[This post is joint with Mika Braginsky, a long-time collaborator on data-sharing and data-viz.]
Data sharing is both a critical scientific need and, increasingly, a mandate by many research funders. The FAIR principles – that data should be findable, accessible, interoperable, and reusable – are a critical guide to how data are shared. Yet even FAIR-compliant datasets in approved repositories are often shared in ad-hoc formats that are hard to reuse or to integrate with other data. In contrast, the most impactful datasets tend to be disseminated thoughtfully through dataset-specific or community-specific platforms. These “domain-specific data repositories” (this was our term from a previous blogpost!) create opportunities for creating data standards and ontologies that fit the needs of a particular community, research problem, or instrument type. They also allow opportunities for engagement through interactive visualizations. But custom repositories and pretty websites with nice visualizations are costly and complicated to create.
We are introducing a set of open-source tools and templates for easily creating datapages, interactive websites to disseminate data for broad reuse. Datapages are easy to deploy for a single project, but extensible enough to host large collections of related datasets. You can learn more and get started at https://datapages.github.io/.
