Final Project

Deadline Timeline

Note: Deadlines are at 1pm on the day listed

• Monday, 10/10/16 Project out
• Friday, 10/28/16 Project Proposal DUE (email to nad@umd.edu)
• Monday, 11/21/16 Project Progress Report Presentation DUE (in class presentation)
• Monday, 12/12/15 Final Project Presentation DUE (in class presentation)
• Friday, 12/16/15 Final Project Report DUE (email to nad@umd.edu)

Project Description

Your final data visualization project should show that you have integrated the knowledge you acquire in this class and are able to apply it in the design and implementation of a data visualization story package. You’ll do this project with a partner which will be assigned (details below).

The theme for your visualizations this year is Urban Data in the US, such as around public data available in Washington, DC, Baltimore, or some other sizable U.S. city where you are able to obtain data. For some inspiration you could see the types of visualizations published on Cityvis.io. Your story does not have to include a map, but it could. It could be a lot of things as long as it has something to do with cities. You should be sure to research the context of your specific issue and really tell a story that informs the public about a city issue you are focused on. Imagine that your project could be published on a local newspaper website and be useful, insightful, or informative for the community there.

To start, you’ll need to find a dataset or datasets that are interesting and which you think will provide a fertile bed for an interesting or even newsworthy visualization-based story. Finding data can be very time consuming, so please start on this as soon as possible; there are many sources of data online that you might find or collect. Many major cities maintain open data portals, e.g. in Washington, DC, New York City, Baltimore, Chicago. Maybe you find data that speaks to issues of transportation (bikes, metro, taxis, buses etc.), environment / pollution, real-estate (prices, licenses, commercial development etc.), or city services. Be sure to be oriented towards data that might have some news value, and that is recent (e.g. from the last few years). Also, remember that after analyzing a dataset you might have additional questions and need to go back and find other datasets to flesh out your story and make it multidimensional and rich. For instance, you might find that you need to integrate Census data to normalize by population densities.

The data you find may need to be cleaned and wrangled into a shape before you can really start working with it; you might want to read up more on data wrangling or review the lecture slides on data again. Once you’ve settled on a dataset that you find interesting you should spend some time understanding the variables in that dataset. Each dataset is different and some of them have special terminology that you may need to research in order to understand. What do the variables mean? How were they measured or collected? Are there limitations or gaps in the data would constrain your use or interpretations? You need to fully understand your dataset before you can build a presentation to help other people understand it easily.

Then you’ll do some exploratory visualization (which you've practiced with Tableau in assignment #1) to find some potential angles or interesting observations about the data. How can you connect your findings into a narrative? You can begin to sketch out ideas for how you want to present the data and visualization as part of a broader story. You will design visualizations, mappings, colors, interactions, and an information layout that ties everything together. What’s the story that you want to tell with this data? How can you help end users experience that story and understand what you’re communicating? Depending on the data types in your data set will you use charts, timelines, maps, network diagrams, or something else entirely?

Finally you’ll implement your designs in HTML, CSS, and javascript. We’ve been learning Vega-Lite in the course however using it in the final project is not mandatory. You could use other charting libraries such as HighCharts, Plotly.js, Google Charts, or another other tools that you want to use to get the job done.

Project Team
You will be assigned a partner to work with on the final project. Please contact your partner ASAP to set up a time to meet. Here are the teams. If you need contact information for your partner let the professor know (or check any of the emails sent to the whole class).

Project Proposal
Your project proposal will succinctly describe (~500 words) what you intend to visualize and why that is an interesting and potentially newsworthy story. You should have already spent time collecting some data and doing some preliminary exploratory analysis. In the proposal write-up include information about the data you have acquired, what the data describes, where you got it, how you processed or cleaned it, and any limitations you have identified. Does the data speak to the kinds of questions you want to answer? Also describe what you think the story might be based on your initial exploratory visualization and analysis or other reporting and research you have undertaken. Include sketches or early mockups that show how you are conceptualizing the story and its presentation. Also look ahead and describe any challenges you foresee in how you will implement your ideas.

You should email a PDF to nad@umd.edu with a file name of "Final_Project_Proposal_<project_title>.pdf" by the deadline listed above.

Project Progress Report Presentation
In order to help assess the strengths and weaknesses of your project you will have ~15 minutes (10 minutes of presentation and 5 minutes for questions and feedback) to present your project to the class on the date listed above. This presentation will give you a chance to both receive feedback from other class members as well as to offer your own critiques of their work. You should have some aspects of your visualization project implemented and you can use this time to demo what you have, explain the intent of the project, the design process or storyboards, and the emerging story. Make sure to describe and motivate your project for the class, and describe what you have left to work on, as well as if there anything you need help with.

Final Project Presentation
Final project presentations of 15 minutes (again 10 minutes for presentation and 5 minutes for feedback) will be made in class on the date listed above. This should be the buffed up and polished version of the progress report presentation you gave previously. Make sure to motivate the project, explain the data you used, how you visualized it and implemented it, and what the story is. This will be an open “public” session with invited guests from the college. For all intents and purposes your project should be done by now.

Project Report
Your project report is due via email to nad@umd.edu as a PDF with file name “Final_Project_<project_title>.pdf” by the date listed above. Also include a .zip file of your project's code so that it can be loaded and viewed (if you have a server where you are hosting the project please also include a link). In addition to the information that you presented in your final project proposal and final project presentation, please also describe and reflect on your project, in particularly the tools you used to implement the project. Why did you decide to design the visualizations the way you did? What was hard or easy about the project? What would you do differently next time? Importantly, be sure to describe in some detail the work that each team member did and how it was broken out.