The use and capability of uncrewed maritime systems (UMS) for collecting data has exponentially increased across the spectrum of maritime applications. Ranging from high resolution imagery above and below the surface to oceanographic and atmospheric data, UMS have been widely adopted across federal, academia, and industry. These data are often used to augment data collected by more traditional means such as ships, or satellites. However, much of the focus is on the improvement of sensor resolutions and extending platform/payload endurance and not on how to handle the magnitude of data coming ashore.
The lack of clearly defined and widely adopted guidelines for metadata and data formats have resulted in a piecemeal approach to data management across the UMS community. This has compounded the challenges inherent in managing UMS-collected data. The absence of harmonized data practices has led to datasets that are less interoperable and less reusable, and often lack transparent data traceability.
We are showcasing an effort to build a Community of Practice across government, academia, and industry aimed at developing data management practices for UMS. Unifying frameworks of metadata and data management practices within and across UMS communities, will enable increased discovery, interoperability, and reusability of these data in more traditional scientific analyses as well as in emerging methods reliant on artificial intelligence and cloud computing.
