Lecture: Visual Analytics Tools
In this lecture you will introduce several visual analytics tools and techniques by giving a short presentation about a research paper. The presentation will be graded and the graded as one of the assignments.
Paper Selection
Below you will find a couple of papers to choose from. If you cannot access a paper from the pdf link I provided do the following:
- try to google the title of the paper - often you can find other sources such as the personal websites of the authors (do pay attention, though that you grab the same version of the paper)
- try to access them from your university's wifi - the university often has access to digital libraries enabled by default from within the university's network
- if you still cannot access a paper let me know which one it is and I will try to send it to you
| Presenting Student | Paper | Possible pdf link | |
| Dimitri Lasne | 1. | Polaris: a system for query, analysis, and visualization of multidimensional relational databases, Stolte, C.; Tang, D.; Hanrahan, P., in IEEE TVCG, 2002 | (pdf) |
| Mengying Du | 2. | CiteRivers: Visual Analytics of Citation Patterns, in IEEE TVCG, Heimerl, F.; Han, Q.; Koch, S.; Ertl, T., 2015 | (pdf) |
| Yufan Zheng | 3. | Collaborative Visualization using RCloud, Sheidegger et al. , VAST, 2015 | (pdf) |
| Gilles Gbakatchetche | 4. | Using visualizations to monitor changes and harvest insights from a global-scale logging infrastructure at Twitter, in Visual Analytics Science and Technology (VAST), Wongsuphasawat, K.; Lin, J., 2014 | (pdf) |
| Visar Mullafetah | 5. | Jigsaw: supporting investigative analysis through interactive visualization, John Stasko, Carsten Görg, and Zhicheng Liu, VAST, 2007 | (pdf) |
| 6. | Snap-Together Visualization: A User Interface for Coordinating Visualizations via Relational Schemata. C. North and B. Shneiderman. AVI 2000. | (pdf) | |
| Alita RUKUBAYIHUNGA | 7. | VisTrails: Visualization Meets Data Management. S. P. Callahan, J. Freire, E. Santos, C. E. Scheidegger, C. T. Silva, H. T. Vo. ACM SIGMOD 2006. | (pdf) |
| Thuc Phan | 8. | Show Me: Automatic Presentation for Visual Analysis. J. Mackinlay, P. Hanrahan and C. Stolte. IEEE InfoVis 2007. | (pdf) |
| Muzamil Hanif | 9. | The sandbox for analysis: concepts and evaluation, William Wright, David Schroh, Pascale Proulx, Alex Skaburskis, and Brian Cort, ACM CHI 2006 | (pdf) |
Presentation format
Every presentation should be a maximum of 12 minutes long.
- Start with a short introduction of the goal and contribution (1-2 slides)
- Then, show the system, either a video, a demo or slides (in order of preference). Keep it under time control.
- Then, give more "important" details. One per slide with illustration.
- Finish in the conclusion with a take-away message and a personal statement.
It's highly recommended you practice your talk at least once (either alone or with a friend) to make sure you will not go over 12 minutes.
On the day of your presentations bring your laptop and if necessary VGA adapters for your laptop to do the presentation. Do not expect internet to work in the room, so download any media you may want to show. If you don't have a laptop for your presentation send me your presentation a day in advance so that I can test it on my laptop.
TODO
Send an email to petra.isenberg@inria.fr with the titles of their favorite papers (up to five total) listed in order of preference. A couple of days later, all students will be informed which paper they have been assigned and when they will present it.
The deadline for sending preferences is Friday October 4th. at 14:00
Student-paper assignments will be done using the Hungarian method. A student getting her first choice will be assigned a cost of -5, the second choice is -4, etc. Getting an unlisted paper yields the highest cost of 0. This situation cannot be avoided altogether but the risk of it happening lowers with the number of papers listed (up to 5).
Students who send their preferences too late (e.g., absent) will be assigned a remaining paper.