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There is an urgent need to improve integrity of large industrial infrastructure. Sharing data can support better understanding of accidents such as recent mining dam collapses, making them less likely to occur, and contributing to sustainability.
The number of chemical compounds and associated experimental data in public databases is growing, but presently there is no simple way to access these data in a quick and synoptic manner. Instead, data are fragmented across different resources and interested parties need to invest invaluable time and effort to navigate these systems.
The past two decades have seen a revolution in digital imaging techniques for capturing gross morphology, offering an unprecedented volume of data for biological research. Despite the rapid increase in scientific publications incorporating those images, the underlying datasets remain largely inaccessible. As the technical barriers to data sharing continue to fall, we face a more intimate, and perhaps more complicated, obstacle to open data – the one in our minds.
Starting last month, publications at Scientific Data now include data citations in the main reference list, rather than in a separate data citations section. This change will be supported by changes to the underlying structure of our content to promote machine readability and reuse of links between scholarly articles and datasets. This aligns the journal with a roadmap for data citation co-developed by representatives of the academic community and several publishers, which seeks to make data citation a standard part of the scholarly publishing process.
The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to the new field of computational social science.
Metadata, data about data, are an essential component of any data sharing system. They power discovery and bind together related datasets. They provide essential context, describing, for example, who generated a dataset and how. The papers in this collection explore and critically analyze issues related to the quality and FAIRness of metadata in public resources. Collectively, these works highlight obstacles, both technical and behavioural, that affect metadata quality, and propose possible solutions. They also shine a light on the important, but often underappreciated, role of data curators and research data managers.