Future archive: visualising the flow of IP use in UGC Platforms

Can data visualisation methods be leveraged to identify patterns of intellectual property (IP) use in Google‘s user generated content (UGC) platform, YouTube? This paper explores the potential limits of such tools as YouTube Analytics, Content ID and the use of WC3 meta-tag data as a means to track the boundaries of copyright use within platforms such as YouTube. The paper draws on David McCandless‘ (2012, 2014) use of data visualisation tools to explore visual narratives and meaningful behavioural patterns arising out of big data from the online information archive. It outlines how such techniques could be used to identify patterns of content rights use within the YouTube archive. The method has potential as a route towards rewarding content owners in the free exchange culture of the YouTube archive (see Lanier, 2012; Lessig, 2008, Anderson, 2009). A digital ethnography of meaningful data patterns of IP and creative commons use will show users and stakeholders how they might track: ownership; sharing; and, the flow of co-created content. Such a method is proposed to help: empower users to make intelligent decisions about ownership and attribution; help UGC creators receive rewards beyond that of cultural capital (Lanier, 2012); allow those who benefit from the use of YouTube content to identify and reward its creators; and, address problems of legal uncertainty about rights management in UGC environments (see 'Review of EU Copyright Rules' (European Commission, 2014).