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The Digital Humanities is an emerging discipline that applies computation to research in the humanities. More than simply conducting research with computers, Digital Humanities scholars utilize all of the emerging tools facilitated by computation to conduct their analysis of the various material throughout the humanities disciplines. It is a suite of resources, a community, a research methodology, cutting edge tools, and more. Check out the Bibliography on the Resources page to learn more.
A large constituency of Digital Humanities scholars employ methods of textual analysis over vast corpora of text documents. Much of this consists of counting word occurrences. Such analytic methods include Topic Modeling, which works by identifying relationships between concepts by counting words that occur near each other often. By incorporating such analytic methods researchers can further explore the concepts that arise. Some prep work is often necessary, so text encoding is performed. Referring to marking up digital text in a machine readable and universally shareable manner, text encoding lends itself to many scholarly activities such as publishing, searching, and text analysis. The Text Encoding Initiative (TEI) is a consortium of developers who maintain guidelines for the representation of texts in digital form and provide schemas with which to work. Marking up a text in TEI ensures that your documents are machine readable and potentially shareable to the greater research community. The Scholarly Commons has three high resolution scanners and Optical Character Recognition Software to convert PDFs as well as text documents into a readable text data set in order create a corpus to perform such computation.
Tools in Scholarly Commons: ATLAS.ti, NVivo, Oxygen, ABBYY Fine Reader, digital scanners
The "spatial humanities" utilizes Geospatial Information Systems (GIS) in order to create interactive maps to assist in better understanding the concept of "space" in relation to humanistic research. Answers to questions such as "How does space influence events?" or "What has this space meant in history?" can potentially be represented with GIS software. For more on spatial data services at the Scholarly Commons, see the Data Services Page.
Tools in the Scholarly Commons: ArcGIS, GRASS, GoogleEarth
Generating visualizations is a way to "see" your data. An example can be a network analysis, which generally refers to the study of the structure of relationships between multiple entities. For example, a researcher may generate a network of concepts, embodied in words, and track how certain concepts relate to each other, influence one another, or even predict one another, or perform a cluster analysis to determine which words occur nearer each other.
Tools in Scholarly Commons: ATLAS.ti, NVivo, R
Example Project: "Visualizing Topic Models"
Planning your research project in advance can help you keep track of your goals and organize your research. A plan will allow you to tackle the various aspects of your project methodically so you don't start on something before it is able to be completed. It is also important to know what you plan to do with the data you generate, whether you want to archive it, share it, etc.
Before getting started, it may be beneficial to talk to a librarian. Harriet Green, the English and Digital Humanities Librarian, can help you with project planning and connecting you with tools and other resources.