Project 1 Guidelines


For this project, you will visualize 311 Complaint Data from the New York City Open Data Portal. You will formulate a research question that can be addressed through the data and identify the audience who would benefit from your research. For example, your investigation might enable a community group to prioritize its efforts, or help individuals decide where to live. Be creative and think about who you want to serve with your work.

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

  • Access, explore, and leverage a public data source
  • Formulate a research question that a specific data set can address
  • Build a thoughtful and accurate visualization using Tableau
  • Contextualize the process and scope of your work in a blog post
  • Publish your blog post with your embedded visualization using the CUNY Academic Commons.

PART I: Project Proposal

See syllabus for due date  (10%)

Your proposal should outline these four dimensions:

  1. Your research question. Your research question can take the shape of a question, topic, or title, but it must be answerable 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 “What month has the most heating complaints?” and then expand into “What year(s) had the most heating complaints, and what buildings are repeat offenders?” Include your motivation for the question. Why do heating complaints matter? What can we infer from the answer to this question?
  2. Your audience. Who would benefit from an answer to your research question? Why does this question matter to them? You can give narrative context or a very direct statement of what is at stake. For example, “Understanding heating complaints is important to the Department of Public Health. By better understanding when heating complaints peak, they can better direct resources to assist those who are at the highest risk.” As you begin to design your visualization, consider what functionality (such as filters or tooltips) would benefit this audience the most.
  3. The data you will use to address your question. You must include the source and a brief description of the variables available in the data set that will be useful for your investigation. For example, “Heating complaints made in all five boroughs, organized by date from 2010 to present.”
  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 visualizations. Explain your visualizations 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 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. You will have the opportunity to receive thoughtful feedback about your work and offer the same to your peers. You must be present in class (synchronous, online) for the critique. Since critique is essential but ephemeral, if you have extenuating circumstances that prohibit you from attending a synchronous 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 visuals to address your question/topic as you wish and as you feel is appropriate, but please use at least 3. You can continue to iterate on your project until you are satisfied, but the first version must be completed by Monday 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.


Part I (10%)

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

Part II (75%)

  • Appropriate choice of visualization (20)
    • The visualization type addresses the research question
    • The choice of graph or chart represents the data truthfully
  • Effective Communication (20)
    • Intended message is communicated clearly
    • Data are 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.