Forward The dynamic nature of water science data—in which approaches to observation, modelling, and prediction of Earth systems are continuously evolving—shape our present data and re-shape our legacy data through a cycle of repeated reanalysis with improved or emerging technologies (e.g., UAVs with new sensors, new models, adoption of machine learning /artificial intelligence). Such repeated interactions with well-managed data—past and present—leads to improved data, new discoveries, and a sustainable process of iterative refinement of knowledge and research questions. This process inevitably results in future data which will become tomorrow’s important legacy. Global Water Futures Observatories (GWFO) is thus steadfastly committed to the long-term stewardship of its open data and, to this end, has devised a new template-based form of data catalogue, GWFNet, capable of incorporating legacy data and future data of a to-be-determined form as readily as it handles data from the present day. GWFNet's ultimate purpose and vision is to enable a variety of information seekers—from the general public to highly specialized scientists—to easily zero in on trails of information and obtain publications, datasets, real-time data sources, and other related information that delivers context to the results associated with their searches (including basins, observatories, research sites, stations, model inventories, software, equipment, principal investigators, programme/project associations, and more).

https://gwfnet.net/fileserver/T-2025-05-23-s1JTDjoVaq0ChRInCLHs3WGQ/LessonsLearnedFromEightFeaturesOfGWFNet.pdf