The HIVE Lab aims to help people make better decisions, particularly through information visualization. We have developed interactive visual tools, evaluated them to see if it works, and extracted theories from the experiences.
We have developed various tools as follows:
- Dust & Magnet helps you choose a right cereal for you (check out the video);
- Visual Nursing Home Choice helps you choose a nursing home;
- SimulSort helps you choose an option comparing multiple attributes;
- Food for the Heart helps heart patients choose right meal plan; and
- OpinionMarks helps you understand tons of online reviews.
As you can see from the list, we have focused on understanding how individual users, who do not have sophisticated background in data analysis, can make a better choice through data visualization approaches.
Developing something is fun, but developing itself cannot teach us something new. We tested these tools via various approaches: We used to rely on a traditional controlled laboratory study, but we found that it is too time/resourcing-consuming. Thus, since 2012 Summer, we have heavily relied on crowdsourcing-base experiment, and we ended up creating our own platform (MechanicalTurkExperimentalPlatform). We also really appreciate more qualitative approaches (e.g., observation, interview, focus group studies, and survey) to understand how and why users behave in a certain way. We also have a Tobii X60 eye tracker to better understand underlying cognitive activities of our users. If you want to see the eye-tracker demo, let us know. Some of insights gained through these evaluation studies could turned into methodological suggestions.
While working on these exciting projects, we sometimes have more deeper understanding of how people interact with visualization techniques. Thus, we have following projects:
- Visualization Literacy
- Information Visualization Theory
- Insight in Visualization
- Individual Differences
In addition, when we run into interesting ideas, we tend to solve the problems:
- POET helps students learn optimization modeling;
- TimeMatrix and MMGraph help social scientists analyze complex social network;
- TimeInvestigator investigates the impact of temporal dimensions on investigative analysis;
- ReadingMate helps you read while running; and
- HHReview reviews the studies in web-based dietary intervention.