Hi folks,

Next Tuesday, we have HCI group meeting and HCI/Vis talk. The meeting will begin at 11:45 am @ DGP Seminar room and the talk will start right after the meeting. In the meeting, Devamardeep, one of our undergrad students, will lead a brainstorming for his summer research about “Layout Management in Virtual Reality using Eyelid Gestures.”  After the meeting, Anamaria Crisan from UBC will be giving a talk, titled “Establishing a visualization design space – A case study in infectious disease genomic epidemiology.” Details are attached below.

Thanks,

Seyong Ha

----- Brainstorming

Topic: Layout Management in Virtual Reality using Eyelid Gestures

I want to the user to perform precise object manipulation, like grabbing a book and moving it only along a table. To do so, we can use information of the surrounding objects (like the table) to constrain the book’s position or create new constraints. Currently there are three constraints that the user can create: point, line, and plane. We also want to activate / deactivate the constraints (maybe I want to move the book through the table). A lot of times in real life you close one eye to help align objects precisely, we are thinking of using this gesture to activate the constraint.

How should objects interact with these constraints? And how can we make it easier to create constraints (ie. snap the plane constraint to be parallel to nearby surfaces)

What other eye gestures can be helpful in this context? ie. shooting lasers out of your eyes to delete objects.

---- Talk

Title: Establishing a visualization design space - A case study in infectious disease genomic epidemiology

Talk Abstract:

Data visualization is an important tool for exploring and communicating findings from genomic and health datasets. Yet, without a systematic way of understanding the design space of data visualizations, researchers do not have a clear sense of what kind of visualizations are possible, or how to distinguish between good and bad options. We have devised an approach using both literature mining and human-in-the-loop analysis to construct a visualization design space from corpus of scientific research papers. We ascertain why and what visualizations were created, and how they are constructed. We applied our approach to derive a Genomic Epidemiology Visualization Typology (GEViT) and operationalized our results to produce an explorable gallery of the visualization design space containing hundreds of categorized visualizations. We are the first to take such a systematic approach to visualization analysis, which can be applied by future visualization tool developers to areas that extend beyond genomic epidemiology.

Bio:

Ana Crisan is a current PhD candidate in computer science at UBC studying how heterogenous types of public health data can be integrated and visualized. She is a CIHR Vanier Scholar and is jointly supervised by Dr. Tamara Munzner (Computer Science) and Dr. Jennifer Gardy (School of Population and Public Health). Prior to her PhD studies, Ana worked with the British Columbia Centre for Disease Control supporting research in genomic epidemiology, and had also previously worked on prostate cancer biomarker development with a Vancouver based start-up. A summary of her present and past work can be found on her website: www.cs.ubc.ca/~acrisan.