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Abstract
The advent of the internet and personal computers as tools of communication and creation radically transformed the world we live in over the past 40 years. The impacts of both technologies across various fields and topics have been well documented, including on the art world. However, discussion in the latter field is often focused on how the internet and computers have transformed art creation or the ways in which memory institutions function and interact with their audiences. Seemingly slightly less focus has been given to how these technologies may have impacted which artists get to be included in art collections. Net Art Revolution? aims to look at this particular aspect of the digital revolution by analyzing data from two different NYC-based institutions that represent the art world before and after the internet and personal computers came into our lives: MoMA, representing the traditional art world; and Rhizome, a smaller and younger institution dedicated to digital-born art and culture, often referred to as net art. Both institutions make data about their collections publicly available -- MoMA in csv and json formats, Rhizome as Linked Open Data -- thus allowing us to peer into their potential differences and what they might mean, with the caveat that both institutions are located in one of the primary art and media centers of the Global North and thus represent a distinctive perspective on art (regardless of type. Despite the potential limitations of the datasets, we believe they are a useful starting point from which to investigate our research question: Did the internet and personal computers have an impact on the make up of art collections?
Credits
This project was undertaken by Margherita Donelli, Chiara Catizone, and Laurent Fintoni for the Electronic Publishing and Digital Storytelling (a.y. 2021-2022) final examination, as part of the Digital Humanities and Digital Knowledge Master's Degree at the University of Bologna.
All duties - data preparation, cleaning, integration, visualization, research, web dev, design, and storytelling - were shared by all. The notebook details more specific breakdown of work.
The project was built primarily using Python for data manipulation, Plotly for data viz, and Miro for storytelling, and brain power for remembering/learning all the different presets and controls in each library 🤣.
Data
Robot, Open Data. (2021). MoMA Collection - Automatic Monthly Update [Data set]. Zenodo.
Rhizome's dataset (AKA the ArtBase), accessed primarily via their SPARQL endpoint. We would like to acknowledge and thank Dragan Espenschied, Preservation Director at Rhizome, for his willingness to answer some of our questions about the formatting of Rhizome's data and supplying us with a copy of the RDF dump.
License
MoMA's dataset is released under a CCO License.
Rhizome's data is available in Linked Open Data format.
Manipulated data is released under the original licenses.
Project website and all related material uploaded to the GitHub repository are released under a CC-BY-4.0 License.