Unleashing Big Data Of The Past – Europe Builds A Time Machine

March 1, 2019

The European Commission has chosen Time Machine as one of the six proposals retained for preparing large scale research initiatives to be strategically developed in the next decade.

€1 million in funding has been granted for preparing the detailed roadmaps of this initiative that aims at extracting and utilising the Big Data of the past. Time Machine foresees to design and implement advanced new digitisation and Artificial Intelligence (AI) technologies to mine Europe’s vast cultural heritage, providing fair and free access to information that will support future scientific and technological developments in Europe.

One of the most advanced Artificial Intelligence systems ever built

The Time Machine will create advanced AI technologies to make sense of vast amounts of information from complex historical data sets. This will enable the transformation of fragmented data – with content ranging from medieval manuscripts and historical objects to smartphone and satellite images – into useable knowledge for industry. In essence, a large-scale computing and digitisation infrastructure will map Europe’s entire social, cultural and geographical evolution. Considering the unprecedented scale and complexity of the data, The Time Machine’s AI even has the potential to create a strong competitive advantage for Europe in the global AI race.

“Time Machine is likely to become one of the most advanced Artificial Intelligence systems ever built, trained on data from wider geographical and temporal horizons”, explains Frederic Kaplan, Professor of Digital Humanities at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and Coordinator of the Time Machine Project.

Cultural Heritage as a valuable economic asset

Cultural Heritage is one of our most precious assets, and the Time Machine’s ten-year research and innovation program will strive to show that rather than being a cost, cultural heritage investment will actually be an important economic driver across industries. This constant source of new knowledge will be an economic motor, giving rise to new professions, services and products in areas such as education, creative industries, policy making, smart tourism, smart cities and environmental modelling. For example, services for comparing territorial configurations across space and time will become an essential tool in developing modern land use policy or city planning. Likewise, the tourism industry will be transformed by professionals capable of creating and managing newly possible experiences at the intersection of the digital and physical world. These industries will have a pan-European platform for knowledge exchange which will add a new dimension to their strategic planning and innovation capabilities.

A new age for Social Sciences and Humanities

Time Machine will mark a new age for Social Sciences and Humanities, as it will offer open access to Europe’s past via unified data and new AI services. This will give “super powers” to researchers by revolutionising the individual researcher’s search capabilities, drastically raising the overall scale and scope of social sciences and humanities research. The resulting knowledge will enable the field to effectively contribute to the development of strategic answers to major pan-European challenges such as sustainable growth, social welfare, migration and integration of migrants, and the safeguarding of European democracy.

Transforming education

Education is a crucial factor for the social and economic well-being in Europe and the world, and Time Machine will help transform it by creating a dynamic new industry for the production of educative digital material based on aligned massive datasets. The resulting online courses, materials, simulations and other experiences will promote active engagement with our combined cultural heritage and make continuous learning more accessible and inclusive.

A unique alliance and a network of cities

Time Machine promotes a unique alliance of leading European academic and research organisations, Cultural Heritage institutions and private enterprises that are fully aware of the huge potential of digitisation and the very promising new paths for science, technology and innovation that can be opened through the information system that will be developed, based on the Big Data of the Past. In addition to the 33 core institutions that will be funded by the European Commission, more than 200 organisations from 33 countries are participating to the initiatives, including seven national libraries (Austria, Belgium, France, Israel, Netherlands, Spain, Switzerland), 19 state archives (Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Germany, Hungary,Lithuania, Malta, Norway, Poland, Romania, Slovenia, Spain, Slovakia, Sweden, and Switzerland), famous museums (Louvre, Rijkmuseum), 95 academic and research institutions, 30 European companies and 18 governmental bodies.

Time Machine is also a growing network of cities. The project is based on a “franchise” operation model grouping scholars, cultural heritage organisations, government bodies and large groups of volunteers around specific integrated projects focusing on cities. The engagement of a large number of volunteers, often local citizens, in these Local Time Machine initiatives is another key element to ensure their long-term sustainability of the project. Local Time Machines are currently being developed in Venice, Amsterdam, Paris, Jerusalem, Budapest, Regensburg, Nuremberg, Dresden, Antwerp, Ghent, Bruges, Naples, Utrecht, Limburg and more. In the next 12 months, Time Machine is expected to grow as a large community of communities, sharing a standardised platform, with more empowering tools.

Background

In early 2016, the European Commission held a public consultation of the research community to gather ideas on science and technology challenges that could be addressed through future FET Flagships. End of 2016, Commissioner Oettinger hosted a round-table event with high-level representatives from the Member States, industry and academia. They agreed on three major areas where promising grand science and technology challenges could be addressed by the FET Flagships: “ICT and connected society”, “Health and the life sciences” and “Energy, environment and climate change”. As a result, a call for preparatory actions for future research initiatives was launched in October 2017 as part of the Horizon 2020 FET Work Programme 2018. From the 33 proposals submitted, six were selected after a two-stage evaluation by independent high-level experts.

The 33 institutions receiving parts of the €1 million to develop Time Machine

1. ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
2. TECHNISCHE UNIVERSITAET WIEN
3. INTERNATIONAL CENTRE FOR ARCHIVAL RESEARCH
4. KONINKLIJKE NEDERLANDSE AKADEMIE VAN WETENSCHAPPEN
5. NAVER FRANCE
6. UNIVERSITEIT UTRECHT
7. FRIEDRICH-ALEXANDER-UNIVERSITAET ERLANGEN NUERNBERG
8. ECOLE NATIONALE DES CHARTES
9. ALMA MATER STUDIORUM – UNIVERSITÀ DI BOLOGNA
10. INSTITUT NATIONAL DE L’INFORMATION GEOGRAPHIQUE ET FORESTIERE
11. UNIVERSITEIT VAN AMSTERDAM
12. UNIWERSYTET WARSZAWSKI
13. UNIVERSITE DU LUXEMBOURG
14. BAR-ILAN UNIVERSITY
15. UNIVERSITA CA’ FOSCARI VENEZIA
16. UNIVERSITEIT ANTWERPEN
17. QIDENUS GROUP GMBH
18. TECHNISCHE UNIVERSITEIT DELFT
19. CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
20. STICHTING NEDERLANDS INSTITUUT VOOR BEELD EN GELUID
21. FIZ KARLSRUHE- LEIBNIZ-INSTITUT FUR INFORMATIONS INFRASTRUKTUR GMBH
22. FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
23. UNIVERSITEIT GENT
24. TECHNISCHE UNIVERSITAET DRESDEN
25. TECHNISCHE UNIVERSITAT DORTMUND
26. OESTERREICHISCHE NATIONALBIBLIOTHEK
27. ICONEM
28. INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ AKADEMII NAUK
29. PICTURAE BV
30. CENTRE DE VISIÓ PER COMPUTADOR
31. EUROPEANA FOUNDATION
32. INDRA
33. UBISOFT

Website: timemachine.eu

Social Media:
Twitter: @TimeMachineEU
Instagram: @TimeMachineEU

Contact:
For more information about the Time Machine Project, please contact:
Kevin Baumer, Ecole Polytechnique Fédérale de Lausanne
kevin.baumer@epfl.ch

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