CSCI 1951-T Syllabus

Surveying VR Data Visualization Software for Research: Augmented Collaborative Data Visualization

Course Summary

In a collaborative group effort, this course will search out, install, test, build, and critically evaluate multi-user AR/VR software and its applicability for exploratory data visualization. A substantial portion of the class will involve evaluating existing multi-user AR/VR software and documenting these findings in the course wiki. Software evaluation will include web research, hands-on case studies, and surveying. Students will also utilize this software to build data visualizations, or build their own multi-user AR/VR software using existing tools and frameworks. At the end of this course, we will have a comprehensive understanding of the current state of collaborative multi-user AR/VR software and will have documented this knowledge to aid future researchers. 

Learning Goals

After this course students will be able to:

1. articulate AR/VR visualization software tool goals, requirements, and capabilities;

2. construct meaningful evaluation strategies for software libraries, frameworks, and applications; strategies include surveys, interviews, comparative use, case studies, and web research;

3. execute tool evaluation strategies;

4. build visualization software packages;

5. comparatively analyze software tools based on evaluation;

6. be familiar with a number of AR/VR software tools and hardware;

7. think critically about software;

8. communicate ideas more clearly;

We will begin the semester by taking stock of candidates for software. Understanding and codifying claimed capabilities will guide the choice of a subset for closer study.  Each student will pick from the subset to critically evaluate, adding the results of their evaluation to the course wiki. Moreover, each student will design a tutorial that highlights the features of the software they select.  Through both the design, construction, and execution of the tutorials, we will gather deeper knowledge of the benefits and costs of the tools. 

At each stage in the course, we will document our findings and analysis in a wiki. One goal for the wiki is to help AR/VR developers to choose wisely in creating their virtual realities.  A second is to identify gaps in available software and thus to nudge the development of future software to fill those gaps.  At some point the wiki will go live, possibly after submission as a research paper, if appropriate.

Grading

Evaluation in the class will be as follows:

•   15% class attendance, class participation, and sharing useful tips via class Slack

•   15% feedback survey design, creation, collection, and analysis contributions

•   20% in-class activity quality

•   10% in-class activity results analysis

•   15% weekly journal of activities and findings

•   25% overall final wiki contributions

Project Evaluation Rubric

Below are a set of questions that should help in evaluating project ideas:

1. clearly identifies deliverable additions to our VR Software Wiki

2. involves collaboration in AR/VR

3. involves large scientific data visualization along the lines of the "Scientific Data" wiki page and identifies the specific data type and software that it will use

4. has a realistic schedule with explicit and measurable milestones at least each week and mostly every class

5. explicitly evaluates AR/VR software, preferably in comparison to related software

6. includes an in-class activity, which can be formative (early in the project) or evaluative (later in the project)

7. has resources available with sufficient documentation

Activities logging rubric criteria:

Journal activities are explicitly and clearly related to course deliverables

deliverables are described and attributed in wiki

report states total amount of time

total time is appropriate

Homework Expectations

Every week there will be homework posted in the course timeline. Make sure to complete this as well as any in-class activities and their deliverables that you did not finish in class. If you did not finish the in-class activity and it is not possible to recreate the deliverable later then please send David and Melvin a slack message. 

Presentations must be sent 24 hours ahead to give us enough to aggregate all of the slides. In-class activity prep should be sent at least 24 hours ahead of time. Other homework is due at 9AM. If the homework is not done by then, it will be marked as late. 

Attendance/Class Participation

This is very much a participation-based class, so you are not only expected to attend class on time every time but also actively participate. If you have an extenuating circumstance and cannot attend a particular class, we require that you acquire and send a Dean's Note. Unexcused absences and/or tardiness will hurt your grade.   

Time Commitment

Over 14 weeks students will spend 3 hour per week in class (42 hours total) plus an average of 10 hours per week on homework, as described above (140 hours).  Total hours for the semester are 182.

Prerequisites

While there are no formal prerequisites listed for this class, CS background at the level of 320 or 330 will be very helpful.  Students should be familiar with downloading, building, and installing open-source software from the internet.  Some experience with modifying open-source software will be helpful, but not essential. Familiarity with graphics libraries will also be helpful.

Academic Support

Brown University is committed to full inclusion of all students. Please inform me early in the term if you have a disability or other conditions that might require accommodations or modification of any of these course procedures. You may speak with me after class or during office hours. For more information, please contact Student Accessibility Services at 401-863-9588 or SAS@brown.edu. Students in need of short-term academic advice or support can contact one of the deans in the Dean of the College office. 

Diversity & Inclusion

Our aim is to provide a welcoming environment to all students who take the class. Course staff have been trained in diversity and inclusion, and all members of the CS community, including faculty and staff, are expected to treat one another in a professional manner. If you feel you have not been treated in a professional manner by any of the course staff, please contact either David Laidlaw (the instructor), Robert Tamassia (Dept. Chair), Tom Doeppner (Vice Chair) or Morgan Beltre (diversity & inclusion staff member). We take all complaints about unprofessional behavior seriously. To access student support services and resources, and to learn more about diversity and inclusion in CS, please visit this webpage.

Laptop Accessibility

We understand that not all students in our class may have access to laptops to complete assignments. In case you need a computer, please email the course staff at melvin_he@brown.edu to discuss potential options.