By discovery we mean locating and obtaining data collected by someone else, along with the relevant metadata. This works both ways – you may want to discover data yourself, to integrate it with your own data (see: Process & Maintain) and/or you may want to ensure that others can discover your data.
In order for others to find you data you need to share them. Data can be shared via open access or restricted access, or even directly between interested parties. You should consider data sharing from the outset of your project and ensure that the details of data sharing are included in your data management plan. You may be even able to include costs for data sharing in your grant application.
You will need to prepare data appropriately for sharing, for instance through de-identification. Have a third party review the data - carry out quality control before you release the data. It is crucial to ensure that a complete documentation (e.g. methodology of data collection and trial protocol) and dataset specifications (metadata) accompany the data. Deposit the data in appropriate repository (see Store & Archive and Repository Checklist).
Reusability of data. Data are not copyrightable – data licenses allow for reuse; metadata allow for pooled analysis or other community reuse. Many papers call for more “off the shelf” licenses, and increasing number of policies specify licenses for reuse. Good practice should encourage the use of community-standardised metadata, or curated platforms for clinical or surveillance data.