Beyond data: Sharing related research outputs to make data reusable

Key points Data sharing is a crucial part of open science, because it enables reproducibility and reusability and thereby accelerates scientific discovery. To make data FAIR, associated resources and outputs need to be made available as well, in order to provide context. Data management plans, instruments, samples, and software are examples of associated resources with strong community support. PIDs and their metadata can be used to identify and connect all these relevant resources. Giving researchers access to not just the data, but also connected resources with assigned PIDs and metadata enables them to fully replicate, understand, and reuse previously acquired data.

Automated summary

Data sharing is crucial for open science as it promotes replicability and reusability of scientific discoveries. Providing context through associated resources and outputs is essential for achieving FAIR data. Examples of such resources include data management plans, instruments, samples, and software, which receive strong community support. Using PIDs and metadata helps identify and connect relevant resources, giving researchers access to not only the data but also the connected resources for complete replication, understanding, and reuse of previously acquired data.