When thinking about arts, one might think about beauty, feelings and emotion. When thinking about data, one might not think about those things at all. Data Science is by nature a very technical kind of discipline and much of the work we do might be seen as manipulating cold, generic, insensitive data. However, these processes can also happen within more creative endeavours, as well as in the understanding of the way art is created and perceived, and in the way it affects our society.
A great example of this particular aspect, understanding how art affects us, is the “Listening Experience Database” (LED) project. As the title implies, this project (now in its second round of funding from AHRC) is about creating a database of “listening experiences”, i.e. records of somebody listening to music. There are many elements to an experience, including the source where the record was found, any information we might have about the listener and about the music they were listening to. Constructing this database relies on a crowdsourcing process, supported by a platform that manages the lifecycle of contributions to the database using linked data technologies. Beyond the mechanisms used to construct it however, the fascinating thing about LED is the value of the data resource it creates: Thousands of listening experiences telling us what different people thought about the different types of music they were listening to, in different places, different times, different contexts… In other words, this kind of endeavours are not actually about building the database – it is only the first step towards the kind of work we are now doing with researchers in music history, using natural language processing, sentiment analysis, clustering and pattern extraction to understand what affects people’s perception of music, and what it affects.
LED is one prominent example of the way we collect data about art: Many other projects are looking at supporting research in various artistic disciplines, in the Data Science Group and elsewhere. But data can also be the base material in support for an artistic process. Last month for example, the Milton Keynes International Festival featured an installation from artists Wesley Goatley and Georgina Voss called “Ground Resistance” (see image above). The idea of this installation was to show how a city (Milton Keynes) looks through the data it generates, and to reflect on the concept, ideas and potential pitfalls of the increasing move towards “Smart Cities”. This relied on data from the MK:Smart project, through the MK Data Hub, to create a visual and sonic experience for residents of Milton Keynes to be able perceive the usually invisible aspects of the city’s infrastructure (including the energy and water distribution networks). As a sustainable element of this initiative, the Ground Resistance website enables exploring more of these data, and the divide that exists in terms of data provision for different areas of the city.
Of course, these might be seen as exceptions, as Data Science is generally more concerned with areas such as eGovernement, finance or industry. However, these initiatives and many others show that there is a lot of value in exploring further what can come from looking at art through data, and at data through art.