Within the project WEA-Acceptance¹, extensive measurement campaigns were carried out, which included the recording of acoustic, meteorological and turbine-specific data. Acoustic quantities were measured at several distances to the wind turbine and under various atmospheric and turbine conditions. In the project WEA-Acceptance-Data², the acquired measurement data will be stored in a structured and anonymized form and will be provided for research purposes. In addition to the data, first evaluations as well as reference data sets for chosen scenarios will be published for the validation and verification of simulation models. In the course of a contribution at the Wind Energy Science Conference3, a specification 1.1 for the data platform and a first anonymized data set is published. Among others, the specification contains the concept of the data platform, which is primarily based on the FAIR (Findable, Accessible, Interoperable, and Reusable) principle. The data set contains meteorological and acoustic data recorded over one month. The data were corrected, conditioned and anonymized. Accordingly, relevant outliers are marked and erroneous data are removed in the data set. The acoustic data initially includes anonymized sound pressure levels and one-third octave spectra. Anonymized time signals and the utilized scripts will be published in later versions. The approach for data anonymization is briefly described in the ReadMe file. In the near future, the wind turbine data will be added to the data set. For further information about the measurements, it is referred to "Martens, S., Bohne, T., and Rolfes, R.: An evaluation method for extensive wind turbine sound measurement data and its application, Proceedings of Meetings on Acoustics, Acoustical Society of America, 41, 040001, https://doi.org/10.1121/2.0001326, 2020. ¹The project WEA-Acceptance (FKZ 0324134A) was funded by the German Federal Ministry for Economic Affairs and Energy (BMWi). ²The project WEA-Acceptance-Data (FKZ 03EE3062) was funded by the German Federal Ministry for Economic Affairs and Energy (BMWi). ³Schössow, D., Preihs, S., Peissig, J.: WEA-Acceptance Data: a FAIR wind turbine dataset, presentation at Wind Energy Science Conference 2023, 23-26. May 2023, Glasgow, United Kingdom