The Amsterdam Time Machine (ATM) is a digital commons on the history of Amsterdam. It is currently coordinated by the CREATE research program at the University of Amsterdam and powered by a consortium of people and institutions in academia, cultural heritage and industry.
Born in 2017, the ATM brings together efforts in the fields of academia, culture heritage and computer science to digitally unlock information on Amsterdam’s past. The ATM comprises many larger and smaller projects that can be found in the Projects tab (add your own!).
Ultimately, the web of information on people, places, relationships, events, and objects will unfold in time and space through geographical and 3D representations. While we’re working on that, we’d like to provide access to the three building blocks of the Time Machine: a Linked Data cloud called ALiDa; Maps and other geo information; and 3D reconstructions.
We invite everyone to join, by connecting their own data and by using the data for research, storytelling, or other purposes. Its linked and open structure, and its collaboration with other Dutch Time Machines, in the European Time Machine, ensures that the Amsterdam data is connected across the Netherlands and abroad, just as the city itself always has been.
The city as research lab
We study cities, in our case Amsterdam, in the broadest possible sense of the word. The city as it is documented, experienced, planned and imagined, in historical textual and visual sources, but also in the minds of people as represented in literature and films. The Time Machine, like a macroscope, allows for scalable humanities research.
We can zoom in and out, observe everyday life and micro-stories, but also identify long-term patterns. The historical city is our lab. Or as Charles Tilly put it, the city is a “privileged site for study of the interaction between large social processes and routines of local life”, and the ATM hopes to help unpack this site. Systematic linkage of datasets from heterogeneous sources allows users to ask questions about, for instance, cultural events, everyday life, social relations, or the use of public space in the city of Amsterdam.
A public urban history
How can we bridge the study of urban history and popular presentation of the urban past? How can be urban history be relevant beyond academia? And how does it relate to the challenging topic of heritage? The Amsterdam Time Machine aims to help bridge the fields and datasets of history and heritage, but also to provide a place where the potential and problems in collaborations can be openly discussed. Perhaps we can, for now, call it, borrowing here from Bob Shoemaker, a public facing research resource. This also means we seek collaboration with broader audiences, collectively negotiating history and heritage.
Like many digital history resources, we see space as a means to organise and present information. Systematic linkage of datasets from heterogeneous sources allows users to ask questions about, for instance, cultural events, everyday life, social relations, or the use of public space in the city of Amsterdam. And admittedly, we’re influenced by the spatial turn, when it comes to analysing the role of space and place in historical change and continuity. By the way: in this explanation of the spatial turn in history, Jo Guldi challenges the city as privileged unity of analysis for social-historical research
Big data of the past & the digital humanities
Big Data of the Past are expected to lead to data-driven historical simulations, making the past de facto as easily accessible as the present. New families of historical search engines, as well as immersive and augmented reality interfaces and other tools, could generate what one could describe as time capsules to seamlessly navigate 2000 years of European history. Thousands of time travellers are already ready to engage in the project, for curating the data, design algorithms and ultimately, to a certain extent, writing a common history of Europe. That approach in turn could apply to other cities, communities and regions of the world.
The digitalisation of historical information often leaves researchers with ‘fuzzy’ data. Besides being difficult to read, they are at times too copious for traditional research methods to process. The Amsterdam Time Machine, like other Digital Humanities initiatives, uses computational techniques to process information from the past in a meaningful, including information stored in visual, linguistic, cartographic material. As these methods process and combine more information, they also allow us to pose more complex questions about the original context the information came from.
Digital methods are increasingly common in undergraduate and graduate humanities classrooms, and we think the Time Machine can be used as a social and pedagogical tool. We develop the Amsterdam Time Machine together with students, this way stimulating students to engage with new technology, collaborate with peers, graduate students, and faculty, and produce tangible scholarship that is publicly visible.