Tools + Methodologies
Below are a number of tools to get you started with your own project. For each set, they will run in rough order from easiest to hardest (i.e. online, very little learning curve to those that require stronger programming skills), and will also include short descriptions of each tool and some background reading and viewing. Wherever possible, we tried to use free trainings open to all, but some (like Lynda.com) require a University of Minnesota login or password, or a personal subscription to Lynda.com.
If there are tools or resources that you think should be on here that aren’t, Let us know!
Data VisualizationRAW: Very easy online data visualization built on the D3.js language
ManyEyes: online IBM platform for more general data visualizations
NodeXL (PC only): Network visualization program
Gephi: Tool for analyzing and visualizing social networks
- "Demystifying Networks", a series of excellent blog posts by Scott Weingart introducing network analysis and visualization
- Elijah Meeks and Maya Krishnan - An Interactive Introduction to Network Analysis and Representation
- David McCandless - “The Beauty of Data Visualization”
- Santiago Ortiz: 45 Ways to Communicate Two Quantities
- Scott Murray - "Interactive Data Visualization for the Web"
Galleries of Data Visualizations:
Multimodal ScholarshipGoogle Sites
Omeka (Web version)
- Local server version
- “Up and Running with Omeka.net", Miriam Posner
- Omeka at University of Minnesota Libraries
- Wendy Hsu, "Ethnography Beyond the Text: How the Digital Can Transform Ethnographic Expressions"
- Tara McPherson, “Introduction: Media Studies and the Digital Humanities.” Cinema Journal 48, No. 2 (Winter 2009): 119-123.
MappingGoogle Maps via Fusion Tables
- Used through Google Drive, have to use personal Gmail account, not U of M
ArcGIS: Proprietary industry standard mapping software; University of Minnesota has a site license
CartoDB: Easy to use proprietary online mapping platform
MapBox: Easy to use proprietary online mapping platform
QGIS: An open-source desktop GIS platform
R Programming Language
- A Guide to Text Mining from Stanford’s “Tooling Up” series
- Matt Jockers - Macroanalysis
- Franco Moretti and the Stanford Literary Lab