This dataset includes melt pond fraction (MPF) over Arctic sea ice during 2000-2019. The spatial coverage of this data is north of 60 °N. The MPF data is projected on a polar stereographic grid with a spatial resolution of 12.5 km and a temporal resolution of 8-day intervals from May 9 to September 6, which is archived in the NetCDF format. This dataset was jointly developed by the Beijing Normal University, University at Albany-State University of New York, and Sun Yat-sen University. Large-scale temporal and spatial distribution of melt ponds over Arctic sea ice have implications for surface albedo, heat and mass balance of sea ice, freshwater in the upper ocean, and primary productivity of ice algae and phytoplankton. We retrieved the MPF data based on a robust ensemble-based deep neural network along with the surface reflectance of 7 bands from MOD09A1 (MODIS surface reflectance 8-Day L3 version 6) as the input and the MPF observations from multiple sources as the target. The validation results show that the retrieved MPF is in good agreement with the in-situ measurements (the details can be found at Ding et al., 2020).