A first step towards identifying and closing data gaps is to take stock of data that already exists. For this dataset, we collected LGBTIQ+ data in European social science archives. We researched all data archives of CESSDA ERIC, the Consortium of European Social Science Data Archives, and found 66 LGBTIQ+ datasets in 9 of the 34 member and partner archives. Besides basic information to identify the datasets and their locations, we recorded temporal and spatial coverage, LGBTIQ+ identities sampled, access category, and keywords. In a separate dataset we take a closer look at the datasets’ keywords. We recorded information about language and whether a given keyword is related to LGBITQ+ identities. To describe the topics covered in the studies, the keywords were mapped to the CESSDA Topic Classification. A sentiment analysis with SentiStrength classifies whether a keyword has negative or positive/neutral sentiment. Additional keywords ( https://thesauri.cessda.eu/elsst-4/en/ ): gender identity, genderqueer, LGBTQI+, non-binary persons, queer persons, transgender persons, sexual orientation, homosexuality, bisexuality, intersex persons

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