Members:
Adam Loew, Nick Reeves, Andrew Lin
Topic and Objectives:
We are planning for our project to create an interactive timeline that shows the positions of Carleton sports teams within the MIAC conference at the end of each season over the years. We’d be using data from the MIAC websites to record the history of each team and will use that data to map it on the timeline. We may include historic moments in Carleton’s history as reference in accordance with the passing years on the timeline.
The proposed methodology:
We have found data on the MIAC’s website that lists all the recorded positions of teams over the years and will add that data into workable files that we can then shape into a timeline. We will be using _____ (to be determined) software to represent our data, with the goal of transforming the long pages of static information into something that is more interactive and easier to read and access. Ideally, for the presentation of our data, we will have a map with an interactive slider bar to showcase many decades of the teams.
Timeline:
Our goal for the next week (8th week) or so is to synthesize our data into some sort of workable file (probably a spreadsheet), and then during 9th week we can work on compiling the data into a timeline. The visualization will show the historical progression of the various teams (to be determined) record.
Project Model:
We will be using ____ as a model for our final project. We also think the SIMILE timeline tool is a good example, although that is more text-based then data-based.
Post Links:
Adam’s post: Click here!
Nick’s Post: Click here!
Andrew’s Post: Coming soon!
One reply on “Carleton Sports Visualization”
Team Sports Viz,
This is a good start for a project idea but still has lots of blanks to be filled in. Visualizing change over time in Carleton’s sports history sounds promising, but to qualify as a DH project you will want to dig into the possible reasons for whatever patterns you find. What historical events correlate with important changes? Are the regional patterns of affiliation or competition that help makes sense of new developments?
There are a couple of tools that might work for the kind of visualization you propose here, including Topotime and Palladio.