I’m a week and a bit into the NEH Institute for Advanced Topics in the Digital Humanities on ‘Spatial Narrative and Deep Maps: Explorations in the Spatial Humanities‘, so this is a (possibly self-indulgent) post to explain why I’m over in Indianapolis and why I only seem to be tweeting with the #PolisNEH hashtag. We’re about to dive into three days of intense prototyping before wrapping things up on Friday, so I’m posting almost as a marker of my thoughts before the process of thinking-through-making makes me re-evaluate our earlier definitions. Stuart Dunn has also blogged more usefully on Deep maps in Indy.
We spent the first week hearing from the co-directors David Bodenhamer (history, IUPUI), John Corrigan (religious studies, Florida State University), and Trevor Harris (geography, West Virginia University) and guest lecturers Ian Gregory (historical GIS and digital humanities, Lancaster University) and May Yuan (geonarratives, University of Oklahoma), and also from selected speakers at the Digital Cultural Mapping: Transformative Scholarship and Teaching in the Geospatial Humanities at UCLA. We also heard about the other participants projects and backgrounds, and tried to define ‘deep maps’ and ‘spatial narratives’.
It’s been pointed out that as we’re at the ‘bleeding edge’, visions for deep mapping are still highly personal. As we don’t yet have a shared definition I don’t want to misrepresent people’s ideas by summarising them, so I’m just posting my current definition of deep maps:
A deep map contains geolocated information from multiple sources that convey their source, contingency and context of creation; it is both integrated and queryable through indexes of time and space.
Essential characteristics: it can be a product, whether as a snapshot static map or as layers of interpretation with signposts and pre-set interactions and narrative, but is always visibly a process. It allows open-ended exploration (within the limitations of the data available and the curation processes and research questions behind it) and supports serendipitous discovery of content. It supports curiosity. It supports arguments but allows them to be interrogated through the mapped content. It supports layers of spatial narratives but does not require them. It should be compatible with humanities work: it’s citable (e.g. provides URL that shows view used to construct argument) and provides access to its sources, whether as data downloads or citations. It can include different map layers (e.g. historic maps) as well as different data sources. It could be topological as well as cartographic. It must be usable at different scales: e.g. in user interface – when zoomed out provides sense of density of information within; e.g. as space – can deal with different levels of granularity.
Essential functions: it must be queryable and browseable. It must support large, variable, complex, messy, fuzzy, multi-scalar data. It should be able to include entities such as real and imaginary people and events as well as places within spaces. It should support both use for presentation of content and analytic use. It should be compelling – people should want to explore other places, times, relationships or sources. It should be intellectually immersive and support ‘flow’.
Looking at it now, the first part is probably pretty close to how I would have defined it at the start, but my thinking about what this actually means in terms of specifications is the result of the conversations over the past week and the experience everyone brings from their own research and projects.
For me, this Institute has been a chance to hang out with ace people with similar interests and different backgrounds – it might mean we spend some time trying to negotiate discipline-specific language but it also makes for a richer experience. It’s a chance to work with wonderfully messy humanities data, and to work out how digital tools and interfaces can support ambiguous, subjective, uncertain, imprecise, rich, experiential content alongside the highly structured data GIS systems are good at. It’s also a chance to test these ideas by putting them into practice with a dataset on religion in Indianapolis and learn more about deep maps by trying to build one (albeit in three days).
As part of thinking about what I think a deep map is, I found myself going back to an embarrassingly dated post on ideas for location-linked cultural heritage projects:
I’ve always been fascinated with the idea of making the invisible and intangible layers of history linked to any one location visible again. Millions of lives, ordinary or notable, have been lived in London (and in your city); imagine waiting at your local bus stop and having access to the countless stories and events that happened around you over the centuries. … The nice thing about local data is that there are lots of people making content; the not nice thing about local data is that it’s scattered all over the web, in all kinds of formats with all kinds of ‘trustability’, from museums/libraries/archives, to local councils to local enthusiasts and the occasional raving lunatic. … Location-linked data isn’t only about official cultural heritage data; it could be used to display, preserve and commemorate histories that aren’t ‘notable’ or ‘historic’ enough for recording officially, whether that’s grime pirate radio stations in East London high-rise roofs or the sites of Turkish social clubs that are now new apartment buildings. Museums might not generate that data, but we could look at how it fits with user-generated content and with our collecting policies.
Amusingly, four years ago my obsession with ‘open sourcing history’ was apparently already well-developed and I was asking questions about authority and trust that eventually informed my PhD – questions I hope we can start to answer as we try to make a deep map. Fun!
Finally, my thanks to the NEH and the Institute organisers and the support staff at the Polis Center and IUPUI for the opportunity to attend.