due Monday, September 29, at 8:30 AM
Put all of your solutions into one text file for your group. The file should be called, for instance:
p04g1.docx for project 4, group 1, and should be stored in the folder: /proj/gpproj14/p04g1/
Group 1 consists of:
p04g2.docx for project 4, group 2, and should be stored in the folder: /proj/gpproj14/p04g2/
Group 2 consists of:
p04g3.docx for project 4, group 3, and should be stored in the folder: /proj/gpproj14/p04g3/
Group 3 consists of:
p04g4.docx for project 4, group 4, and should be stored in the folder: /proj/gpproj14/p04g4/
Group 4 consists of:
p04g5.docx for project 4, group 5, and should be stored in the folder: /proj/gpproj14/p04g5/
Group 5 consists of:
This project is about visualizing data. It will give you some time to write ababout data visualization and to take a little break from coding.
1. Check out the website Many Eyes (sponsored by IBM). Find 4 (or more) separate plots on Many Eyes (please give links to each of these plots) that violate the concepts of effective data visualization that are discussed in the handouts from class (e.g., in Cleveland's book and Robbins's book, and in the paper "How to display data badly"). Write a paragraph about each plot, with a critique of what aspects of the plotting could be improved. Imagine, for instance, that you were going to correspond with the people who designed the plot, and give them guidance about how to make a more effective depiction of the data. (Your discussion of these 4 plots should be at least one single-spaced page in (say) 12 point Times font, for example... but more than 1 page is certainly allowed.) Each student should write about at least 1 plot.
2. Revisit the website Many Eyes (sponsored by IBM). Find 4 (or more) separate plots (again, with links to the plots) on Many Eyes that do an overall good job of effective data visualization. Justify the reasons why you think that the plots are effective. (Again, please write at least one page total, justifying the reasons that you think the plot is effective.) Each student should write about at least 1 plot.
3. Check out the website Information Is Beautiful. Find 4 (or more) separate plots on Information Is Beautiful (please give links to each of these plots) that violate the concepts of effective data visualization. Write a paragraph about each plot, with a critique of what aspects of the plotting could be improved. Imagine you were going to correspond with the people who designed the plot, and give them guidance about how to make a more effective depiction of the data. Your constructive criticism should be at least 1 page altogether.
4. The Wealth and Health of Nations is a fun depiction of data. On the other hand, as with many depictions of data, it violates some of the techniques of effective data display. Please write an explanation of which techniques of effective data display are violated. If you imagine you are writing a constructive criticism to the authors of this animation, please make suggestions for how the depiction of data (for the health and wealth, over the years displayed) could have been done more effectively. Please make sure your explanation is at least 1 page long.
5. Describe (at least!) 4 very significant ways that the poster winner "Congestion in the sky" (from the Data Expo 2009 poster competition results) could be significantly improved, using the concepts of effective data visualization. Write a constructive criticism (of at least 1 page) that gives suggestions for improvement on each aspect that you criticize.
6. For the other posters (do not use the winner, "Congestion in the sky", since it was discussed already in question 5), find a total of at least 4 significant ways that some of the other posters can be improved. You can analyze several different posters, that is OK. Your constructive critique should be at least 1 page.
7. Which of the posters in the Data Expo 2009 do you think should be the winner? Why? (It is OK if you choose the poster that actually won, or any of the other posters.) Thoroughly justify your answer, using the techniques of effective data visualization, to justify your answer, with an explanation that is at least 1 page long.
8., 9., 10. Imagine that you are going to enter the Data Expo 2009. Rather than having to organize your information into a poster, prepare 3 pages of analysis, exploring some aspects of the airline data set that are interesting to you, and which you think might be of broad interest to potential readers too. Your discussion and plots should be at least 3 pages long.