Datafying Media Art. Assessing Digital Methods for Media Art Research

Abstract

Where the initial wave of Digital Humanities (DH) concentrated mainly on textual analysis, the contemporary DH witnessed a visual turn. This resulted not only in establishing visuals as subject of digital analysis but also a focus on graphical methods of knowledge production, the development of transferrable tools and collaborative knowledge generation (see Burdick, Drucker, Lunenfeld, Presner, & Schnapp, 2012, p. SG 2). At the same time the trend of datafication paired with data analysis is often equaled with the promise of a deeper understanding of complex and dynamic realities (see Schäfer & Es, 2017, p. 13).

Using the Archive of Digital Art (ADA) as prime example, this paper will assess digital methodologies for MediaArtResearch that are capable of taking into account the high complexity of MediaArt, e.g. its nature as (interactive) processes as well as the realms of experience made possible by rule-based systems and technological configurations. Working on mediations of MediaArt projects the analysis of these documentations needs to reach “beyond their surface”.

The multifaceted methodology of digital archiving is a central point of investigation. On the one hand an open Web 2.0 archive serves as basis for further digital analysis as it collaboratively builds up a large corpus of comparable data and metadata about media art projects that can be enhanced by a community with multiple perspectives. On the other hand the methodology of modeling as knowledge generation process promotes specific understandings of the nature of MediaArt projects. Going beyond this base-methodology the paper will show possibilities of further mixed-method analysis that can be performed on ADA-metadata, enabling new questions and insights towards the complex field of MediaArt.