CMSC 23900: Data Visualization

Piazza sign-up, Q&A

Instructor: Gordon Kindlmann
TAs: Andrew McNutt, Kai Li

Lectures:
Tues & Thu
12:30-1:50pm,
Ryerson 251
Labs:
Mon 1:30-2:50pm
or 3-4:20pm,
CSIL

Class Description

Data visualizations provide a visual setting in which to explore, understand, and explain data sets. This class describes mathematical and perceptual principles, methods, and applications of "data visualization" (as it is popularly understood to refer to primarily to tabulated data). A range of data types and visual encodings will be presented and evaluated. Visualizations will be primarily web-based, using D3.js, and possibly other higher-level languages and libraries.
Prerequisites: One of CMSC 12200, CMSC 15200 or CMSC 16200.

People

Instructor Gordon Kindlmann
Office hours (Ryerson 161-B): Mon 10am-11am, Thur 2:30pm-3:30pm
TA Andrew McNutt
Office hours (CSIL 1): Wed 1:00-2:30pm
TA Kai Li
Office hours (Ryerson 162): Wed 4:30-6:00pm

Grading and Assignments

The following items determine the class grade, according to their percentages: All homeworks and Project 1 are at 10pm, so that you can get some sleep at night. See this week-by-week diagram of the expected assignment dates so that you can plan your quarter accordingly. Thoughtful class participation (such as asking and answering questions) may also influence your final letter grade.

Late Policy

Late work is not graded. However, throughout the quarter, you may get up to four 24-hour extensions (“late-chips”) on any of the assignments except Homework 1 and Project 2. Only one extension may be used per assignment (they may not be "stacked"). You request late-chips at work-groups.cs.uchicago.edu, but must do so before the original (non-extended) assignment deadline (even if work-groups.cs.uchicago.edu allows you to do do after the deadline). A late-chip for project 1 is applied to all group members. Exceptional circumstances may warrant additional consideration, at the instructor's discretion (post a private question in the per-assignment folder on Piazza). It is hard to be generous with a student panicking near the deadline about a situation that could have been anticipated earlier.

Communication and Resources

Academic Honesty

In this course, as in all your courses, you must adhere to the college-wide Academic Integrity & Student Conduct guidelines as set forth at http://college.uchicago.edu/policies-regulations/academic-integrity-student-conduct. The college’s rules have the final say in all cases. To paraphrase them:

  1. Never copy work from any other source and submit it as your own.
  2. Never allow your work to be copied.
  3. Never submit work identical to another student's.
  4. Document all collaboration.
  5. Cite your sources.
If you break any of these rules, you will face tough consequences. Specifically, any student who is determined to have participated in academic dishonesty will not be allowed to withdraw and will receive a course grade no higher than a C. You will also be reported to your adviser and may face further discipline as a result.

Please note that sharing your work publicly (such as posting it to the web) definitely breaks the second rule. With respect to the third rule, you may discuss the general strategy of how to solve a particular problem with another student (in which case, you must document it per the fourth rule), but you may not share your work directly, and when it comes time to sit down and start typing, you must do the work by yourself (or with your partner for that project). If you ever have any questions or concerns about honesty issues, raise them with your instructor, early.

(Thanks to Adam Shaw for this statement of academic honesty.)