NEW 300/600 Dataviz Syllabus
The contents of this site, including the syllabus and schedule, are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. This is explained at the bottom of the syllabus.
Due to the rapidly evolving nature of the data visualization landscape, this syllabus is subject to change. I will do my best to inform you of significant changes as early in the class as possible.
Tuesday / Thursday 12:30 – 1:50 p.m.
Rooms: 252/253 CMR.
Duration: Feb. 21 – Mar. 23, 2017
Professor: Dan Pacheco, Chair of Journalism Innovation
Office: Newhouse 2, room 494 or Innovation Lab.
Phone: 303.465.5560 (texting is fine)
Office Hours: TBD, or by appointments requested and scheduled here: http://doodle.com/danpacheco.
Last Updated: Feb. 17, 2017
How to Contact Me
Feel free to reach out to me in email about anything you want to stay private, or via Twitter for anything public that you don’t mind others seeing. You can call me at the number above and it will forward to my cell phone, but it may go to voicemail if I’m not in speaking range or am otherwise tied up. I promise to get back to you within 24 hours about anything substantial that requires a response.
This course is about telling stories through numbers presented through graphics that can be explored by the viewer. In any given day we are bombarded with stories driven by numbers, from the number of deaths due to Ebola in West Africa to the number of votes cast for political candidates. But simply providing the facts in text, video or voice is sometimes not as effective as showing it visually through a chart, graph or map. Even better: if readers and viewers can dig through the data by clicking on visual elements, they are transformed from passive recipients of information to active researchers, learners and potentially even contributors.
- Provide an overview of common types of interactive visualizations and how they’re used in journalistic storytelling around the world.
- Develop practical skills around finding and presenting data in several types of visualizations, using different tools.
- Get comfortable working with numbers and make friends with math. It’s not your enemy!
- Provide basic understanding of how web coding and data fit together to create interactive experiences.
By the end of this course, you should have a solid understanding of the following:
- Where to find public data, and what format and fields are typically required in order to present it in a visual way.
- How to clean up and normalize the data you find using Excel and Google Drive.
- How to analyze and “interview” data to uncover interesting stories.
- How to create different types of interactive visualizations (maps, sortable searchable tables, graphs, timelines and infographics) using online services.
What is this class not?
You will be working with code in this class. While I teach some basic code literacy, this is not a coding class. If your goal is to learn how to become a master coder you should consider many other more qualified 3-credit courses and programs offered elsewhere at Syracuse University.
While this class meets for only five weeks, the amount of work required for those five weeks is equivalent to one-third of the work required in a full-semester class. The intensity during that five weeks is the same as it would be in a full-semester class, and if you fall behind it will be even harder to catch up due to the shorter duration of the course. Be careful not to assume that because this class meets for five weeks that it is only one-third of the work of your other courses. You should expect to spend at least 6 hours each week outside of class doing reading, practice exercises, homework or projects related to the course.
- A Mac or Windows laptop with the latest Chrome or Firefox browser.
- A Google account
- A Twitter account
- A CartoDB account (free, academic upgrade also available)
Software We’ll Be Using:
- Blogging: WordPress
- Text Editing: SublimeText or TextWrangler
- Microsoft Excel
- Google Drive spreadsheets
Attendance and Attitude
This course depends heavily on class participation. For this reason, you are expected to attend every class on time. If you cannot attend, you must notify me in advance via email and provide an explanation. One absence will be granted for any reason with no explanation. Each subsequent absence with an acceptable explanation will result in a half letter-grade reduction in your final grade (for example, and A becomes an A-, and a C- becomes a D+).
Please show respect for each other as well as for the instructor. Disagreements and spirited debate about concepts are acceptable and welcome. Personal attacks of any nature are not.
While there is no textbook for this course, there will be a series of short readings (usually articles or short essays) or videos that are assigned during class. You can find additional readings in a Data Visualization group I have created on Diigo.com at this URL: https://groups.diigo.com/group/new300dataviz. (And a little hint for those of you who like to get ahead of the game: some of the assigned readings are already in this list!)
At minimum, I expect you to regularly peruse the following news sites that typically produce data visualizations:
- The Upshot from The New York Times: http://www.nytimes.com/upshot
- Nate Silver’s Fivethirtyeight.com: http://fivethirtyeight.com/
- The Guardian’s Data Blog:http://www.theguardian.com/news/datablog
- Vox Media: http://vox.com
- Twitter hashtags #datavis and #dataviz. People constantly share cool stuff there!
Share your own finds
When you find something interesting that will make for a good class discussion or exploration, post a link to it in Twitter using the hashtag #NHdata. You are required to share at least 5 finds (an average of one each week) as part of your grade. I will tally these up throughout the semester and incorporate them into your final grade. Note that if you post all 5 during the last week of class — meaning that you procrastinated — you will receive credit for only one during that period.
Note that anything you share in Twitter is public to the world, and will be out there forever. I also reserve the right to include your finds in a list of resources for future class participants.
The assignments for this class will all be done online using interactive tools that are specified in the assignment. In most cases will turn in your assignment by embedding your visualization along with a story that explains the data on the class blog at http://journovationsu.org.
How to Turn in Assignments
Assignments are posted and turned in using Blackboard (the ONLY thing we will use Blackboard for in this course).
I will go over how to turn in assigments in Blackboard during class. All you have to do to turn in an assignment is to post a link to your blog post. Please also make sure you do the following in the blog post itself:
- Enter the assignment number and title in the title field. For example: Assignment 1 – Introduce Yourself.
- Check the Turned-In Assignments category (not Assignments) before publishing.
- Type your name at the beginning of the subject line of the post. While your user name will appear, sometimes it’s necessary for me to edit your post, which changes the user name. I want to make sure it’s clear who the author is, and that you get proper credit for your work.
- Put your name in as a tag. This makes it easier to search for your assignment, again to make sure you get credit.
Syracuse University students now have free access to online classes and tutorials from Lynda.com. Many of these courses are about technical skills that can be directly applied to your work in this course. I have posted a few relevant courses in the class Blackboard site. You are required to take at least one Lynda.com course on your own time and write a blog post about what you learned, ideally also creating a new data visualization or making one of your assignments better through what you learned in the Lynda course you pick. You must post a link into this blog post into the Lynda.com Requirement assignment in Blackboard.
As part of additional class work requirements, you will be required to either launch your own site where you publish your visualizations and stories after receiving feedback from me, or get them published in another online medium – for example, TheNewshouse.com or The Daily Orange web site. I will provide training outside of class on how to set up a WordPress site for those who are interested (this training is available for everyone, not just graduate students).
The grading scale for assignments and final grade is as follow:
I will make every effort to post grades online through Blackboard, or by email if there are Blackboard issues, within one week of assignments being turned in. Assignments that require testing in a VR headset may take longer for obvious reasons. I require a 24-hour waiting period before discussing any posted grade. This is to give us both a chance to think rationally about the assignment and grade so that we can have a meaningful discussion.
Your overall class grade will be calculated based on a point system, with 200 total points possible in the class. The breakdown is as follows:
- 40% Assignments: 80 points possible from 8 assignments, worth 10 points each.
- 40% Final Project: 80 points possible.
- 10% Professionalism and classwork: 20 points possible. Includes attendance, sharing finds, class participation and quizzes.
- 10% Lynda.com Requirement: 20 points possible.
Policy for Late Work
In the professional world, you never get credit for something that is submitted late without a prior discussion and agreement on a different deadline. This means anything you submit late without a discussion with me in advance will get an F grade.
In what circumstances would I accept late work? Only for those that would fly in the business world, and for which you can provide evidence. These are usually “Act of God” types of issues. For example, if you get hit by a car and are in the hospital, I will understand and we can work something out, but I may ask to see something from the hospital. I reserve the right to reduce the score for an assignment by a half-letter grade for each day it is submitted late, even if you have an excuse.
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Use of Student Work
The professor may use academic work that you complete this semester for educational purposes in this course during this semester. Your registration and continued enrollment constitute your permission.
The professor may use academic work that you complete this semester in subsequent semesters for educational purposes with your permission. Before using your work for that purpose, your professor is required to either get your written permission or render the work anonymous by removing all your personal identification.
You can find the entire class schedule, including all assignments, on this site here.
The entire contents of this site, including the syllabus and schedule and any homework assignments or projects that you post to the class site, are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. That means you are free to use what you find here elsewhere for non-commercial uses as long as you provide attribution, and others who use the content do the same and also share their modifications under this same license. If you do not want your classwork to be Creative Commons licensed, please talk to me about other ways to turn in your work.