Can massive computing power and artificial intelligence crack the code of deep history of places? This is a fundamental question of a project discussed in an article on “The ‘time machine’ reconstructing ancient Venice’s social networks”. Frédéric Kaplan plans to “…scan documents including maps, monographs, manuscripts and sheet music. It promises not only to open up reams of hidden history to scholars, but also to enable the researchers to search and cross-reference the information, thanks to advances in machine-learning technologies.”

The Venice Time Machine can link citizens and businesses with historic maps of Venice, such as this sixteenth-century view of the city. Credit: EPFL/Archivio di Stato

The goal is to crunch enough data to outline the connections that emerged in historical societies including “social networks, trade, and knowledge”.  While of interest to historians, it could also inform economists and epidemiologists, as well as other disciplines.  Much like Rome, Venice, mentioned as “The Serene Republic“, is a good for this endeavor due to the wealth of knowledge and its organization, aided by its protected lagoons and it’s desire for documentation.

“As Venice’s empire grew, it developed administrative systems that recorded vast amounts of information: who lived where, the details of every boat that entered or left the harbour, every alteration made to buildings or canals.”

While there was been study over the years, much of the archive “…predominantly written in Latin or the Venetian dialect, has never been read by modern historians. Now it will all be systematically fed into the Venice Time Machine, along with more unconventional sources of data, such as paintings and travellers’ logs.”

Kaplan’s interest has been to employ AI for lingustics, so the concept of using machine learning to study patterns in language is fundamental to the work, along with digitization of many thousands of pages of documents, building on work already done by the Italian Ministry of Cultural Heritage.

There’s a lot more about the linguistic ‘hacking’ of documents, as illustrated below, but the concept also involved diving into the archival cartography.   “In 2006, a huge, purpose-built scanner began to digitize the archive’s precious store of more than 3,000 maps of Italian towns, including many commissioned by Napoleon. These ‘cadastral’ maps delineate property boundaries and record the ownership of small parcels of land; some of the documents are as large as 4 metres by 7 metres.”

The result is the ability to create some amazing detail with overlay of multiple sources:

“One cadastral map of Venice that he commissioned in 1808 has provided a backbone of reliable data, allowing historians to add geographical context to a 1740 census that lists citizens who owned and rented property in the city. By combining this with 3D information about buildings from paintings such as those of Canaletto, the time-machine team has produced an animated tour through Venice, showing which businesses were active in each building at the time.”

A video on YouTube outlines the ambitions of the project.  From their summary:  “The State archives of Venice contain records stretching back over a thousand years. The vast collection of maps, images and other documents provide an incredibly detailed look into Venetian history. This could be used to create a kind of virtual time machine for historians and the public to explore the city.”

What implications does this have for hidden hydrology?  To me, the overwhelming task of both digitizing information and determining patterns is something that is daunting for a team of professionals, much less individuals looking to glean discoveries from their local place.  The sheer effort and technology in digitization and analysis could be employed to discover key linkages and patterns that may illuminate historical hydrology, topography, and other clues.  An example mentioned in the article highlights the concept, using animations to look at spatio-temporal change , in fact “One is a dynamic video of the development of the Rialto from AD 950 onwards, using diverse sources of information at different time points. The simulation shows how the buildings — and the iconic Rialto Bridge — sprung up among the salt marshes, along with the area’s periodic destruction by fires and subsequent reconstructions.”

The possibilities with large data sets is intriguing, and the article mentions cross-disciplinary opportunities, as well as larger connections to other ‘time machines’ in cities, such as a new effort in Amsterdam and possibilities in Paris.  It adds a dimension of big data as a potential avenue for exploration, yet is tempered by age-old techniques and cautions of the next shiny object.

“The unbridled ambitions of the time-machine project are a concern for some researchers, not least because many of its core technologies are still being developed. “The vision of extending digital representation into different time slots is absolutely, self-evidently right — but it might be better to develop things more in a lot of different, small projects,” says Jürgen Renn, a digital-humanities pioneer and a director at the Max Planck Institute for the History of Science.  Nevertheless, Daston suspects that the time machine heralds a new era of historical study. “We historians were baptized with the dust of archives,” she says. “The future may be different.”

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