My First Academic Conference: A Roadmap to Mapping Messiness
by Jianing Zhao (class of 2020, Slavic major)
“I’m a trained cartographer, and I love maps because they lie.” We all laughed at this remark made by a participant on the first day of our workshop, but it turned out to be one of my most important takeaways.
More about “digital mapping” than about “Eastern Europe,” this workshop united experts across disciplines who work on diverse topics ranging from gentrification in US cities to community-managed national parks in Belize. Even though English was the third or forth language for many workshop participants, our research methodology – mapping – served as our common language. This allowed me, an undergraduate majoring in Slavic and with interest in Classical archeology, but with little background on Eastern Europe, to be able to understand presentations on unfamiliar topics, to draw inspiration from their DH methods, and to reflect on their applicability to my own research project. It is rather unique that an academic conference can feel so beginner-friendly, while providing a great roadmap –not of what to do, but of what to look for and what to look out for.
The first thing we learned about mapping was what challenges to expect, such as the fluid borders and the variety of geographical names. These elements of tension stayed in the back of my mind as the workshop progressed, constantly nudging and reminding me that data is often messy, borders are often blurry, and maps are only models. Are borders necessary at all? I thought. What if we just map the dots – locations of pottery finds across the ancient Mediterranean, for example, to trace regional influences and developments in pottery style? I was excited to discover that the keynote speaker, Katharina Lorenz, is a classical archaeologist. It was such a pleasant surprise, and a truly eye-opening talk as she introduced various applications of mapping as a way to visualize events and places in historical processes. Stanford’s Orbis project, for example, renders geographical distance as time distance to illustrate routes and constraints related to travel in the Roman world. This indirectly responded to my previous thought about the intricacies of juxtaposing time and space in maps.
But new questions started to surface– more theoretical, systematic ones: how do we approach digital mapping when geospatial practices are already an intrinsic part of the discipline? For example, mapping with digital tools such as Total Station and RTI has been integral practices in archaeology for long, so does it count as digital humanities? Why do we never say “digital physics”? It was as if the keynote speaker saw the questions in my head, since she soon brought out an important point: Digital mapping must be approached as a research method, not a means of making or illustrating arguments: reading-in, not reading-from. It was a moment of epiphany for me. For as long as I’ve been exposed to DH, it draws me in like a blackhole – I’m eager to incorporate DH methods in my projects, without having thoroughly thought through what exactly I want to find or argue, and why DH is necessary to help me achieve that.
Let me take a step back. On the evening of the second day of the workshop, I finally started doing the preliminary research I should have done long ago for my potential thesis project – on Russian émigrés in Paris during the interwar period. I looked at DH projects on relevant topics and scopes to see how I can do similarly or differently. The whole environment of the workshop was deeply motivating – I searched, I reflected, I planned, and for the first time in my life, I feel like a real academic, even though I’m just an undergraduate at the very beginning of my academic career. I changed my major to Slavic following this workshop, and am going to Moscow this winter for a first round of archival research. But these are just the tip of the iceberg.
I started really paying attention to what kinds of data I need, what kinds of data I have, and what to do to bridge the gap in between. For the data I’ll have, I already know that they will not all fall into neat categories. Paris in the interwar period is a huge messy web of people, events, and connections, and how to map this messiness will be a question I soon need to face – as well as why I want to map it. Maps lie, but if they lie well, we might be able to tell some truths from their lies. This workshop taught me how to read maps by telling truths from lies, and inspired me to makes maps that lie well.
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