Complex biosphere interactions make estimating and predicting the impact of Arctic amplification difficult for Earth system modelers. Field-measured fractional cover (fcover) of Arctic vegetation species and plant functional types (PFTs) can improve vegetation composition, diversity, and biomass estimates in Earth system models. Specifically, high-resolution fcover maps can provide detailed, function-specific information that was not previously included in models. However, field campaigns that collect fcover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we harmonized fcover data from various field campaigns to create a high-quality, consistent repository schema for remote sensing-based fcover mapping applications. Specifically, we (1) developed an open-source and reproducible workflow that harmonizes fcover data derived from releve and non-releve plots in northern Alaska. The workflow produces (2) a sample database of North Slope Alaska fcover data that we used to create 20-meter resolution fcover maps of Alaska PFTs. The dataset contains fcover at both a standardized species-level and standardized PFT-level. We incorporated auxiliary information and flags for sorting and filtering plots, such as collection date, field collection method, author, citation, the purpose of field work, GPS accuracy, cover type, etc. Lastly, we (3) summarized the plot features of our North Slope database to emphasize not only how field campaigns differ greatly, but also how they can be used together to produce accurate fcover estimates at a regional scale. This work provides a data store blueprint that is user-friendly for researchers outside the field of Arctic ecology. Further, the current harmonized dataset and future iterations will be crucial for improving Arctic vegetation representation in Earth system models.