Data Visualization - Winter 2021

Submission instructions | Report format | Grading rubric

Exercise 1 - Create a visualization

Develop visualization for a given data.

  • Data - README, olympics.csv, olympics.json
  • Sample motivation: Explore dominance of winning countries over time, per gender and sport type. You may pick other driving motivation for your project, but these must be non trivial. For example, a trivial example is a single visualization showing aggregated medals won by each country.
  • Report (See report format) - Up to 2 pages for individual work and up to 3 pages for group work (additional pages won’t be graded). Describe your visualization. The description may include the motivation for your visualization, and must include which tasks it intends to accomplish. Explain the choice of visual elements and interaction and discuss the expressiveness and effectiveness of your visualization. Note any omitted or supplemental data in the report.
  • Tools - D3JS is strongly recommended. However, you may use any programming toolkit/language for this exercise.
  • Due Date - Jan 23, 1am PT Refer to submission instructions

Exercise 2 - Apply color maps

Apply different color maps to your visualization solution for exercise #1

  • Note: If your exercise 1 solution does not use color in significant way, you must create a new visualization for exercise 1 data using any tool like d3js, Tableau, etc then perform the following tasks.
  • Task 1 - Apply different colormaps for your visualization from Exercise #1
  • Task 2 - Take screenshots of your original visualization from Exercise #1. Test them for three common color deficiencies using one of the websites provided here. Rectify any problems encountered by changing colormap.
    • Note: If your original visualization has a single color or simple line plots, create a visualization in Tableau with color and test it for color deficieny
  • Report - Up to 2 pages for individual work and up to 3 pages for group work (additional pages won’t be graded). Discuss how colormap changes affect the effectiveness of visualization. Use side by side (or up and down) images of before and after color deficiency correction in the report. Use multiple images as necessary. Refer to report format
  • Code not required for submission.
  • Due Date - Feb 6, 1am PT Refer to submission instructions

Exercise 3 - Create a visualization

Develop visualization for a given data.

Exercise 4 - Visualize a Network

Create a visualization of the provided sheep data. You may create either an adjacency matrix visualization, or a node-link visualization.

  • Data - sheep_data.zip, sheep_ml.graphml
  • Tools - Python NetworkX reccomended, D3 force layout may also be used (for node-link visualization).
  • Report - Up to 3 pages (anything beyond three pages will not be graded). Discuss the expressiveness and effectiveness of your chosen visual idiom. Describe any findings that can be identified or learned from the visualization. See report format
  • Notes - The edge weights are non-symmetric, meaning that the network has directed edges. You are NOT required to visualize the weights on both directions of each edge as this can get very complicated (specifically with node-link visualizations). You are allowed to simply pick one value for each edge.
  • Grading - Since implementing interativity with NetworkX solutions is a significant challenge, for NetworkX solutions without interactivity, interactivity points will be awarded in one of two ways:
    • If the data is augmented (i.e. extra properties of the data are computed and used for visualization) the interactivity portion of the grade will be assigned to the expressiveness and effectiveness of the visualization of this augmentation (please also discuss the augmentation in your report).
    • Otherwise, the interactivity points will be evenly split between the effectiveness and report sections (making them 40% and 30% respectively). This means if you choose not to use interactivity or augmentation, please put extra attention into your report and the justification of the effectiveness of the choices you made in your visualization.
  • Due Date - Feb 20th, 1am PT Refer to submission instructions

Exercise 5 - Case Study

Present a research paper (not a blog) or a book chapter (not from course textbooks) on visualization. (Recommended). ** Do not choose papers from machine learning that are not solely focussed on visualization. ** Paper/Book Chaper section below provides several resource to pick research papers.

OR

Identify and analyze two existing visualizations. Present them to the class, discussing their design in terms or expressiveness and effectiveness, utility, key strenghts and weakness. Refer to chapter 15 in the textbook for how to deconstruct the visualization and present it as case study. ** A list of visualization is provided below

Note: Indicate your case study or visualization selection on this spreadsheet. Do not choose anything that has been already taken by others.

Presentation

  • 10 mins (Presentation) + 5min (QA/discussion). Time limit will be enforced
  • Presentation will be graded
  • Use your own laptop for presentation (Bring HDMI or VGA adaptor for your laptop)
  • Presentation order will be randomly generated and will be noted TBD

Submission

  • Slide format: Powerpoint (No report)
  • Title slide: Include Visualization(s)/paper title with links and your name.
  • Make the slides self contained such that if the web link does not work you could still present.
  • Polls - each student must complete this poll independently
  • Due Date - Feb 20th, 1am PT

Below are a list of sample ideas, although you are not constrained to select from this list. You may pick other visualizations that represent sufficiently complex data. Please avoid choosing trivial visualizations, email us well in advance of deadline if you have any questions on eligibility of your visualization choice for the case study.

Exercise 6 - Fix a graphic/visualization Cancelled no need to submit

Select two visualizations one from each category from the given list. Identify any problems, then recreate the visualization to fix them.

  • List of graphic / visualization
  • Report - One page per visualization (anything beyond one page per visualization will not be graded). Describe the problem in chosen graphic and how your solution fixes it. Discuss the expressiveness and effectiveness of your solution. Include side-by-side image of chosen vs your visualization. Interactivity is optional as no code/application file will be submitted. Refer to report format
  • Tool - Use any tool you like, even MS Excel.
  • Code not required for submission.-
  • Due Date - Mar 6, 1am PT Refer to submission instructions Cancelled no need to submit

Exercise 7 - Geospatial and Temporal Visualization

Create a visualization to explore the incidents of West Nile Virus across geography (California counties) and time (2006-2015). Discuss the expressiveness and effectiveness of your visualization based on design choices. Identify and report any conclusions drawn about the spread of the virus from your visualization.

Report Format

  • Must be written in third person narrative style
  • Letter size page 8 1⁄2 in × 11 in
  • One inch margin on all sides
  • Font: Times New Roman, size 11pt or 12 pt, you may use larger font size up to 14pt for headings.
  • Include your name in header section
  • Title in form: “Exercise NN Report: Brief title for the visualization”
  • PDF (recommended) or Microsoft Word ONLY
  • For ‘Create a visualization’ exercises the following sections would be appropriate in the report
    • Motivation
    • Data augmentation (if any)
    • Tasks
    • Expressiveness of design
    • Effectiveness of the solution
    • Interaction
    • Conclusions

Exercise Grading Rubric

All exercises are graded on scale of 10 points.

  • Expressiveness of design (30%)
    • Match between choices of visual encodings with properties of data.
    • Choice of encodings based on the importance of the data.
    • How well the design expresses facts?
  • Effectiveness of the solution (30%)
    • Does the solution communicate and support the intended idea?
    • Are the encodings used perceptually effective?
    • Is the data used comprehensively or augmented?
  • Interaction support in solution (20%)
    • Does the solution support comparison, selection, filtering, linking, etc? For non programmatic solutions this weight is added to expressiveness and effectiveness
  • Report (20%)
    • Does the report provide motivation for the visualization?
    • Is there a clear description of the problem/tasks your visualization is attempting to solve?
    • Is the choice of visual encodings explained and justified in terms of expressiveness of dataset attributes? Refer Chapter 5.4.1 in Munzner
    • Is the choice of visual encoding explained and justified in terms of effectiveness of channels? Refer Chapter 5.4.1 in Munzner
    • Finally, does the visualization accomplish solving the problem or tasks that were identified?
    • Sample report 1 and Sample report 2 Note: The sample reports are provided merely reference, they should not be used as template for your reports. Do not include improvements section in your report.
  • Bonus (up to 10%)
    • Outstanding submissions may receive up to 10% bonus. Late submissions are not eligible for bonus points.
  • Late submission Incurs 20% penalty after the deadline, there after additional 20% penalty per week. Final project must be submitted by deadline (no exceptions).

Submission Instructions

  • All submissions must be made to the DSE Data Cloud. In case of Group Submissions, just one of you need to submit the exercise, submission should clearly note names of all group members.

    • Submission setup

    • Your accounts have been created with username as your email prefix and emails ending in @ucsd.edu. For example if your email is xyz@ucsd.edu your username is xyz
    • Reset your account password at https://dse.seedmelab.net/user/password
    • Upon login, visit the Data (Links to an external site.) page > Open the ‘Shared’ tab in left side bar
    • Open the folder named “dse241-Your-Name”
    • Submit your assignment as zipped file in corresponding ‘exercise-1’, ‘exercise-2’ …. folders
  • All students must independently respond to Polls corresponding to the exercise
  • Submission must include report in report format with content noted in grading rubric
  • Submission must include a readme file with relevant instructions to run your visualization with all the required files and data.
  • All exercises submissions are due on 1 am on the day of class.
  • Submission shall be well organized structure as follows. (Do not zip the folder)
  • Not following the submission format will result in 5% deduction of acheived exercise score after two infringments. This includes missing readme file, non working code. 
    exercise-N-firstname-lastname
  report.pdf
  index.html
  css/
    style.css
    ...
  data/
    data.json
    ...
  img/
    logo.png
    ...
  js/
    script.js
    ...
  other-folders-as-needed/
    ...
  • Report must be in PDF format and include items noted in the grading rubric above. Submissions without the report will not be graded.