GLARE: global lake atlas in research

Lakes are vital landscape units with ecological, economic, and social importance, and there has been a surge in scientific research aimed at understanding and addressing the challenges to ensure the preservation and sustainable management of lakes. However, there is limited knowledge regarding the geographical distribution of the studied lakes, the specific issues and driving factors in the research. There is still a need for comprehensive datasets that combine lake morphology and watershed characteristics with research topics. In this dataset, we assembled metadata from 58,024 peer-reviewed publications on 2,542 lakes and geometric, meteorological, and socioeconomic attributes from multisource databases, including HydroATLAS, NOAA PSL, GCP, and HILDA+. These datasets were aggregated into the Global Lake Atlas in REsearch (GLARE) by parsing the literature documents, extracting the lake entities based on deep learning, geocoding the lakes, and allocating 17 topics and 54 subtopics. The open-source GLARE dataset is essential for addressing global lake challenges and strengthening research in underrepresented regions by linking literature information with physical and biogeochemical data. Furthermore, the methodology applied in GLARE can be employed to extract any unstructured data, making it highly applicable to various other academic fields.