We are interdisciplinary group of researchers who focus on data practices to inquire into how data become part of the working processes and research methods, and how they are material in curation of digital objects and archives, creation of artistic work, experimental design, software development, in legal practices and beyond.
Magdalena Tyżlik-Carver is Associate Professor of Digital Communication and Culture in the Dept. of Digital Design and Information Studies at the School of Communication and Culture at Aarhus University. She is also curator and researcher whose research interest is in posthuman curating and computational culture, critical data studies, affective data and data fictions. Her current research focuses on developing speculative and participatory methods for data practices beyond BigTech extractivism and expansive infrastructural politics. She is an educator who engages trans*feminist values in her teaching on Critical Data Studies program at Aarhus University. Her recent curatorial projects include Fermenting Data (2021) and Screenshots: Desire and Automated Image (2019).
Daniela Agostinho is assistant professor at the Department of Digital Design & Information Studies, University of Aarhus. She works across visual and digital culture, artistic and curatorial research, with a focus on arts & social justice. She is interested in the role of digital and data practices in social justice movements and everyday practices of freedom, sovereignty and liberation. She is co-editor of the books Uncertain Archives: Critical Keywords for Big Data (MIT Press, 2021) and (W)archives: Archival Imaginaries, War and Contemporary Art (Sternberg Press, 2020). At Aarhus University, she is co-founder of the research unit “Postcolonial Entanglements”. She currently co-leads the network “Reparative Encounters: a transcontinental network for artistic research and reparative practices” with colleagues from Denmark, the US Virgin Islands, Ghana and Kalaallit Nunaat/Greenland (Nordic Culture Fund 2023-2024).
Midas Nouwens is an action researcher focused on digital rights and regulation. He studies the digital harms of pervasive software systems to society and how to increase our democratic control over such software through regulatory intervention, participatory design, and collective action. In general, this means technically deconstructing complex systems to understand how they work, gathering empirical data about how those systems affect people’s behaviours and perceptions, and building new software as interventions, data collection tools, and critical alternatives.
Dr Jussi Parikka is Professor in Digital Aesthetics and Culture at Aarhus University in Denmark. He is also visiting professor of at Winchester School of Art (University of Southampton) and at FAMU at the Academy of Performing Arts in Prague. In 2021 he was elected as member of Academia Europaea. His published books include Insect Media (2010), Digital Contagions (2007/2016) and A Geology of Media (2015), and A Slow, Contemporary Violence (2016). Recently, he co-edited Photography Off the Scale (2021) and is the co-author of The Lab Book: Situated Practices in Media Studies (2022). His book Operational Images is forthcoming in Spring 2023. Parikka’s books have been translated into 11 languages including Japanese, Korean, Chinese, Czech, Italian, French, Spanish and Portuguese. Http://jussiparikka.net.
Pablo Velasco is Associate Professor at the department of Digital Design & Information Studies at the University of Aarhus, where he also co-direct sthe Center for the Study of Technological, Emerging, and Ethical Methods (STEEM), and the Center for Science, Technology and Society Studies (STS) during 2020. He is also affiliated to the Humans and Information Technology research programme (HIT) and the Digital Aesthetics Research Center (DARC). His research critically explores digital culture through its technical infrastructures and practices. Working with Digital Methods for Social Research, he is currently interested in the political and ontological implications of the progressively pervasive use of automated computational techniques, e.g. procedural generation and unsupervised machine learning methods.
