**The following guest post is by [Rob Myers](http://robmyers.org/weblog/), artist, hacker, writer, and member of the OKF Working Groups on [Open Data in the Humanities](http://wiki.okfn.org/wg/humanities) and [Cultural Heritage](http://wiki.okfn.org/wg/heritage).**
Art Open Data is Open Data that concerns art institutions, art history, the art market, or artworks. Using this data, we can examine art history and contemporary art in powerful new ways.
There are many potential sources of such data:
* Institutions produce collection catalogues, show listings, attendance figures, and organisational information.
* Writings by artists, critics, theorists and historians can be processed to provide institutional and market data, to discover factual information, or for affective and aesthetic analysis.
* Records of art auction prices have been kept for hundreds of years, with older records freely available.
* Biographical information about artists can be extracted from digitised historical sources and from modern sources such as Wikipedia.
* Institutional, historical and market data about artworks can build up a picture of its production, reception, and provenance.
* Reproductions of artworks can be analysed algorithmically or socially.
The problem, as so often, lies in accessibility. Older sources are often in formats that are not machine readable, while newer sources may have restrictive usage terms.
There are numerous ways to start dealing with these problems, such as:
* Finding existing open APIs and sources of data, and adding them to CKAN.
* Encouraging organisations to make data and APIs available openly.
* Scanning or photographing out-of-copyright text and images, and uploading the results to repositories.
* Cleaning up digitised copies of text and images, converting them to machine-readable formats and extracting information from them, and tagging or categorising them.
Once we have access to this data openly in usable formats, we’ll be able to use techniques such as statistical analysis, machine learning and social network analysis to study the workings of the art world and of the economic and critical reception of art. We’ll even be able to explore the aesthetics and iconography of artworks. Doing so won’t, of course, displace art theory, connoisseurship, or the social history of art, but rather will support them by helping us to find new evidence to suggest, support or refute their theories. If you’re interested in exploring the ways open data can expand our historical, aesthetic, and social understanding of art, check out the [OKF Cultural Heritage Working Group](http://wiki.okfn.org/wg/heritage).