Group Project Update

Progress

We’ve currently been working on compiling the data we have on the cave, as well as information we need to look up for each specific artist. In our shared spreadsheet, we have been filling out the following columns for every band listed on the Carleton Cave archive: Date of Performance, Band/Artist Name, Genre, Origin, Current Listener Count, Group Id, Student Band. While some of these labels are self explanatory, some were added to specifically add more depth to our project. Origin refers to where the band/artist is from, current listener count refers to how many people currently listen to their music, group id refers to a special attribute a band may have, and lastly, the student band column holds checkboxes to indicate if a band was made up of students or not. This task has been fairly tedious, but having five group members expedites this process. 

Problems

Our greatest task so far has been compiling all of our source data into a google sheet. This has proven to be tedious as we have to gather specific information about hundreds of individual artists. We have tackled this challenge by delegating roles to each group member. A couple people have been using the Carleton website to compile data on when bands/artists performed. While other members have been using external websites to gain more specific information about the bands. Delegating different tasks within the group has prevented miscommunication and the repetition of data, proving to be most efficient. So far, the extent of data we are collecting has not hindered our ability to get the project done on time. However, if it takes longer some proposed solutions are having a couple people begin to work on the timeline/network analysis, while other people continue collecting data, or using more outside class time to work on the project.

Tools and techniques

We’re planning on using TimelineJS to create a timeline of the bands and add some visual components (pictures/videos we have of them) to different data points. As for the network analysis, we can use Palladio’s graph feature to show the relationships between artists based on the genre of their music. Specifically, the nodes will be bands and the edges will be genres. Color coding them based on a range of years in which may also be beneficial for viewers. 

Deliverables 

Week 9: 

By Tuesday: Data collected from our sources. Pull all the bands into the spreadsheet, including listener count and genres.  

On Tuesday/by Thursday: Create our main timeline with all the bands on it 

Thursday: Work on network and make the timeline look nice

By Sunday: Create our website, including our timeline and network. 

Week 10: 

Tuesday: Presentation slides finished.  

Our project is still on track. We still have a bit of source work to get done, but if we finish collecting data by Tuesday we should still be on track. The data collection is definitely the most tedious aspect of our project, so once we get it done the work should move quicker. 

Personal Statements

Vanessa

Margie

Nora

Nelson

Ryan

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