OpenSTAC: an open spatiotemporal catalog to make Earth Observation research data findable and accessible

Abstract

In line with Open Science practices and FAIR principles, researchers are publishing their Earth Observation (EO) related research data at public research data repositories, such as Zenodo and Figshare. Files that are in raster grid data formats such as GeoTIFF, NetCDF, and HDF, as well as supplementary vector data, are common in these research datasets. Although such data files include detailed spatiotemporal information, which is very useful to find data for specific regions and time periods, unfortunately this information is currently not effectively utilized by the research data repositories and the researchers are asked to enter spatial and temporal information manually as part of the dataset metadata, which is usually limited to a textual description or simple metadata attributes. Moreover, the repositories also do not provide effective tools and interfaces to search research data by location, e.g. by specifying a geographical extent. Therefore, EO-related research data largely becomes "invisible" to the researchers and can only be found if some keywords match textual location description. This highly limits the findability and accessibility of research data with spatiotemporal characteristics. On the other hand, there are many initiatives that aim to facilitate access to EO data by using modern tools and technologies. One such initiative is the SpatioTemporal Asset Catalog (STAC), which is an emerging open standard designed to enhance access to geospatial data, especially on the Cloud. STAC provides a unified framework for organizing and describing geospatial assets, making it easier for users to discover, access, and work with EO data. It enables data providers to create catalogs of geospatial assets, each with detailed metadata, including spatial and temporal information, formats, and links to data files. This standardized structure improves data discoverability and interoperability across various software tools and platforms, streamlining the process of finding and accessing geospatial data. OpenSTAC leverages the capabilities of the STAC ecosystem and aims to create an open spatiotemporal catalog of public research datasets published at major research data repositories. For this purpose, geospatial data files available in research datasets are analyzed, and spatiotemporal information embedded in these files are extracted. This information is used to create a global STAC catalog, OpenSTAC, which enables the researchers to easily find and access EO research data by using a wide range of open-source tools provided by the STAC ecosystem, including visual data browsers, command line tools, and data access libraries in various languages, e.g. Python, R, and Julia . Hence, it significantly improves the FAIRness of EO research data. This talk provides a detailed information about the methodology developed to monitor the research data repositories to identify published geospatial datasets, to collect spatiotemporal metadata of datasets by using existing metadata and by analysing and extracting additional information from the geospatial data files, and to update a STAC-based spatiotemporal catalog of the datasets by using the collected information. The methodology's implementation through open-source software will be presented, providing insights into its functionality and practical applications. Additionally, a live demonstration of the operational OpenSTAC platform will showcase its features, capabilities, and real-world applicability, highlighting its role in facilitating seamless integration and execution of the methodology.