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Gaia Mosconi, M.A.

gaia_mosconi
gaia.mosconi(at)uni-siegen.de

Room: US-D 105

Phone: +49 271 740-2293

Vita

Gaia Mosconi is research associate and doctoral student at the University of Siegen within the group on CSCW and Social Media (Prof. Dr. Volkmar Pipek). She received a I level Master in Sociology and a II level Master in “Smart Community Design and Management” at the University of Trento. She applies sociological research methods (mainly Qualitative Research, Action-Research) to the study and development of Information Systems. Her research interests range from civic engagement to research collaboration and data infrastructures.

Since November 2016, she is a member of the CRC1187 “Media of Cooperation” (https://www.mediacoop.uni-siegen.de/en/about-sfb-1187/) where she works in the project INF “Infrastructural Concepts for Research on Cooperative Media” (https://www.mediacoop.uni-siegen.de/en/projects/inf/). In INF, Gaia investigates how collaborative research data practices and infrastructures are changing under the auspices of the Open Science agenda. Moreover, she is the main organizer of the “Research Tech Lab”, a seminar format where PhD students explore, discuss (even design) research approaches, methods and tools. She is also involved in the conceptual development of “Research-hub” (https://research-hub.social/), a platform for research collaboration and sharing. Finally, since September 2019 she is also a member of the Locating Media Graduate School (http://www.locatingmedia.uni-siegen.de/gaia-mosconi/).


Publications

2019

Gaia Mosconi, Qinyu Li, Dave Randall, Helena Karasti, Peter Tolmie, Jana Barutzky, Matthias Korn, Volkmar Pipek (2019) Three Gaps in Opening Science, Computer Supported Cooperative Work (CSCW) 28(3), p. 749-789, url, doi:10.1007/s10606-019-09354-z

2017

Gaia Mosconi, Matthias Korn, Christian Reuter, Peter Tolmie, Maurizio Teli, Volkmar Pipek (2017) From Facebook to the Neighbourhood: Infrastructuring of Hybrid Community Engagement, Computer Supported Cooperative Work: The Journal of Collaborative Computing (JCSCW) 26(4-6), p. 959-1003, url, doi:10.1007/s10606-017-9291-z