Wikiversity:Fellow-Programm Freies Wissen/Einreichungen/opening data science
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OPENING DATA SCIENCE: co-creating research entry points for a critical investigation of data science[Bearbeiten]Projektbeschreibung[Bearbeiten]In our digital age, it becomes crucial for researchers in the social sciences and the humanities to be able to reflect on the power of algorithms, big data, and information platforms; being it in relation to social media data breaches, algorithmic recommendation schemes, or predictive policing regimes. But how to gain access and better understanding of such digital phenomena, processes, artifacts, social worlds? Building on my PhD project investigating the making and use of algorithmic prediction in climate impact research (scenarios of sea level rise, drought, migration, etc.) I would like to share, discuss and further develop strategies and methodologies for research access in ‘digital research’ – here referring to the research subjects (e.g. algorithms, developers, start-ups, supercomputers), but also to the methods used to investigate them (e.g. quantitative social media analysis, but also analogue methods such as participant observation). The proposed project within the Wikipedia fellow-programme aims at triggering a debate challenging notions of “openness” and “access” in the era of algorithms, big data, and information infrastructures. It strives for the operationalization of inventive methods (Lury and Wakeford 2014; Marres et al. 2018) identifying research access points, fostering data literacy and opportunities for data critique (Gray et al 2018; boyd and Crawford 2012; Giessmann and Burkhardt 2014) within the social sciences, the humanities and beyond. Concretely, this involves the organization of informal meetups (a co-lab, see Niewöhner 2015) for scientists investigating ‘the digital’, setting up a collaboration infrastructure for the group enabling debate across time and space, and publishing insights of the process within a digital website and/or publication.
boyd, danah, and Kate Crawford. “Critical questions for big data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information, Communication & Society 15, no. 5 (June 2012): 662–79. Giessmann, Sebastian, and Marcus Burkhardt. 2014. “Was Ist Datenkritik? Zur Einführung.” Mediale Kontrolle Unter Beobachtung 3 (1). Gray, Jonathan, Carolin Gerlitz, and Liliana Bounegru. “Data Infrastructure Literacy.” Big Data & Society 5, no. 2 (July 2018). Lury, Celia, and Nina Wakeford. 2014. Inventive Methods: The Happening of the Social. Oxon, UK: Routledge. Marres, Noortje, Michael Guggenheim, and Alex Wilkie. Inventing the Social. S.l.: Mattering Press, 2018. Niewöhner, Jörg. “Epigenetics: Localizing Biology through Co-Laboration.” New Genetics and Society 34, no. 2 (April 3, 2015): 219–42. Zwischenbericht[Bearbeiten]Der Zwischenbericht kann eingesehen werden über Wikiversity:Fellow-Programm_Freies_Wissen/Einreichungen/opening_data_science/Zwischenbericht. Abschlussbericht[Bearbeiten]Der Abschlussbericht kann eingesehen werden über Wikiversity:Fellow-Programm_Freies_Wissen/Einreichungen/opening_data_science/Abschlussbericht. Autor/in[Bearbeiten]
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