may be almost impossible to derive generic rules, but by considered how to transition from generally noisy raw data collected by citizens to data of scientific value that can be stewarded by a trusted data service, a set of guidelines—or at least advice—can be generated to provide useful inputs in the early development stages to ensure there is a clean data stream from the original raw data to those archived long term, as well as advocating good practices. These issues are sociological as well as technical, and such general assessment is highly appropriate under CODATA’s leadership with WDS contributing the technical aspects.