AISIT Database of Pan-Arctic stable oxygen isotope (delta18O) and barium measurements from seawater, freshwater, rivers, fjords, and precipitation north of 60 degrees North, 1967-2025

This database is a curated compilation of stable oxygen isotope (delta18O) and barium measurements from seawater, freshwater, rivers, fjords, and precipitation, covering the pan-Arctic region (here defined as north of 60 degrees North). Data were assembled from 99 published and archived source datasets spanning the Arctic Ocean, Beaufort Sea, Bering Sea, Chukchi Sea, Davis Strait, Barents Sea, Laptev Sea, Kara Sea, East Siberian Sea, Greenland Sea, Svalbard, Greenland fjords, and major Arctic rivers (Yenisey, Lena, Ob, Mackenzie, Yukon, Kolyma). Measurements were collected between December 1967 and August 2025, totalling 45,737 data points, of which 6504 are freshwater samples and 5,286 are land-based .

Each record includes the delta18O value, the measurement standard used (predominantly the Vienna Standard Mean Ocean Water (VSMOW)), and associated ancillary data including geographic coordinates, sampling depth, temperature, and salinity where available. 5531 out of these delta18O records contain total barium measurements. All source datasets have been harmonised to a common schema and subjected to quality assurance and quality control (QA/QC) processes, with World Ocean Circulation Experiment (WOCE) flags applied where present in the original data. The database was constructed as part of the Artificial Intelligence for Stable Isotope Tracers (AISIT) programme, funded by the Natural Environment Research Council (NERC) and the Engineering and Physical Sciences Research Council (EPSRC), to provide an Artificial Intelligence (AI) ready, Findable Accessible Interoperable and Reusable (FAIR) compliant resource for the study of Arctic freshwater sources, hydrological processes, and climate change. The database is designed to support reproducible scientific analysis, isotope-salinity relationships, and machine learning applications.

The AISIT project was funded by NERC and EPSRC with the grant no. NEB2678.