ATM: Amsterdam Time Machine
The Amsterdam Time Machine presents historical information about people, places, relations, events, and objects in its spatial and temporal context. The web of historical data is created by systematically linking datasets from social and humanities research with municipal and cultural heritage data.
Is it possible to travel back in time and walk the streets of historical Amsterdam? We certainly think so. The Amsterdam Time Machine (ATM) is an integrated platform to present historical information about people, places, relations, events, and objects in its spatial and temporal context. The web of data on the history of Amsterdam is created by systematically linking existing datasets from social and humanities research with municipal and cultural heritage data. Where possible this is done in the form of Linked Open Data. The linked data can then be organized and presented in spatial representations, such as geographical and 3D visualizations. The result is a ‘Google Earth’ for the past, which invites users to explore the city through space and time, at the level of neighborhoods, streets, or individual houses.
A CLARIAH grant made it possible to develop a first proof of concept. In the CLARIAH Amsterdam Time Machine project the linked data from cultural heritage institutions made available in the AdamLink project is combined with that of various scholarly research projects at the International Institute for Social History, Huygens ING, Meertens Institute and University of Amsterdam, and integrated with a GIS developed by Fryske Akademy. Subsequently, the historical geographical and topological context for these linked datasets is made available open access in the CLARIAH infrastructure at the KNAW Humanities Cluster.
The project also comprises three research use cases on language, social mobility and leisure. These use cases demonstrate how the Amsterdam Time Machine offers instruments for research into urban space as a connecting factor for observing and analyzing social and cultural processes. On the one hand, they testify to the potential of the framework for innovating disciplinary research in Linguistics, History and Media Studies. On the other hand, they show how the research infrastructure also supports interdisciplinary research, by making a connection between the social development of Amsterdam’s historical population groups, their language development and their leisure activities in local theatres and cinemas.
More generally, ATM facilitates ‘scalable digital humanities research’: smoothly navigating historical data from the micro level of one location, anecdote or document to the macro level of patterns in large, linked datasets that expose broader social and cultural processes. Charles Tilly described the city as a “privileged site for study of the interaction between large social processes and routines of local life” (Tilly 1996, 704). The Time Machine operationalizes this by investigating the urban history of Amsterdam on a scale that varies between the micro level of a plot, person or place and the macro level of broader societal processes in the city as a whole - a microscope and telescope in one. Such a research environment offers an unprecedented opportunity to explore the relationship between physical and social space and how this connection was experienced and transformed over time. With space as a connecting factor, the Time Machine provides a concrete illustration of the research potential of linking social and economic data with cultural data, allowing researchers to study specific historical and cultural phenomena against the background of broader societal developments.