Making sense of large quantities of content in its raw form is tedious at best. As a culture, we now possess increasing quantities of data from a variety of sources, such as those generated regularly by RADARs, SONARs, acquired by satellites, ground-based telescopes, surveys or polls conducted, usage metrics of our hospitals and highways, and income as well as expenditures. We must use this data and act upon it to predict weather, locate anomalous (interesting?) signals from outer space, modify the phrasing of political campaigns, manage services for patients, healthcare providers, or commuters, and plan our national budget. While generations of humanists have read and interpreted the Bible or works of Shakespeare through the written word, employing computational power for textual data provides us a new mechanism for engaging with literature, historical data, finding patterns that a diligent reader may miss over the course of several readings of a text. Presenting content by extracting and enhancing its visual qualities enables us to transition from understanding the data to analyzing it and potentially, to focus on specific situations of interest.
In this course, we will study the concepts, issues, and strategies used for visualizing large content--numeric and textual, structured and unstructured. We will explore the landscape of techniques that have been developed for visualising information in an engaging manner. We will learn the use of Web-based toolkits as well as desktop products that enable data presentation in various formats. In addition, we will develop our own presentations for small data sets using the Processing language. Working with data invariably requires cleaning, massaging, and curation. However, this class will not focus on these critical aspects of the data presentation process but rather on the presentation mechanisms and techniques themselves.
All course-related readings and materials will be made available online through Canvas or linked through the course web page. The reading list is available at: http://courses.ischool.utexas.edu/unmil/2015/Spring/viz/readings-viz-2015sp.html
This course will enable you to:
- evaluate the conceptual, metaphorical, visual, and interactive properties of visualizations
- evaluate information properties of visualizations--facts vs. interpretation
- design visualizations that meet your desired visual and information properties
- assess available data and manipulate it for use by visualization software
- design and develop D3.js visualizations
- recommend visualization and data management software
10% - Class participation (individual - discussion points, class discussion)
10% - Visualization showcase (pair presentations)
30% - Assignments (individual, pair)
50% - Project (groups of 3-ish)
I have an open door policy. You are welcome to drop by my office (UTA 5.408). I will do my best to make time for you. To be sure that I will have time when you come by, please email me (email@example.com) to setup an appointment. I am also happy to meet outside of regular working hours and using videoconferencing tools to maximize availability. skype: unmil.karadkar, Google+: firstname.lastname@example.org (no email, videoconf only)
All students are expected to abide by the University of Texas Honor code, reproduced below for your convenience.
The core values of The University of Texas at Austin are learning, discovery, freedom, leadership, individual opportunity, and responsibility. Each member of the university is expected to these values through integrity, honesty, trust, fairness, and respect toward peers and community.
Violation of academic integrity, especially plagiarism, will not be tolerated. The first infraction will result in a grade of zero for that component of the course as well as a formal reprimand in your student file for future reference. Penalty for a second violation will include failure of the course and University-level disciplinary action.
The University of Texas at Austin provides upon request appropriate academic adjustments for qualified students with disabilities. For more information, contact the Services for Students with Disabilities (SSD) at (512) 471-6259 (voice) or (512)-410-6644 (video phone). An official letter from SSD is required in order to avail academic accommodations.
Please notify me as quickly as possible if the material being presented in class is not accessible (for example, instructional videos need captioning, course packets are not readable for proper alternative text conversion, etc.).
Please see details in the files section.
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