A Collaborative Platform for Data-Science-Driven Art History

adapted from a work of Dustin Gaffke, licensed under CC BY 2.0

Bridging the gap between Humanities and Science

The fields of humanities and sciences are commonly seen as fundamentally distinct and incompatible, both as of their discourses and as of their methods. This unconciliatory position often hinders interdisciplinary collaboration and novel approaches. ARTizen strives to bridge this gap.

ARTizen is a data-science-driven collaborative research platform for art history of the long 19th century, based on data gathered by the gaming platform ARTigo, which has to this date produced over 7 million semantic tag annotations for 60.000 thousand artworks.

Citizen Science

In the last century, science has been traditionally carried out by trained professionals with the general public mostly excluded from substantial contributions. "Citizen Science", as coined by Rick Bonney and Alan Irwin, seeks to overcome this separation by involving volunteers actively into the scientific process. While most citizen science projects today harness volunteers in the early stages of research for data collection and classification, they generally concede little influence on the direction of the research to the volunteers and leave analysis and interpretation of the obtained data exclusively to professional scientists.

In contrast, ARTizen tries to transfer the spirit of citizen science already present in the data-gathering by ARTigo to the analysis and interpretation of the generated data. Based on the quantitative analysis of data relevant for art history, the ARTizen platform gives anyone the possibility to collaboratively analyze and interpret the data, share and discuss their findings with others and publish them to the general public. Volunteers can participate in all steps of the scientific process.

Data Science

Even though results of data science are increasingly used to influence every aspect of today's life, (generating product recommendation in online shopping, determining a person's chances to receive a loan, or even providing and edge in elections) a broad understanding for these methods in the public is exceedingly rare beyond the fields of computer science and statistics. For the minority of students who have the chance to take data science classes, these courses often focus on theoretical aspects of algorithms and tends to neglect the practical applications.

ARTizen strives to familiarise a broad audience with the power of data science. It provides both groups, the interested layperson and the computer scientists looking for practical applications, easy access to data science tools without requiring programming skills. Instead, ARTizen provides a set of easy-to-use data analysis tools.