In digital, networked culture, we spend our lives engaged with data systems. Although our experience is shaped by interfaces, friendly surfaces, we are inevitably aware of their functional undersides. The web is increasingly a set of interfaces to datasets. In 2004, Alan Liu observed the page-based paradigm of the web being interrupted by database incursions — what he called ‘data pours’ (Liu, 2004). On the contemporary web the data pour has become the rule, rather than the exception. The so-called ‘web 2.0’ paradigm further abstracts web content into feeds, real-time flows of XML data.
In the background of these developments — what Liu characterises as the post-industrial rationalisation of networked culture — is data itself. In this context it is not surprising that new media art has in recent years turned towards data as both subject and material. In 2001, exhibitions such as the Whitney Museum’s ‘Bitstreams’ and ‘Data Dynamics’, and the San Francisco Museum of Modern Art’s ‘010101’, signalled the emergence of data practice as a key element in new media art.
Data art has also attracted some theoretical attention since it came to prominence. Lev Manovich’s 2002 essay ‘The Anti-Sublime Ideal in Data Art’ (Manovich, 2002) has largely set the theoretical agenda, especially in its focus on issues of scale and the sublime (or not) aesthetics of this practice (Jevbratt, 2004). Others have deployed theoretical frameworks from conceptual art (Sack) and postmodern theory (Simanowski, 2005a). While informed by these approaches, this paper considers a more basic question.
Data art involves a creative grappling with the nature of our now ubiquitous data systems. It draws data out, makes it explicit, literally provides it with an image. It also probes data’s constitution, potential, and significance. In the process of working pragmatically with data — using it as a generative resource, a way of making — data art is involved in the culturally crucial figuration of data and its contemporary domain. This practice is a concrete exploration of what data is, does, and can do, but it also involves a set of assumptions, narratives and ontologies that construct data as an entity in the cultural imagination.
Coming to grips with the figure of data is made more difficult by a basic ambiguity in the way the term is used; particularly in relation to art, ‘Information’ and ‘data’ are often used interchangeably. Warren Sack’s paper on ‘Aesthetics of Information Visualisation’ also uses the phrase ‘data visualisation’ (Sack); Simanowski (2005a) uses ‘data’ in general, but interposes ‘information’ without explanation; Manovich’s (2002) analysis of ‘data art’ occurs in the context of a wider project on ‘info-aesthetics’.
This blurring of data and information obscures a fundamental distinction — and in turn, a fundamental relation — between the two terms. As Wikipedia’s entry on information states: ‘Information is the result of processing, manipulating and organizing data in a way that adds to the knowledge of the person receiving it’. A recent text on data mining describes that task as ‘discovering useful information in large data repositories’ (Tan et al, 2006: 2). Some data artists recognise the same distinction: Mark Hansen and Ben Rubin, creators of the installation ‘The Listening Post’ (2003), describe their sonification work as ‘exploring the information hidden in data’ (Hansen and Rubin, 2001). This distinction draws on a sense of information as related to context and meaning; following Donald MacKay (1969) and Gregory Bateson, information here is a ‘difference that makes a difference’ (Bateson, 1973: 428) rather than the structural, mathematical formulation of Claude Shannon’s information theory (Shannon and Weaver, 1949).
Prising these terms apart, we can begin with a notion of data from empirical science, as a set of measurements extracted from the flux of the real. In themselves, such measurements are abstract, blank, meaningless. Only when organised and contextualised by an observer does this data yield information, a message or meaning. The concepts are converse, two sides of the same thing: data is the raw material of information, its substrate; information is the meaning derived from data in a particular context. In deploying data, artworks inevitably involve its flip-side, information. Often, data art actively resists, or defers, information; it aims to somehow present us with the data ‘itself’. The implications of that drive, and its manifestations in these artworks, offer a useful critical perspective on data art practice.
Excerpted and reprinted from FCJ-067: http://eleven.fibreculturejournal.org/fcj-067-art-against-information-case-studies-in-data-practice/
Mitchell Whitelaw is an academic, writer and artist with interests in new media art and culture, especially generative systems and data-aesthetics. His work has appeared in journals including Leonardo, Digital Creativity, Fibreculture, and Senses and Society. In 2004 his work on a-life art was published in the book Metacreation: Art and Artificial Life (MIT Press, 2004). His current work spans generative art and design, digital materiality, and data visualisation. He is currently an Associate Professor in the Faculty of Arts and Design at the University of Canberra, where he leads the Master of Digital Design. He blogs at The Teeming Void.
Bateson, G. Steps to an Ecology of Mind (St. Albans: Paladin, 1973).
Hansen, M and Ben Rubin. ‘Babble Online: Applying Statistics and Design to Sonify the Internet’, Proceedings of the 2001 International Conference on Auditory Display, http://www.acoustics.hut.fi/icad2001/proceedings/papers/hansen.pdf
Jevbratt, L. ‘The Prospect of the Sublime in Data Visualizations’, Ylem Journal 24.8 (July/August 2004).
Liu, A. ‘Transcendental Data: Toward a Cultural History and Aesthetics of the New Encoded Discourse’, Critical Inquiry 31.1 (Fall 2004), http://criticalinquiry.uchicago.edu/issues/current/31n1.liu.htm
MacKay, D. Information, Mechanism and Meaning (Cambridge MA: MIT Press, 1969).
Manovich, L. ‘The Anti-Sublime Ideal in Data Art’ (2002) http://www.manovich.net/DOCS/data_art.doc
Sack, W. ‘The Aesthetics of Information Visualisation’ http://hybrid.ucsc.edu/socialComputingLab/Publications/wsack-infoaesthetics-illustrated.doc
also (2010) ‘Aesthetics of Information Visualization’ in Context Providers: Conditions of Meaning in Media Arts; Margot Lovejoy, Christiane Paul and Victoria Vesna (eds). New York; Intellect Ltd.
Shannon, C., and W. Weaver. The Mathematical Theory of Communication (Urbana: University of Illinois Press, 1949).
Simanowski, R. “Mapping Art as Cultural Form in Postmodern Times”, http://www.brown.edu/Courses/GM/GM144-2005/52-lecture-mappingart.doc.
Tan, P., Michael Steinbach and Vipin Kumar. Introduction to Data-Mining (Boston: Pearson Education, 2006).
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