Student Posts

Project Plan (JW)

April 22, 2010

Description

The project involves comparing climate observations from across North America to downscaled climate predictions for Wisconsin using 15 different climate models. There are two time spans, 2046-2065 and 2081-2100, for each set of predictions. The visualization will also take into consideration three different carbon emission scenarios. The state of Wisconsin will be divided into cells (.1 degree latitude by .1 degree longitude) with an analog displayed somewhere within North America.

Desired outcomes

An interactive map and accompanying geo-visual analytic tool will be produced. The visualizations will be designed for display online, with the data residing in a database accessible though standard web requests.

Reading List
Shneiderman, B. 1994. Dynamic Queries for Visual Information Seeking. IEEE Softw. 11, 6 (Nov. 1994), 70-77.

Eick, S. G. 1994. Data visualization sliders. In Proceedings of the 7th Annual ACM Symposium on User interface Software and Technology (Marina del Rey, California, United States, November 02 – 04, 1994). UIST ’94. ACM, New York, NY, 119-120.

Nakhimovsky, Y., Miller, A. T., Dimopoulos, T., and Siliski, M. 2010. Behind the scenes of google maps navigation: enabling actionable user feedback at scale. In Proceedings of the 28th of the international Conference Extended Abstracts on Human Factors in Computing Systems (Atlanta, Georgia, USA, April 10 – 15, 2010). CHI EA ’10. ACM, New York, NY, 3763-3768.

Timetable
Week 1: Gather all of the data from the Jack Williams lab and create a relational database for the different carbon emission scenarios, climate models and time spans.
Week 2: Create an interactive map capable of defining each cell within Wisconsin. The map should have the same basic navigational capabilities as Google maps, Yahoo or Bing.
Week 3: Begin integrating the climate data with the maps of Wisconsin and North America. Every cell on either map should have the capability of displaying the relevant data for a given location.
Week 4: Build a geo-visual analytic tool that shows the original Wisconsin data point and the distance to all of the related points for North America. I’ll have a better idea what this will look like after working with the data.

Description
The final visualization will contain two maps side-by-side. The map on the left will allow the user to navigate the state of Wisconsin in order to select a cell for comparison. Once a cell has been selected, the map on the right will show all of the results in relation to the Wisconsin cell. Lines will be draw between the original cell and all of the results, with the ability to mouse-over each line to display the distance and bearing. Drop down menus will allow the user to select different scenarios, models and time spans for unique database queries. I’ll add the ability to switch base tiles so that a user can evaluate the landscape using aerial photos, road networks or a hybrid of both. A tool for analyzing the relationship between the original cell and each result will reside below the set of maps.

Description

Desired outcomes

Reading List

Shneiderman, B. 1994. Dynamic Queries for Visual Information Seeking. IEEE Softw. 11, 6 (Nov. 1994), 70-77.

Eick, S. G. 1994. Data visualization sliders. In Proceedings of the 7th Annual ACM Symposium on User interface Software and Technology (Marina del Rey, California, United States, November 02 – 04, 1994). UIST ’94. ACM, New York, NY, 119-120.

Nakhimovsky, Y., Miller, A. T., Dimopoulos, T., and Siliski, M. 2010. Behind the scenes of google maps navigation: enabling actionable user feedback at scale. In Proceedings of the 28th of the international Conference Extended Abstracts on Human Factors in Computing Systems (Atlanta, Georgia, USA, April 10 – 15, 2010). CHI EA ’10. ACM, New York, NY, 3763-3768.

Timetable

Week 1: Gather all of the data from the Jack Williams lab and create a relational database for the different carbon emission scenarios, climate models and time spans.

Week 2: Create an interactive map capable of defining each cell within Wisconsin. The map should have the same basic navigational capabilities as Google maps, Yahoo or Bing.

Week 3: Begin integrating the climate data with the maps of Wisconsin and North America. Every cell on either map should have the capability of displaying the relevant data for a given location.

Week 4: Build a geo-visual analytic tool that shows the original Wisconsin data point and the distance to all of the related points for North America. I’ll have a better idea what this will look like after working with the data.

Description

The final visualization will contain two maps side-by-side. The map on the left will allow the user to navigate the state of Wisconsin in order to select a cell for comparison. Once a cell has been selected, the map on the right will show all of the results in relation to the Wisconsin cell. Lines will be draw between the original cell and all of the results, with the ability to mouse-over each line to display the distance and bearing. Drop down menus will allow the user to select different scenarios, models and time spans for unique database queries. I’ll add the ability to switch base tiles so that a user can evaluate the landscape using aerial photos, road networks or a hybrid of both. A tool for analyzing the relationship between the original cell and each result will reside below the set of maps.

How do you depict time?

April 17, 2010

in Cool Stuff,Student Posts

http://www.papress.com/html/book.details.page.tpl?isbn=9781568987637

Project Plan

April 17, 2010

in Final Project,Student Posts

Topic:

I want to explore the use of textons, textures, color blending, and their combination as a means to clearly show relationships in a general Euler diagram.

Desired outcomes:

I want to develop a technique, or a set of techniques, that can be used to style a Euler diagram so that the relationship of any subregion to the rest of the diagram is obvious and require little cognitive resources to understand. A part of this goal will be to create visually pleasing illustrations, and things such as color harmonies will be taken into account.

Initial reading list:

Cohen-Or, D., Sorkine, O., Gal, R., Leyvand, T., and Xu, Y. 2006. Color harmonization. ACM Trans. Graph. 25, 3 (Jul. 2006), 624-630. DOI= http://doi.acm.org/10.1145/1141911.1141933

Hagh-Shenas, H., Interrante, V., Healey, C., and Kim, S. 2006. Weaving versus blending: a quantitative assessment of the information carrying capacities of two alternative methods for conveying multivariate data with color. In Proceedings of the 3rd Symposium on Applied Perception in Graphics and Visualization (Boston, Massachusetts, July 28 – 29, 2006). APGV ’06, vol. 153. ACM, New York, NY, 164-164. DOI= http://doi.acm.org/10.1145/1140491.1140541

Papers on texture synthesis from: http://graphics.cs.cmu.edu/people/efros/research/synthesis.html

Time Table:

Week 1
- Compile and begin reading the reading list
- Visualize color harmonies in several color spaces
Week 2
- Finish reading list
- Complete harmony visualization
- Formulate optimization framework for finding colors
- Decide on an approach for texture synthesis
Week 3
- Implement all approaches, including some combinations
- perform Initial testing
- Begin write up
Week 4
- Finish write up
- Prepare presentation
- Additional testing

End result visualization:

Given a Euler diagram, the aim will be to color it using the approaches described in such a way that it can be understood easily. Something like this, but in a way that scales to more complicated relationships and regions

Project Plan (LW, DA)

April 16, 2010

in Final Project,Student Posts

Topic:

The topic that we plan to explore in this project is how to compare multiple network visualizations. While techniques to address this issue have a wide variety of potential applications, there is not a substantial amount of existing literature directly addressing this problem. Thus far, we have a few potential ideas for implementation, but plan to elaborate on these and develop others over the course of the project.

Desired Outcomes:

The outcome of this project will be the implementation of multiple proposed solutions to the network comparison problem. Because of time limitations and lack of existing solutions for guidance, we will likely simplify the problem set to series of small networks. The details of the implementation, such as language and development package, have yet to be decided.

From this project, we hope to gain a better understanding of graph embeddings and techniques for improving readability as it applies to graph comparison. As we’ve seen, graph and network style visualizations are very common in practice. We hope to better understand how techniques that we’ve covered in class can help to create better means of comparison.

Reading List:

Graham and Kennedy. Exploring Multiple Trees through DAG Representations. IEEE InfoVis, 2007.

Frishman, Y. & Tal, A. Online Dynamic Graph Drawing IEEE Transactions on Visualization and Computer Graphics, 2008.

Frishman, Y. & Tal, A. Dynamic Drawing of Clustered Graphs Proc. IEEE Symposium on Information Visualization, 2004.

C. Collberg, S. Kobourov, J. Nagra, J. Pitts, and K.Wampler. A system for graph-based visualization of the evolution of software. In SoftVis ’03: Proceedings of the 2003 ACM symposium on Software visualization, 2003.

Ogata et al. A heuristic graph comparison algorithm and its application to detect functionally related enzyme clusters. Oxford University Press, 2000.

Hoebe and Bosma. Visualizing multiple network perspectives. ACM, 2004.

Major Layout Algorithms. http://www.yworks.com/products/yfiles/doc/developers-guide/major_layouters.html

Erten et al. Simultaneous Graph Drawing: Layout Algorithms and Visualization Schemes.

Time Table:

- Week 1:
  - Develop Project Plan
  - Compile Initial Reading List
  - Begin readings

- Week 2:
  - Complete readings
  - Brainstorm potential solutions
  - Select most promising solutions
  - Select implementation language/package
  - Create initial data set
- Week 3:
  - Implement solutions
  - Test over additional data sets
- Week 4:
  - Prepare report and presentation

Output & Data Sources:

We hope to implement several solutions to the network comparison problem. The data sources used for this visualization will likely be small, derived data sets. Hopefully there will be potential to apply our solutions to real-world data sets. However, since the purpose of this project is for exploration of general technique, integrating real-world data visualization is not currently part of the project plan.

Infographic on Infographics

April 9, 2010

in Cool Stuff,Student Posts

Click for full size

Project Proposal: Visualizing weather data on a map

April 7, 2010

in Project Ideas,Student Posts

Daily weather data are collected at ground stations and sampled to a 1 sq. km. for the entire United States. The data are made available in a scientific format called NetCDF, which is essentially a hierarchical format capable of storing an arbitrary number of nested arrays. While suitable for storage and targeted analysis, NetCDF is not easily amenable to spatial query and visualization.

This is a proposal to convert the NetCDF format to a spatial database format, and then write routines and build the interface that would allow spatial selection of weather data and display them on a map as geo-referenced image.

The project would focus on creating a web-based working prototype for a specific part of the country. The prototype would be scalable to the entire country.

Plus: I already have the data; the spatial routines are pretty well established; the scientific contribution factor is high.

Minus: There is not much “new” in this proposal even though the innovation quotient in terms of improving a process is pretty high.