Literature and Technical Paper

In our literature review and technical paper, we were able to explore elements of storytelling through data visualization, look at best practices, and develop and design the features we would build in our own visualization if we had more time.

We chose to do a literature review as our technical paper, because fully conducting research on a data visualization that we coded ended up being too broad a scope to accomplish this summer. Insetead, we opted to design what features we would have made, based on our literature review, exploration of the data, and information we learned about the issue of irresponsible AI this summer.

A big part of the technical paper was developing clarity around the process of data visualization research, and building that process into the structure of our technical paper. Our research process has followed the following steps/considerations:

• Data: What data are we visualizing? This step contains both data curation as well as just orienting oneself to the dataset.

• User: Who is our user? A researcher? A layperson? How comfortable are they with technology as well as the dataset?

• Best Practices: What are the current best practices for conveying data in this field? What research has already been done on best practices?

• New Feature: Build a new feature based on current best practices and an analysis of user needs. What does not exist yet that could aid visualization for this dataset and audience?

• Build feature and test with ideal user group.

• Make feature available for ideal user group to use.

This was the outline we generated for developing research in data visualization, and aimed to follow throughout the summer. While this project was largely a survey experience of the different parts of research, we may not have gone in depth in each of these steps, but we did at least explore each one and gain some experience in how to approach each step effectively.