Data+visualization

**Evaluation: 35% of final mark**
 * CCT470: Data Visualization**
 * Assigned: Details to be posted on or before October 20th**
 * Due: November 24th (to be submitted by December 1st at noon) **
 * Team Size: Select a partner (recommended, but working alone is permissible)**


 * Overview:** Develop a research project on a topic of your choosing and find a related dataset (or sets) to explore. Work with this data for the remainder of the semester and be prepared to present your findings in some 'final' format (slideshow, printout, interactive demonstration, video, website, etc.) on November 24th. You will probably work with software during this process, so think about how each of the platforms covered in seminars or class might be useful within your investigation. This is a self-directed research project so it is imperative that you find a topic and data that you are interested in – additionally, consider working with a partner with a complimentary skill set.


 * Some tips for beginning your research: **

On pg. 82 of //Visualizing Complexity// Manuel Lima describes they key to beginning a network visualization as the fact that "every project should start with a question" and that "this inquiry should lead to further insights about the system and perhaps answer questions that were not originally asked". With this as a goal think of a singular question that you would like to explore for the remainder of the semester in this course.
 * 1. START WITH A QUESTION**

Some examples:
 * 1) How do I move through and navigate the city?
 * 2) What kind of quality of life do new citizens (recent immigrants) to Canada have compared to 2nd or 3rd generation Canadians?
 * 3) How would the relationship of a community of friends, peers or coworkers be visualized over time?

//Pro: Will help you develop a (working) thesis as a starting point, before you begin to design. This will change over time, but you will definitely have a course or trajectory right out of the starting gate.// //Con: You may not be able to find the data you need for your investigation.//

Determine a field you have an emotional investment in and begin hunting for data related to it. Shape/determine your question based off your instincts — see what data you can find and consider the possible questions and exploration each dataset prompts (this may require experimentation with rough visualizations). Choose the most promising option and move forward.
 * 2. START WITH A FIELD**

Some examples:
 * 1) International Development
 * 2) Social Networking
 * 3) A social science – e.g. Human Geography

//Pro: You can play to your strengths and pick a field you are knowledgable in.// //Con: None, really. This is probably the safest strategy (although it does not guarantee an interesting research question – you have to craft that as you research)//

Find a dataset you are interested in and/or lends itself to visualization. Begin constructing some crude visualizations with it and think about the questions it might allow you to ask, use the process of exploring the data to help you formulate a representational strategy.
 * 3. START WITH A DATASET**

Some examples:
 * 1) Use your [|Facebook data] to construct a personalized 'social map'
 * 2) Use [|World Bank] data to explore & compare international debt over time.
 * 3) Carry a GPS device (or [|use your smartphone]) to track your location for a month – and map the results.

//Pro: You can start with great data.// //Con: You might not know what to do with it. This option may be more straightforward than the others, but it might yield a project where it is harder to get emotionally invested in the work.//

//Hint: See some of the free data resources I've listed on the visualization tools & workflows page.//


 * Exercise:** Approach this assignment as if it were an essay or major research paper. As you are used to, you will be collecting sources and constructing arguments but in this case you'll also be testing your sources (your data) as to how it is best communicated visually – legibility is the basis of your 'argument' rather than a linear narrative. Use the data you've collected to tell a story. It might be one large story (an information map) or a series of related graphs/visualizations that support one another and build a comprehensive 'view' of a topic. This will probably feel a bit foreign, and that is a good thing as it means you are doing something new – //trust your instincts.//


 * Workflow:** At the time of posting, you have approximately six weeks to complete this exercise. In order to execute a thorough investigation you'll need to work diligently and 'publicly' – each group should be prepared to discuss their progress with the class for 10-15 minutes each week (and have work to show!). Each project will take a very unique direction and it is essential that as soon as each team has chosen a topic/dataset they begin experimenting with their data – expect the majority of time associated with this assignment to be spent exploring data and troubleshooting your workflow. Where possible the instructor will assist in resolving technical issues on various software platforms with the students – but responsibility for resolving technical issues ultimately belongs to each team.




 * Evaluation:** Given that each project will be unique in terms of content, workflow and the final deliverables – evaluation will be flexible and take into account the idiosyncrasies of each project. Marks will be awarded for clarity and legibility of each submission, but they will also be awarded for ambition, work ethic (e.g. did a final project 'appear' in the last week, or did the group show up each week with new material to review/discuss – //these marks now fall under the 'lab report' portion of the evaluation for the term//), and creativity – so any efforts to tackle an ambitious workflow will be acknowledged as part of the marking process.