Why Engage in Digital Mapping?
▪ Relates qualitative and quantitative information to space (and time)
▪ Dynamic representations of place and space
▪ Complements traditional interpretive narratives
▪ Enables researchers and students to explore data in new ways and ask new questions
▪ Students from GWSS 3590: Environmental Disparities & Sustainability worked with the Minnesota Pollution Control agency to map population demographics like race and class alongside environmental features like sites of toxicity and emissions levels
Digital mapping allows researchers to georeference or geolocate their idea. Using a geographic information system (GIS), scholars relate information to space (and sometimes, time, too). As Gregory & Geddes (2014) put it, “GIS can be thought of as a type of software that provides a way of representing features on the Earth’s surface and a suite of operations that allow the researcher to query, manipulate, visualize, and analyze these representations.”
Digital mapping allows for both qualitative and quantitative data to be mapped ‒ in this way, mapping can be part of a mixed methods approach.
“A humanities GIS-facilitated understanding of society and culture may ultimately make its contribution … by creating the simultaneous context that we accept as real but unobtainable by words alone … In sum, it promises an alternate view of history and culture through the dynamic representation of memory and place, a view that is visual and experiential, fusing qualitative and quantitative data within real and conceptual space. It stands alongside ‒ but does not replace ‒ traditional interpretive narratives, and it invites participation by the naive and knowledgeable alike.”
-Bodenhamer, Corrigan, and Harris (2010)
But while digital mapping can expand the ways in which scholars analyze the subject matter of their disciplines, GIS poses challenges. Researchers must learn how to effectively move data into a GIS database and then learn how to effectively utilize the maps, web applications, and other outputs to display this new knowledge.
One key aspect is mapping data in a way that allows the researcher to ask new questions of the data, rather than mapping the data with a specific output in mind.
“The challenge, then, for humanities GIS is to use technology to probe, explore, challenge, and complicate, in sum, to allow us to see, experience, and understand human behavior in all its complexity. As in traditional humanities scholarship, the goal is less to produce an authoritative or ultimate answer than to prompt new questions, develop new perspectives, and advance new arguments or interpretations.”
-Bodenhamer, Corrigan, and Harris (2010)
By incorporating digital mapping techniques, researchers are able to view their data through the lens of geographic analysis, allowing for both new interpretations of data and the ability to pose new questions of existing data.
For any questions or assistance, please contact us (email@example.com).
Diverse Farms, Diverse Foods: Farm Size and Nutrient Diversity
(esri, Peder Engstrom, Master of Geographic Information Science, College of Liberal Arts, University of Minnesota, Best Overall Map, U-Spatial Mapping Prize Winner 2017)
Mapping for Justice: Air Emissions Impacts on Vulnerable Minneapolis Communities
(Students of GWSS3590: Gender, Women, and Sexuality Studies, College of Liberal Arts, University of Minnesota – Undergraduate Student: Best Body of Work, U-Spatial Mapping Prize Winner 2017)
Boundaries of Discrimination: US Congressional District Gerrymandering Case Studies
(esri Story Maps, Frank Wagner, Master of Geographic Information Science, College of Liberal Arts, University of Minnesota – Graduate Student: Best Body of Work, U-Spatial Mapping Prize Winner 2017)
Impact of the Camino
(esri, Grace Johnson, Master of Geographic Information Science, College of Liberal Arts, University of Minnesota – Graduate Student: Best Use of Maps, U-Spatial Mapping Prize Winner 2017)
Discovery: A Spatial Summary of Captain Scott’s British National Antarctic Expedition
(esri Story Maps, Carl Reim, Master of Geographic Information Science, College of Liberal Arts, University of Minnesota – Graduate Student: Best Body of Work, U-Spatial Mapping Prize Winner 2016)
Tax Increment Financing in Chicago
(esri Story Maps, Keavy McFadden, PhD candidate, Geography, Environment and Society, College of Liberal Arts, University of Minnesota – Graduate Student: Most Provocative/Transformative, U-Spatial Mapping Prize Winner 2016)
The Mapping of Joy and Pain
(esri, Rebecca Krinke & Borchert Map Library, University of Minnesota)
Mapping Balzac’s Paris
(Taporware, Voyant-Tools, HTML, CSS, ESRI/Leaflet API, ArcGIS for Desktop, ArcGIS for Server, and GitHub, Jennifer Reinke, Borchert Map Library, University of Minnesota)
Spatial History Project
(Center for Spatial and Textual Analysis, Stanford University)
Humanities GIS Projects
(Drupal, GeoHumanities Special Interest Group, Alliance of Digital Humanities Organizations)
Recommended Tools for Digital Mapping
Learn more about the tools that can facilitate digital mapping.
University licensed; web-based; basic and advanced functions are not overly complex; can use for spatial analysis of mapped data.
University licensed; Windows only; robust desktop GIS software; basic and advanced functions can be complicated to learn; can use for spatial analysis of mapped data.
Esri Story Maps are web applications that let authors combine maps with narrative text, images, and multimedia, including video.
Free; open source; Windows, MacOS, Linux; desktop GIS software; basic and advanced functions can be complicated to learn; can use for spatial analysis of mapped data.
Free; web-based; great for mapping time-enabled data; basic functions very easy to learn; advanced functions require some knowledge of HTML and/or SQL.
Free plug-in for Omeka platform; most useful with a basemap or background image; can be useful for data that is hard to map or needs a lot of contextual information for each data point; not as robust as an actual GIS.
Free; web-based; relatively easy to use; can be useful for data that needs a lot of contextual information for each data point; not as robust as an actual GIS.
Free; web-based; relatively easy to use; not as robust as an actual GIS.