When the dust settles on the 21st century, and all of the GIFs have finished animating, the most important cultural artifacts left from the digital age may very well be databases.
How will the societies of the future read these colossal stores of information?
Consider the eBay databases, which contain information for every transaction that happens and has happened on the world’s biggest marketplace. $2,094 worth of goods are sold on eBay every second. The records kept about this buying and selling go far beyond dollars and cents. Time, location and identity come together with text and images to leave a record that documents both individual events, as well as collective trends across history and geography.
This summer, Mark Hansen and I created an artwork, installed at the eBay headquarters in San Jose, which investigates this idea of the eBay database as a cultural artifact. Working in cooperation with eBay, Inc., and the ZERO1 Biennial, the piece was installed outside of the eBay headquarters and ran dusk to midnight from September 11th to October 12th.
As a conceptual foundation for the piece, we chose a much more traditional creative form than the database: the novel. Each movement begins with a selection of text. The first one every day was a stage direction from the beginning of Death of a Salesman which reads:
A melody is heard, played upon a flute. It is small and fine, telling of grass and trees and the horizon. The curtain rises.
Before us is the Salesman’s house. We are aware of towering, angular shapes behind it, surrounding it on all sides. Only the blue light of the sky falls upon the house and forestage; the surrounding area shows an angry glow of orange. As more light appears, we see a solid vault of apartment houses around the small, fragile-seeming home. An air of the dream dings to the place, a dream rising out of reality. The kitchen at center seems actual enough, for there is a kitchen table with three chairs, and a refrigerator. But no other fixtures are seen. At the back of the kitchen there is a draped entrance, which leads to the living room. To the right of the kitchen, on a level raised two feet, is a bedroom furnished only with a brass bedstead and a straight chair. On a shelf over the bed a silver athletic trophy stands. A window opens onto the apartment house at the side.
From this text, we begin by extracting items1 that might be bought on eBay:
Flute, grass, trees, curtain, table, chairs, refrigerator. This list serves now as a kind of inventory, each explored in a small set of data sketches which examine distribution: Where are these objects being sold right now? How much are they being sold for? What does the aggregate of all of the refrigerators sold in the USA look like?
From this map of objects for sale, the program selects one at random to act as a seed. For example, a refrigerator being sold for $695 in Milford, New Hampshire, will switch the focus of the piece to this town of fifteen thousand on the Souhegan river. The residents of Milford have sold many things on eBay over the years – but what about books? Using historical data, we investigate the flow of books into the town, both sold and bought by residents.
Finally, the program selects a book from this list2 and re-starts the cycle, this time with a new extracted passage, new objects, new locations, and new stories. Over the course of an evening, about a hundred cycles are completed, visualizing thousands of current and historic exchanges of objects.
Ultimately, the size of a database like eBay’s makes a complete, close reading impossible – at least for humans. Rather than an exhaustive tour of the data, then, our piece can be thought of as a distant reading3, a kind of a fly-over of this rich data landscape. It is an aerial view of the cultural artifact that is eBay.
A motion sample of three movements from the piece can be seen in this video.
Before Us is the Salesman’s House was projected on a 30′ x 20′ semi-transparent screen, suspended in the entry way to the main building (I’m afraid lighting conditions were far from ideal for photography). It was built using Processing 2.0, MongoDB & Python. Special thanks to Jaime Austin, Phoram Meta, Jagdish Rishayur, David Szlasa and Sean Riley.
- Items are extracted through a combination of a text-analysis algorithm and, where needed, processing by helpful folks on Mechanical Turk. ↩
- All text used comes from Project Gutenberg, a database of more than 40,000 free eBooks ↩
- For more about distant reading, read this essay by Franco Moretti, or, for a summary, this article from the NYTimes ↩