The Venice Time Machine project aims to digitize and structure information from 80 km of documents in the State Archives of Venice to create a searchable digital archive. This will be accomplished through 1) digitizing all documents, 2) using semi-automatic transcription of handwritten texts, and 3) creating a structured database with data mining. As a proof of concept, the project aims to find all records regarding Battista Nani by structuring the information into categories of people, places, institutions, and objects linked to dates. The end goal is to reconstruct histories of Venice through archived documents and create 3D visualizations.

1. The Venice Time Machine
A new way of navigating in the past
Frédéric Kaplan Dorit Raines
Ecole Polytecnique Fédérale de Lausanne Università Ca’ Foscari Venice

2. Battista Nani (1616-1678), Venetian ambassador, writer, historiographer

3. Birth act of Battista
Nani in the Venetian
State Archives

9. The Frari convent – today’s State Archives of Venice

10. The ambition of The Venice Time Machine project is to transform
this huge archive into a digital information system.

11. How can one find all records
regarding Battista Nani in
80 km. of documents?

12. The Venice Time Machine project
aims to address this question by
structuring the information
contained in the records

13. 1. Digitization of all documents
2. Semi-automatic transcription
of handwritten documents
3. Data mining and structured
data base
* We are currently in the experimental phase

14. Digitization of documents

15. Virtual X-ray reading
“Reading” manuscripts using x-ray tomography.
A single tomographic set could indeed yield the same information
of traditional digitization process with minimized interaction with
the document, drastically reducing the risk of damage and speeding
up the process.

16. The X-ray imaging of the writings is made possible by the use, for
many centuries and all over Europe, of iron-based inks generically
denominated “iron gall”.
There is a direct correlation between the ink iron content and the
quality of x-ray attenuation-contrast images: a fundamental issue of
the studies is the chemistry of the inks.

18. Semi-automatic Transcription of
Handwritten Documents
The framework based on machine-vision and machine-learning
techniques is comprised of the following steps:

19. 1. Pre-processing algorithms used to enhance the readability of the
textual content
Optimal binarization

20. 2. The pre-filtered images go through a classification process with the purpose of classifying
the document contents in graphical and textual elements and layout structure

21. 3. The textual content is finally processed using a semi-automatic transcription tool in order
incrementally construct a digital version of the documents

23. Data mining and structured data base
Each archival series will need its own structure (reduced to minimum to match others)
BUT
On a metacontent level ONLY 4 categories are important:
Persons
Places
Institutions
Objects
+ date
The search will be done using the above 4 categories (metacontent), with sub divisions:
METACONTENT: Painting 16th century; GRANULAR LEVEL: Titian; woman
METACONTENT: Pietro Basadonna 1675; GRANULAR LEVEL: Capuchin order;
mansionary
Each source creates the link between dates and facts

24. Let’s turn back to Battista Nani

32. But we can do better still – we can create 3D representations of Venice and
link documents to each palace in order to tell its history and the urbanistic
changes throughout the ages

33. The Rialto bridge area - 1500

34. A 3D rendering of the Rialto bridge area

37. And many more projects to come!
Garzoni. Aprenticeship,
labor and society, by
Valentina Sapienza

38. The Venice Time Machine Project
Our website: dhvenice.eu
Partner Institutions
Archivio di Stato di Venezia, direttore Raffaele Santoro
École Polytechnique Fédérale de Lausanne (EPFL), president Patrick Aebischer
Università Ca’ Foscari di Venezia, rettore Michele Bugliesi
With the support of
Fondation Lombard Odier
Director
Frédéric Kaplan, École Polytechnique Fédérale de Lausanne (EPFL)
Project Management
Giovanni Colavizza, École Polytechnique Fédérale de Lausanne (EPFL)
Isabella di Lenardo, École Polytechnique Fédérale de Lausanne (EPFL)
Katerina Kunz, École Polytechnique Fédérale de Lausanne (EPFL)
Andrea Mazzei, École Polytechnique Fédérale de Lausanne (EPFL)
Giovanni Caniato, Archivio di Stato di Venezia
Simon Levis Sullam, Università Ca’ Foscari di Venezia
Dorit Raines, Università Ca’ Foscari di Venezia
Partner projects
“Garzoni project”, coordinator Valentina Sapienza, Université de Lille
“Visualizing Venice”, Steering Committee: Caroline Bruzelius, Donatella Calabi, Andrea Giordano, Mark Olson, Andrea
Rinaldo, Victoria Szabo, Guido Zucconi.
Technical support
4DigitalBooks, Ivo Iossiger, scanner provider, Ecublens, Switzerland
Bread and Butter, digital media, Lausanne, Switzerland
AMstudio, 3D modelling, Venezia, Italy
Olivo Bondesan, foto-riproduzione, Archivio di Stato di Venezia
Thank you!