Project 2 Guidelines


For this project, you will create a new dataset. You may choose to analyze your own data, aka quantified self or create a dataset from a topic or area you are interested in, quantifying the world around you.

First, you will collect data about an aspect of your life, and then create a visualization from that data. You could make a completely new dataset over the course of a day or a week (ex: how many times you check your phone, the number of times you enter or exit a building) or curate a new one from your digital (or analogue) footprint (ex: your email data, your location data) or count the number of squirrels who pass your window over a day.

This project will require you to engage with the full “data life cycle”: you will turn a general curiosity into an engaging research question; identify the variables necessary to answer that question; design the data structure and collection methodology; assemble your data set; analyze your data set through visualization; and finally, communicate your findings as a blog.

Additionally, your data set is poised to have significant personal context and qualitative value. In the past 10 years (basically since the advent of “wearables”), this type of quantified self has gained prominence and stirred significant debate. This project is designed to speak to that movement while giving you the opportunity to get creative about what aspect of your “self” or the world around you to quantify.

By the end of this project, you will be able to:

– Design and create a data set from scratch

– Identify and utilize quantitative proxies for qualitative behavior

– Engage with the full “data life cycle”

PART I: Project Proposal

See syllabus for due date  (10%)

Your proposal should outline these four dimensions:

  1. A research question. Your research question can take the shape of a question, topic, or title, but it must be coherent and addressable by this data set and through a visualization. Your research question will develop as you work with the data set. For example, your project may start with “How often do I look at my phone in a day” and expand into “What times of day do I look at my phone the most?”, “Is there a relationship between task or location and phone use?”
  2. Your audience. Who would benefit from an answer to your research question? Are you the primary audience for your work, or are you anticipating interest from a broader audience? You can give narrative context or a very direct statement of what is at stake. For example, “I use my phone nearly all of the time: I am a cyborg. This project explores the nature of my phone usage, and analyzes when and why I reach for the device.” Invariably, this project speaks to a larger audience as your individual experience is symbolic in some way of the larger human experience.
  3. The data you will use to address your question. You must include how you collected (or plan to collect) your data. You are welcome to collect new data, or use existing data from an activity tracker, meal planner, calendar, email, text messages, historical data about yourself, etc. For this section, you must clearly articulate what the data is, how it was or will be collected, what are the parameters on the data (category, time frame, what “counts” and what doesn’t).
  4. A sketch of how you plan to visualize your data. The sketch must be visual, preferably hand drawn. Label your axes and indicate if it’s a bar chart, line graph, scatter plot, tree map, etc. Critically consider if your sketch represents the data logically and if it addresses your question/topic. If you’d prefer, you may create the sketch on a computer in a program such as Gimp. However, this sketch should not be a computer generated graph (don’t make your sketches in Tableau or Excel). Attach a picture of this sketch to your email.

If you have any questions about your proposal, please reach out ASAP. If your project needs revisions, you will not need to submit a revised proposal. However, if there are major changes, I may ask to schedule a discussion to help reframe your project.

PART II: Visualization and Blog Post

See syllabus for due date  (75%)

You will publish a blog post on your CUNY Academic Commons Site that includes the following components. The written component should be approximately 300-800 words.

  1. Your research question. Your research question may have evolved or completely changed since you submitted your proposal – that’s ok. However, your blog post description and analysis must reflect the question or topic you have addressed in this version of your visualization. Motivate this question. Why does this question matter? Where are you drawing inspiration from? What got you curious about this question?
  2. Your audience. Describe the audience this visualization aims to serve.
  3. A written description of your visualization. Explain your visualization in terms that a data novice would understand. In one sentence to one paragraph, what conclusion should I draw from your visualization?
  4. Your embedded visualizations. Your visualizations or dashboard should be published on your Tableau Public Profile and embedded in your blog post. It should retain the interactive functionality you built in Tableau (do NOT just put in images or screenshots).  Here’s the link to embedding. If your visuals are difficult to see on the commons, please ALSO include a link to your Tableau Public site. If you have fewer than 3 visuals, try to explore another dimension of the data.
  5. An explanation of the data and design decisions you made. This section should illustrate what you did and why you did it. Why did you choose the type of chart/graph/visualization that you did? How does that choice best represent the data and address your question? Through this explanation, you will illustrate that the decisions you made were intentional and how they contribute to the project. You should also explain any limitations you encountered and any subsequent compromises you made with the data or your design.
  6. Next steps. Finally, explain where you could take this project in the future. What would the immediate and more complex next steps look like? What improvements, developments, or alterations in scope would you make?


See syllabus for due date (15%)

The final component of this project is a pin up and critique. Everyone will have the opportunity to receive thoughtful feedback about their work and offer the same to their peers. You must be present in class for the critique. Since critique is essential but ephemeral, if you have extenuating circumstances that prohibit you from attending a synchronous Zoom class, you must make advance arrangements.

Some questions to help shape feedback:

  • Does the data address the question?
  • Does the visualization address the question?
  • Does the visualization fit the data?
  • Who is the intended audience of this visualization?
  • Was the author successful in depicting the relationships in the data?
  • Is the output informative and honest?
  • Where could a consumer misinterpret the data?

Some notes

You can use as many or as few visuals to address your question/topic as you wish and as you feel is appropriate. You can continue to iterate on your project until you are satisfied, but the first version must be completed by Monday 1 hour before class. If you have major revisions after the critique, you may submit your project for reassessment.

Finally, the end product (from the website to the visualizations) should be reflective of you and your style. The objective is that you will have a portfolio of work at the end of the semester that illustrates your visualization skills. If you already have a portfolio or a personal site, talk to us about how to incorporate the two.


Part I (10%)

10/10 for submitting on time and addressing all the components

Part II (75%)

  • Appropriate choice of visualizations(20)
    • The visualization types address the research question
    • Each graph or chart represents the data truthfully and logically
  • Effective communication (20)
    • Intended message is communicated clearly
    • Data is accurately represented without distortion
  • Design and aesthetics (20)
    • All elements and features of the visualization have a communicative function
    • The visualization has a thoughtful layout and an intentional design
    • Title, headings, labels create helpful context and have appropriate sizes, locations, spellings
  • Content of blog post (15)
    • The blog provides helpful context that makes the visualization more understandable and approachable
    • The writing provides the reader an inside look into the visualization’s intent and creation process
    • All components of blog post are addressed
    • Decisions are in line with good visualization practices (see Data Points and Storytelling with Data)

Part III (15%)

15/15 for actively participating in the pinup. This includes sincerely listening to the feedback from the class as well generously offering your best ideas for improving the work of your peers.