This page is an archive. Visit Data visualization - Winter 2017

Data Visualization - Winter 2016

Exercise 1 - Etch a sketch

Develop a compelling story about the given data set and then design a visualization to accomplish it. Your design choices must have a rationale.

  • Data - README, olympics.csv, olympics.json
  • Report - Up to 2 pages. Describe your visualization and the story. Your story may emphasize one of the many aspects for the data, mention which data was left out due to design or story. In the description include design choices of visual elements and data transformation or sorting. How do these decisions facilitate effective communication? Refer to report format
  • Tools - Paper/pen. No coding or vis application should be used for this exercise
  • Due Date - In class

Exercise 2 - Create a visualization

Develop visualization for a given data.

  • Data - README, olympics.csv, olympics.json You may augment the data to include additional information such as GDP, Population, etc.
  • Report - Up to 2 pages (anything beyond two pages will not be graded). Describe your visualization. The description must include the problem that your visualization is attempting to solve, the choice of visual elements and interaction. See report format
  • Tools - D3JS is recommended. However, you may use any programming language or software application for this exercise.
  • Due Date - 1am PT, Jan 22, 2015 Refer to submission instructions

Exercise 3 - Apply color maps

Apply different color maps to your visualization solution for exercise #2

  • Note: If your exercise 2 solution does not use color in significant way, you may create a new visualization for exercise 2 data using any tool like d3js, Tableau, etc then perform the following tasks.
  • Task 1 - Apply different colormaps for your visualization from Exercise #2
  • Task 2 - Take screenshots of your original visualization from Exercise #2. Test them for color deficiency using one of the websites provided here. Rectify any problems encountered by changing colormap.
  • Report - Up to 3 pages. Discuss how colormap changes affect the effectiveness of visualization. Use side by side (or up and down) images of before and after in the report. Interactivity is optional. Use multiple images as necessary. Refer to report format
  • Code not required for submission.
  • Tools - D3JS is recommended, or other tools you used for exercise#2
  • Due Date - Feb 5th, 1am PT Refer to submission instructions

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 2 pages. 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 5th, 1am PT Refer to submission instructions

Exercise 5 - Fix a graphic/visualization

Select at least two visualizations from different categories from the given list. Identify any problems, then recreate the visualization to fix them.

  • List of graphic / visualization
  • Report - One page per visualization. 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. Refer to report format
  • Tool - Use any tool you like, even MS Excel.
  • Code not required for submission.
  • Due Date - Feb 19th, 1am PT Refer to submission instructions

Exercise 6 - Case Study

Identify and analyze two existing visualizations. Present them to the class, discussing its design, utility key strenghts and weakness. Alternatively present a published research paper (not a blog) or a book chapter on visualization. Refer to chapter 15 in the textbook for how to deconstruct the visualization and present it as case study.

Presentation

  • 10 mins (Presentation) + 5min (QA/discussion). Time limit will be enforced
  • Presentation will be graded
  • Single laptop will be used for presentation

Submission

  • Slide format: Powerpoint (avoid animations) or PDF document.
  • 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.
  • Due Date - Feb 19th, 1am PT

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 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.

Exercise 8 - Visualization design survey

Design multiple visualizations templates for given set of data attributes

Final project proposal

Develop and formally present your proposal for the final project. The goal of the final project is to create/develop compelling visualization solution for a non trivial data set. Following items should be considered for choosing the project

  • Dataset: Identify an open and publicly available dataset that will be used for the project.
  • Tasks: Specify five tasks that you intend to address with visualization.
    • What problem are you trying to solve for the chosen data?
    • Is visualization meant for data exploration, hypothesis confirmation or presentation?
    • What data transformation needs to be undertaken to work with the data?
    • What are the use case scenarios?
  • How: How will the visualization solution be implemented?
    • You may include sketches or concept diagrams.
    • Programming dominant - The solution will be implemented using some library for e.g bokeh, d3js, etc.
    • Application dominant - The solution will use a visualization application for e.g. Tableau, VisIt, etc. Some scripting may be done for data translation, etc. Since this work will likely take less effort than programming dominant solution. You must do an extensive literature survey for related class of problems and include that in your report and presentation.

  • Who: Who are the stake holders (for e.g. public or analysts)

  • Students are highly encouraged to do the project solo. However, in exceptional case focusing on challenging and substantial problem a team of up to 2 members with with clear division of responsibilities may propose the project.
  • Final proposal submission
    • Up to six slides/pages in PDF format (no exceptions). You may include sketches or concept diagrams in the submission document.
    • You will present your proposal in class. Up to 5 minutes for presentation , 2 minute for discussion and change to next student.
    • Presentation will be graded based on requirements above.
    • Presentation order - Randomly generated
  • Due Date - Feb 5th, 1 am PT.

Final project

Final projects will be presented to the entire class. Each presentation will be followed by Q & A session

  • Presentation
    • 20 mins (Presentation) + 5min (QA/discussion). Time limit will be enforced
    • Presentation order
    • You may do a live demonstration (at your own risk) or use a video (up to 5 mins). Video is recommended, but not mandatory.
    • Video tutorial link will be posted here.
    • Presentation will be graded
    • Use your own laptop for presentation. Make sure to bring a display adapter for your laptop. HDMI adapter has worked well, but tf you plan to use something else, please check with Stacey Williams (staceyw@eng.ucsd.edu)
  • Submission
    • Due Date - Mar 18th, 1 am PT
    • Presentation slides
    • Demonstration video (optional)
    • Code - Include code for programming dominant solutions. Include Tableau / application file for application dominant solutions.
    • Data - Include data or reference / link to download the data in submission. If you are using a database backend, make it accessible for grading purpose.
    • Readme.txt - Explain how to run your code or application
    • Report for programing dominant projects must include the following sections
      • Report format
      • Page limits: 6 - 8 pages
      • Project title
      • Page break up for each section below are rought guidelines
      • Abstract (300 words, 0.5 page) - Summarize project goals, results and findings.
      • Introduction (0.5 page)- Provide a brief background and motivation for the project
      • Dataset (0.5 - 1 page)- Briefly describe the data and summarize its key attributes. Include description of significant preprocessing that was required for the project.
      • Tasks (0.5 - 1 page)- Describe the chosen tasks and the audience for the project
      • Solution (2 - 3 pages)
        • Visualization design - Describe and justify the design choices and idioms used to accomplish listed tasks
        • Implementation - Briefly summarize key aspects of the implementation
        • Usage - very briefly outline software usage
      • Results (2 - 3 pages)
        • Include key snapshots as appropriate. You may also refer the time in submitted video where appropriate.
        • Discuss the expressiveness and effectiveness of your solution
        • Discuss findings as well as key hurdles and challenges overcome
        • What are weakness in the solution and lessons learned?
        • How could work be refined if more time was available?
        • Bibliography (does not count against page limit)
    • Report for application dominant project must include the following sections
      • Report format
      • Page limits: 15 - 20 pages
      • Project title
      • Page break up for each section below are rough guidelines
      • Abstract (300 words, 0.5 page) - Summarize the project goals, results and findings.
      • Introduction (0.5 page - 1 page) - Provide a brief background background and motivation for the project
      • Dataset (1 page) - Briefly describe the data and summarize its key attributes. Include description of significant preprocessing that was required for the project.
      • Tasks (2 pages)- Describe the chosen tasks and the audience for the project
      • Related works (5-8 pages)
        • Comprehensive explanation of similar/related work to your project that is published literature. See good sources for literature survey above. Include image snapshots as appropriate.
        • Discussion of relevance of related literature survey to your project
      • Solution (3-4 pages)
        • Visualization design - Describe and justity the design choices and idioms used to accomplish listed tasks
        • Usage - Outline software usage
      • Results (3-4 pages)
        • Include key snapshots as appropriate. You may also refer the time in submitted video where appropriate.
        • Discuss the expressiveness and effectiveness of your solution
        • Discuss findings as well as key hurdles and challenges overcome
        • What are weakness in the solution and lessons learned?
        • How could work be refined if more time was available?
      • Bibliography (does not count against page limit)

Final project grading rubric

  • Programming Dominant
    • Visualization Design & Expressiveness 35%
    • Comprehensiveness/Task Completion & Effectiveness 25%
    • Interactivity 10%
    • Report 20%
    • Presentation 10%
  • Application Dominant
    • Visualization Design & Expressiveness 20%
    • Comprehensiveness/Task Completion & Effectiveness 20%
    • Report 50%
    • Presentation 10%

Report Format

  • 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
  • PDF (recommended) or Microsoft Word ONLY

Grading Rubric

  • 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.
  • 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
  • Bonus (up to 10%)
    • Outstanding submissions may receive up to 10% bonus, but late submissions are not eligible for bonus points.
  • Late submission (incurs 20% penalty per week, after deadline submission incurs 20% penalty)

Submission Instructions

  • All exercises submissions should be emailed to the TA (not to the instructor) before 1 am the morning of class.
  • Submissions should contain a folder of all files required to run your visualization in addition to a report in PDF format.
  • Submissions without the report will not be graded.
  • The structure of your submission should be as follows
    • HW1/
      • Report.pdf (for exercise 2, on 3rd page append a photograph of your exercise 1 - sketch)
      • Code/
        • readme.txt - explaining how to run your visualization (external dependencies, Python 2 vs. 3, etc.)
        • index.html (or vis.py)
        • data.csv
        • Other folders for scripts / code as needed

Class policy

  • Attendance mandatory
  • Must complete all exercises except one
  • Must complete final project