Frederic Kaplan
Professor
Digital Humanities Lab (DHLAB), EPF Lausanne
Switzerland

Biography
Prof Frederic Kaplan holds the Digital Humanities Chair at Ecole Polytechnique Federale de Lausanne (EPFL) and directs the EPFL Digital Humanities Lab. He conducts research projects combining archive digitisation, information modelling and museographic design. He is currently working on the "Venice Time Machine", an international project in collaboration with the Ca'Foscari University in Venice, aiming to model the evolution and history of Venice over a 1000 year period. Frederic Kaplan graduated as an engineer of the Ecole Nationale Superieure des Telecommunications in Paris and received a PhD degree in Artificial Intelligence from the University Paris VI. Before coming to Switzerland, he worked ten years as a researcher at Sony Computer Science Laboratory and six years at CRAFT, the EPFL pedagogical research laboratory. He published more than a hundred scientific papers, 6 books and about 10 patents.

Abstract
How to Build a Historical Time Machine ?

The Venice Time Machine, an international scientific programme launched by the EPFL and the University Ca’Foscari of Venice aims at building a multidimensional model of Venice and its evolution covering a period of more than 1000 years. Venice was Europe's economic hub for centuries, a door to the Orient and dominated the seas. The digitalization of hundreds of kilometers of Venetian archives, itself a daunting task already underway, creates challenges for data management, image and character recognition. But the central scientific challenge of this big data project is to qualify, quantify and represent uncertainty at each step of this digitisation and modelling process. In the context of this research programme, I'll discuss the new role of algorithms for recreating maps and networks of the pasts, pinpointing the importance of an ethics of representation and of the systematic documentation of meta-historical information (information about the intellectual processes underlying the data produced). I'll also argue about the relevance of linking closely research with educational programmes preparing a new generation of young scholars to work with "big data of the past”.