Herder, EelcoRoßner, DanielAtzenbeck, ClausHansen, ChristianNürnberger, AndreasPreim, Bernhard2020-08-182020-08-182020https://dl.gi.de/handle/20.500.12116/33511User behavior and the resulting behavioral data forms the basis of personalized feeds, recommendations and advertisements in social networks such as Facebook. These platforms are now required to provide users with their personal data. However, these dumps with chronological data in different files do not provide users insight in overarching themes and connections in their online behavior. In this paper, we discuss the development and preliminary evaluation of an exploratory interface for visual data exploration. First insights include that the less obvious, more associative and obscure connections are more interesting and relevant to the user than very close semantic or temporal connections.enspatial hypertextsocial networksuser profilesGDPRdata explorationtransparencyText/Workshop Paper10.18420/muc2020-ws111-343