Associate Professor, American University of Beirut

How did you make that (digital) literary geography?

How did you make that (digital) literary geography?
American University of Beirut
24 November 2015


At the invitation by IT academic services and the Center for Teaching and Learning at AUB, this short presentation will give an overview of some digital approaches to location-based literary phenomena (sociology of literature, modeling narrative, digital storytelling, map-text relationships, etc).

Outline of the presentation:

1  Introduction

Tomorrow’s Teaching and Learning (circulated by CTL, 19 Nov) – higher order thinking skills, spatial literacies, interdisciplinary co-learning, making critical arguments in a variety of formats, open geographic data, modeling data
Moretti’s Atlas of European Novel vs. national literary geographies (Ferre, Bartholomew, de Oliviera)
Miriam Posner’s blog How did they make that?
DHCommons Journal “How Did They Make That?” issue 1
GeoHumanities gallery Humanities GIS
starter bibliography
related workshop– Cairo October 2015 (with hands on component, not all literary)

pieces of a spatial project: locations, geographic coordinates, other relevant metadata, projection system, database, base maps, APIs

2  Advanced non-literary examples (born-digital data)

Obesity map @kyle_e_walker
What: visualization of open data about obesity in the US
How: fetching data on obesity from CDC, programming language R, processing data, pushing automatically to cloud web mapping (CartoDB), “abstract” base map

Wimbledon 2014
What: A map of tweets during Wimbledon final match
How: twitter mining, cloud hosting and visualization using torque (CartoDB)

2  (Mostly hand curated, non-born digital data) Examples from literature and culture

Pre-modern Spanish literature @RojasCastroA
What: A map of places mentioned in Spanish Golden Age works by Gongora.
How:  manual extraction and geoparsing,cloud hosting of data, use of color, unlabelled political map, info box containing snippets of text,web mapping (CartoDB), open data

Roman de la violette (vers vs prose) @DJWrisley
What:  mentions of places in a 13th c verse text and its 15th prose rewriting
How: manual extraction and geoparsing,cloud hosting of data, contrasting color and shape, unlabeled satellite view, web mapping (Google Maps), open data

French epic space-time choropleth vs torque @DJWrisley
What: mentions of places in a corpus of medieval French epic poems by date of composition
How: manual extraction and geoparsing, cloud hosting of data, unlabelled political map, web mapping and animation (CartoDB), open data

Exploring Place in the French of Italy @MVSTFordham @DJWrisley
What: exhibit built around mention of places in a corpus of medieval French texts composed in Italy, individual maps, weighted by place, composite map and essays
How: semi-manual extraction, geoparsing and counting, cloud hosting of data, embedded maps in Omeka (from CartoDB), open data

Dislocating Ulysses
What: locating objects from an exhibit about Ulysses within their geospatial context and historical context within Dublin
How: manual geoparsing, hosted in Google Earth (here viewed as video capture)

Slave Revolt in Jamaica, 1760
What: animated thematic map of Jamaica slave insurrection
How: manual extraction and geoparsing?, listed archival sources, “locational database”, historical base map, animation, timeline, Leaflet

Grub Street Project
What: “a digital edition of eighteenth-century London”, “both a real place and an abstract idea”
How: digital edition in TEI linked to map, manual extraction and geoparsing, web mapping, custom interface

Life of Maya Angelou
What: digital storytelling of places important across time for the life of Maya Angelou
How: manual extraction and geoparsing, Odyssey.js, cloud hosting of data, Markdown

Bruce Chatwin’s Utz vs Vichy
What: contrast of two novels by Chatwin and different narratological modes
How: ArcGIS?, fuzzy spaces as dispersion, color, not web mapping (static images)

Interactive Ibn Jubayr
What: a set of interactive exhibits from a class on Ibn Jubayr
How: manual extraction and geoparsing, Omeka, Neatline

Atlantic Networks Project
What: visualizations of data from the “logbooks of the merchant vessels that participated in an Atlantic commodity network”
How: manual extraction of data, ArcGIS, web mapping (ArcGIS), semi-open data

Mapping the Lakes: A Literary GIS
What: an exploration of the places mentioned in Gray’s and Coleridge’s accounts of the Lake District, the emotions expressed in them
How: semi-manual extraction of data, ArcGIS?, not web mapping (static images) and Google Earth kmz download, semi-open data

Visualizing Medieval Places in Time @DJWrisley
What: mention of real places in medieval French literature by date of composition
How: semi-manual extraction of data, cloud hosting of data, third-party hosting of map, custom time slider written in Java

ReNom (Ronsard vs Rabelais)
What: Database, map visualization, people & places (real, mythical, imaginary) of two French authors
How: semi-automatic extraction of data, Drupal, filterable interface, web mapping and text interconnected

Rai’tu Ramallah @Randa_DH
What:  A visualization of the places mentioned in Barghouti’s novel about Palestine, contrasting places visited and not visited (created in Fall 2013 Intro to DH seminar)–other student projects here
How: manual extraction and geoparsing, color, web mapping (Google Maps), open data

Beirut publishes…  @DJWrisley
What: A thick map of the Lebanese publishing industry over the last century (under construction, course project)
How: Manual extraction from archival materials, cloud database, mobile data collection, web scraping of publication metadata, open dataset to be published (GitHub and Zenodo with DOI)

What: Project quantifying and visualizing the Lord of the Rings, map, timelines
How:  Grid built based on Tolkien’s map, image coordinate system, “infographics”, timelines

“Where are you in Beirut?”  @DJWrisley and ENGL 229
What: A response to Mapping a City without Street Names, visualizing crowd conceptions of location in Beirut
How: human-created data by-product of Mapping Language Contact in Beirut, data field in mobile data collection application (Fulcrum), cloud live hookup, web mapping (CartoDB)

“What do you tell the taxi to get where you are in Beirut?”
What: Another response to Mapping a City without Street Names, visualizing crowd conceptions of closest place for public transport mobility
How: human-created data by-product of Mapping Language Contact in Beirut, data field in mobile data collection application (Fulcrum), cloud hookup, web mapping (CartoDB)

3  Discussion

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