M2 Information Design Project Instructions
- Gain a better understanding of document design and visualizations
- Write based on a specific purpose and audience
- Create appropriate visuals from numeric data
- Use visuals to support a specific point or argument
- Analyze visuals to integrate data into an argument
- Apply principles of design to create a visually appealing, readable document
This project asks you to engage with data, present data for a specific audience, and practice making effective data visualizations. The project focuses on the fair, accurate, and ethical use of data, the conventions of writing with numbers and data, how to integrate figures into a document, and how to design effective visualizations. Audience and purpose are central to the goal of the final deliverable. As you will learn in completing this project, numbers don’t speak for themselves, and writing with data requires critical and rhetorical thought, as well as visual design skills.
In working on this project, you will engage with different types of visuals, as well as the conventions of writing with data and numbers. To achieve these goals, you will select a data set work with from one of the resources listed below. You will decide on a point you want to make for a specific audience using your data. You will then make decisions about which data to visualize from the larger data set, create three data visualizations help you make your point, and craft that data into a final deliverable of one page that includes three visuals and the text necessary to explain their data and make your point. You also will compose a reflective memo that explains your choices and goals, and how the final deliverable achieves them.
In addition to your the textbook chapter on Visual Design, you may which to use this Periodic Table of Visualization Methods (Links to an external site.) to explore various types and uses of visuals.
Data visualizations bring a number of benefits to any professional document, even short ones:
- Though they have become extremely easy to make, people in the workplace still tend to be impressed by the extra effort and thoughtful presentation implicit in making a visualization.
- Data visualizations also help to make the work of digesting and interpreting data more efficient by displaying trends or illustrating the significance of specific information without poring over page after page of numbers.
- Because of this efficiency, visual elements are also better at communicating certain ideas more quickly than words or tabular data. Something that may take many sentences to communicate, a sudden drop in the efficiency of a process, or a surge in sales among a certain demographic, are instantly recognizable as spikes or dips along the X axis of a line graph.
This short report from the Department of Education (Links to an external site.) provides an overview of literacy and numeracy for men and women. In this online short report, the authors created two bar charts that are designed to show relationships between data and then they briefly explain the importance of the data.
Infographics take advantage of the immediacy and efficiency of data visualizations and can be used to emphasize the main points of a written document, or stand on their own to advocate and inform. For example, this infographic about diversity in STEM fields (Links to an external site.) uses a handful of colorful data visualizations and a small amount of text to draw attention to specific deficits and disparities in specific workplaces. It’s also careful to note the sources of its information in case the reader would like a greater level of detail or information about how the data was collected.
Similar to the examples above, select a specific concept, issue, or topic related to your major or something that you are interested in researching. Locate and collect numerical data about the subject (in the form of studies, reports, spreadsheets, or articles), and select which data you feel provide the best overall sense of the subject. Keep a list of links to these sources for later. If you can’t find numerical data on your topic, pick a topic that is easier to research.
For this project, you will find a data set and create a short informational report that includes at least three data visualizations that you feel best communicates that data in a form that maximizes the impact of the data to suit a specific audience and purpose.
To help you find a data set, here’s a link to a list of websites that provide raw data sets on various topics:
19 Free Public Data Sets for Your First Data Science Project (Links to an external site.)
Find a data set you want to work with and spend some time with the data. Identify the trends that jump out at you as most significant. As you identify your audience, think about who would want to know about the data and the point you’d like to make.
Below are potential tools you can use to make your visual reports:
Those are all free but may require you to sign up. Of course, Adobe Photoshop, Excel, Word, etc. can all be used. The above are just extra resources and tools for those that want them. As always, questions, concerns, etc., feel free to email me or drop by during office hours!
A one-page, informative, visually interesting report that provides a broad overview of your subject. This report should incorporate at three types of visuals along with a discussion/analysis of the data in your figures. The text included should introduce the topic and its importance, explain the meaning of the visuals, and to point to the conclusions suggested by the data. You should think through and identify a clear audience. The analysis of the audience informs how the data is presented, the form the visualizations take, and the point you use the data to make, as well as the overall purpose of the document.
A short 250- to 500-word note that explains the following (use headings to identify each topic):
- How and why you selected your data set
- How you selected which data to visualize and why you visualized it in the form you did
- Who was your target audience and what was your overall goal/purpose
- How you ensured that your visualizations of the data were fair, accurate, and clear
- The raw data set used to create the report (with a citation for the data)
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