$\mathrm{U}\times \mathrm{S}$ Data Interoperability: Establishing Foundational Guidelines for Metadata and Standardization

Uncrewed systems (
$\mathrm{U}\times \mathrm{S}$
) use and capability has increased exponentially across the entire maritime domain. As the maritime domain has embraced these new technologies, much of the focus has been on development of higher resolution sensors and longer mission endurance. Many of these missions are augmenting traditional data collection methods, adding volume to already robust datasets. This has led to challenges in managing the data collected by
$\mathrm{U}\times \mathrm{S}$
since there have not been any widely adopted guidelines with regards to metadata and other specifications unlike other geospatial data. This lack of guidelines and standards in the
$\mathrm{U}\times \mathrm{S}$
community has contributed to the lack of FAIR (findable, accessible, interoperable, and reusable) data; that is less interoperability and reusability between agencies, limited discoverability of data by users, as well as limited traceability of data lineage. A multi-agency project led by the Naval Meteorological and Oceanography Command (NMOC) and the National Oceanic and Atmospheric Administration (NOAA) chartered under the Commercial Engagement through Ocean Technology (CENOTE) Act of 2018 has led to the development of data and metadata guidelines for
$\mathrm{U}\times \mathrm{S}$
[1]. This effort establishes foundational guidance on data standardization and metadata for uncrewed systems data. In order to further interoperability, discovery, and accessibility of UxS data (thus aligning with FAIR principles), these guidelines draw from both the ISO (International Organization for Standardization) and the IHO (International Hydrographic Organization) and establish the necessary parameters to ensure the metadata records are compliant and interoperable with domestic and international partners. The authors applied modular components to develop a logical data model that forms the basis of the guidelines. This design of the logical data model can be modified easily and rapidly to incorporate new platforms and sensors as both
$\mathrm{U}\times \mathrm{S}$
technology and data evolves. The intent of the guidelines is to encompass end-to-end data management, capturing both the acquisition information at the time of data collection and information about the processing of that data as itis curated to an archival repository or data portal. The acquisition data guidelines include Sensor Metadata and Vehicle (platform) Metadata components, geographical information about the operation or mission, and information about the agency performing it. The acquisition data guideline also includes engineering and physical aspects of platforms and sensors that will be leveraged to improve platform efficiency and sensor configurations in the future. The sensor and platform metadata are based on OGC compliant sensorML XML specifications that document payload configuration, calibration, and data collection parameters. These components make up the Core Metadata of the data model that will remain with the data throughout its lifecycle. As
$\mathrm{U}\times \mathrm{S}$
data is processed and developed into products, the
$\mathrm{U}\times \mathrm{S}$
data curation guidelines specify required parameters for the Curated Metadata record. The curated metadata record documents the level of processing done to create the data product, file naming conventions, and incorporates the Core Metadata from the data acquisition stage. Both the acquisition and curation metadata include information security markings (ISM) portions for security classification, handling, and dissemination. These guidelines have been instrumental in the development of data pipelines that automate ingest and initial processing of
$\mathrm{U}\times \mathrm{S}$
collected data to create XML metadata files, viewable KMZ footprints, and conversion into non-proprietary (netCDF) formats.