{"references": ["Schneider, Stefanie; Kristen, Maximilian; Vollmer, Ricarda (2023): Re: ARTigo. Neuentwurf eines Social-Tagging-Frameworks aus funktionalen Programmbausteinen. In: DHd 2023. Open Humanities, Open Culture. Konferenzabstracts, 173\u2013178.", "Bry, Fran\u00e7ois; Schefels, Clemens; Schemainda, Corina (2018): Eine qualitative Analyse der ARTigo-Annotationen. In: Kuroczy\u0144ski, Piotr; Bell, Peter; Dieckmann, Lisa (Eds.): Computing Art Reader. Einf\u00fchrung in die digitale Kunstgeschichte, Heidelberg, 97\u2013114.", "Schneider, Stefanie; Kohle, Hubertus (2017): The Computer as Filter Machine. A Clustering Approach to Categorize Artworks Based on a Social Tagging Network. In: Artl@s 6.3: 81\u201389.", "Wieser, Christoph; Bry, Fran\u00e7ois; B\u00e9rard, Alexandre; Lagrange, Richard (2013): ARTigo. Building an Artwork Search Engine With Games and Higher-Order Latent Semantic Analysis. In: Proceedings of Disco 2013, Workshop on Human Computation and Machine Learning in Games at HComp, Palm Springs, CA, USA."]}

ARTigo (https://www.artigo.org/) is a Citizen Science project that has been jointly developed at the Institute for Art History and the Institute for Informatics at Ludwig Maximilian University of Munich since 2010. It enables participants to engage in the tagging of artworks, thus fostering knowledge accumulation and democratizing access to a traditionally elitist field. ARTigo is built as an interactive web application that offers Games With a Purpose: in them, players are presented with an image – and then challenged to communicate with one another using visual or textual annotations within a given time. Through this playful approach, the project aims to inspire greater appreciation for art and draw new audiences to museums and archives. It streamlines the discoverability of art-historical images, while promoting inclusivity, effective communication, and collaborative research practices.