Course Details

Course Name
Digital Humanities: Coding and Data Visualization
Course Type
Bachelor Programme
Institution
University of Pittsburgh at Greensburg
Department
Humanities Division
Information
http://dh.newtfire.org/CDV.html
Curriculum
http://greensburg.pitt.edu/academics/info/digital-studies
Status
record actively maintained
Course Language
English
Start Date
2019-01-07
recurring
ECTS
-
Lecturer
Elisa Beshero-Bondar
PID
Disciplines: Arts and Cultural Studies, Computer Science, History, Human Language Technologies, Linguistics and Language Studies, Literary and Philological Studies, Media and Communication Studies, Philosophy, Social Sciences, Theory and Methodology of DH
Techniques: Brainstorming, Browsing, Collocation Analysis, Commenting, Distance Measures, Encoding, Georeferencing, Information Retrieval, Mapping, Pattern Recognition, Preservation Metadata, Scanning, Searching, Technology Preservation, Text Mining
Objects: Artifacts, Computers, DigitalHumanities, Data, File, Images, Interaction, Link, Literature, Manuscript, Map, Metadata, Multimedia, Multimodal, NamedEntities, Projects, Research, ResearchProcess, ResearchResults, Software, Standards, Text, TextBearingObjects, Tools, Visualization
Access Requirements
* cross-platform compatible * students work with an oXygen XML Editor license supplied by U. of Pittsburgh * students work with Cytoscape (free network analysis software) and Google Maps * students set up a GitHub account and create GitHub repositories * students build websites on the instructors' server
Description
In this course, you will learn methods for marking, extracting, and analyzing data from digital documents to produce visualizations such as graphs, charts, diagrams, maps, which you will design in the context of real projects. This course is meant to be complementary with the Coding and Digital Archives course, but where the emphasis in that course is on curating and preparing reading views of documents, this course concentrates on analyzing data to produce informational graphics. Neither course is meant to be a prerequisite for the other: you may take either one as a beginner. Returning students (in either semester) serve as student instructor-mentors to beginning students for units and assignments they have already completed confidently. Our class is one of the core courses of Pitt-Greensburg’s Digital Studies Certificate, and it satisifes a range of general education requirements in quantitative reasoning, behavioral sciences, and humanities. That is because this course is distinctively interdisciplinary in engaging formal and quantitative reasoning through computer coding in ways that matter to students in humanities and social sciences who are not training to be computer scientists. Students gain hands-on experience in this course with applying computer coding to represent and investigate cultural materials. As we design projects together, you will gain practical experience in editing and you will certainly fine-tune your precision in writing and thinking. You will also be learning in an openly collaborative environment (as professional coders learn and work) with an emphasis on building sustainable and freely accessible resources on the public web. Students who complete this course will gain skills in digital project management and web development, and their digital projects will distinguish them as investigators and makers, able to wield computers creatively and effectively for human interests. Your success will require patience, dedication, and regular communication and interaction with us, working through assignments on a daily basis. Your success will not require perfection, but rather your regular efforts throughout the course, your documenting of problems when your coding doesn’t yield the results you want. Homework exercises are a back-and-forth, intensive dialogue between you and your instructors, and we plan to spend a great deal of time with you individually over these as we work together. Our guiding principle in developing assignments and working with you is that the best way for you to learn and succeed is through regular practice as you hone your skills. Our goal is not to make you expert programmers (as we are far from that ourselves). Instead, we want you to learn how to apply coding technologies for your own purposes, how to track down answers to questions, how to think your way algorithmically (step-by-step) through problems to find good solutions. Survey of Coding Technologies Covered: We work primarily with eXtensible Markup Language (XML) because it is a powerful tool for modelling texts that we can adapt creatively to our interests and questions. XML represents a standard in adaptability and human-readability in digital code, and it works together with related technologies with which you will gain working experience: You’ll learn how to write XPath expressions: a formal language for searching and extracting information from XML code which serves as the basis for transforming XML into many publishable forms. You’ll learn to write XSLT: a programming “stylesheet” transforming language designed to convert XML to publishable formats. In this course, you will also learn XQuery, an XPath-based language designed to query XML as a database, and we will use XQuery to extract information and plot it in charts in graphs in Scalable Vector Graphics (SVG). You will learn how to design your own systematic coding methods to work on projects, and how to write your own rules in schema languages (like Schematron and Relax-NG) to keep your projects organized and prevent errors. Since one of the best and most widely accessible ways to publish XML is on the worldwide web, you’ll gain working experience with HTML code (a markup language that is a kind of XML), styling HTML with Cascading Stylesheets (CSS), and adding dynamic features to your website with JavaScript.
Keywords
Disciplines: Arts and Cultural Studies, Computer Science, History, Human Language Technologies, Linguistics and Language Studies, Literary and Philological Studies, Media and Communication Studies, Philosophy, Social Sciences, Theory and Methodology of DH
Techniques: Brainstorming, Browsing, Collocation Analysis, Commenting, Distance Measures, Encoding, Georeferencing, Information Retrieval, Mapping, Pattern Recognition, Preservation Metadata, Scanning, Searching, Technology Preservation, Text Mining
Objects: Artifacts, Computers, DigitalHumanities, Data, File, Images, Interaction, Link, Literature, Manuscript, Map, Metadata, Multimedia, Multimodal, NamedEntities, Projects, Research, ResearchProcess, ResearchResults, Software, Standards, Text, TextBearingObjects, Tools, Visualization