Data Essay assignment instructions
The goal of this assignment is to explore a dataset through a combination of data visualization and text. Your essay should be live on the web and designed and written for a non-specialized public audience. You may select your dataset, tools, and visualization types. You will submit the link to Moodle by Friday, March 28.
Your project should include:
- A bibliography with the data’s source and any secondary sources consulted. Citations should be detailed and consistent (i.e. Chicago, MLA, APA…) and should include hyperlinks.
- A title for your essay (and for any individual visualizations if relevant)
- One or more visualizations embedded as still images or interactive objects, with labels and keys.
- Approximately 300-500 words of text
Your essay should include:
- A narrative about this data: an interpretation of what the visualization(s) might show or suggest.
- An explanation (in your own words) of the dataset itself and how it was collected, along with any context you think is relevant for interpretation.
- An explanation of your choices in selecting tools, visualizations, a any additional cleaning work you performed.
- A description of any relevant limitations of the dataset, or the unanswered questions it raises.
Data options
You may choose any dataset, as long as it is well documented and you are able to glean sufficient context to inform your analysis. I recommend looking at the datasets featured in the Data is Plural podcast or Responsible Datasets in Context, or in the Introduction to Cultural Analytics in Python textbook.
Tool options
Here are some options I recommend:
- RawGraphs
- Voyant
- ArcGIS online (Map viewer)
- Python
- Microsoft Excel/Google Sheets
- Tableau Public
- Flourish
- Data Wrapper
- Adobe Illustrator
- D3 (Javascript library), R, or another programming tool
- Any of the tools in Hands-on Data Viz or other things you find
- Non-digital media, as long as you feature a scan or photograph in your essay
Resources
- Hands-On Data Visualization by Jack Dougherty & Ilya Ilyankou (2025)
- Introduction to Cultural Analytics in Pythonby Melanie Walsh (2021)
- The Pudding’s blog post series: “How to Make Dope Shit”, by Ilia Blinderman: Part 1: Working with Data, Part 2: Design, and Part 3: Storytelling
- Sample data essay repository: Data essay live and Data essay repo. You can fork this repository and use it for your template. Just make sure you deploy it as a website (see: deployment guide).
Rubric
| Category | Rubric | Value |
|---|---|---|
| Execution | Does the work follow assignment instructions and include all required features? | 25% |
| Insight | Does the written description demonstrate critical thinking and cogent analysis of the dataset? Does the overall project offer a substantive engagement with the material? | 25% |
| Presentation | Do the visualization and essay communicate ideas effectively to a general audience? Are labels and keys present and helpful in understanding the data story? Do design choices serve the content? | 25% |
| Effort | Does the project show strong effort, including one or more of the following: evidence of skill-building beyond what has been covered in class, customization or use of an advanced tool, additional effort put into research or data work, or advanced creativity in design and visualization? | 25% |