Project Plan (He,Khan,Liu)

April 14, 2010

in Final Project

Project: VAST 2010 Mini Challenge 2

David He, Faisal Khan, Ye Liu

Introduction

For this challenge, we have been given hospital admittance and death records for cities involved in the major epidemic outbreak. There are two main tasks. One is to characterize the spread of disease by considering attributes like symptoms of the disease, mortality rates, temporal patterns of the onset, peak and recovery of the disease. Secondly, we are asked to compare the outbreaks across cities as well.

Initial Readings

We will try to add more readings here before Friday. As for now we know that we will be going through this book –  “Illuminating the Path”. It is freely available as an e-book.

Milestones or Weekly Goals

Week 1: This week our main goal is to get familiarity with the dataset. We are planning to write small tools for assisting in understanding things like mortality rate over time, leading syndromes for mortality. For this prep-processing phase, we need to do some text processing because of the abbreviations and aliases used for name of the syndromes. Also we will be making simple plots to analyze above-mentioned variables. For this purpose, we have imported all the data in sqlite database and soon going to start running queries and do some basic charting to analyze the data. We are using python with gnuplot for this purpose.

Additionally, we will do some handsome amount of readings. Mostly we are targeting reading parts of the book on  “Illuminating the Path” to get some understanding of the idea behind visual paralytics. We will try to find some papers on epidemiology that are relevant to our project.

Week 2: During this week we will focus on coming up with multiple visual designs that answers the first question of the challenge i.e. characterize the spread of the disease. We are hoping that we will not have to do a lot of implementations for evaluating these design. Perhaps, use of some mock-up designs or static images might help us narrow down choices. We plan to begin by getting concrete understanding of how domain experts study spread of diseases. We will look into existing visualization tools and some literature dealing with the understanding of the spread of disease. If we get access to domain expert, we will seek his/her help on this topic as well.

We expect to finalize the development environment for our project by this week.

Week 3: By this week we are hoping to finalize a design for visualization the spread of the disease. Among different other criteria that we will consider for finalizing  the design, one important one will be the suitability/extensibility of this design to answer the second part of the challenge i.e. ability to compare disease spread across different cities. We will spent most of the time on implementations and remaining on doing some readings on the evaluation of visualizations.

Week 4: Finish implementing the visualization. Begin evaluating the visualization.  Write the report and present.

Individual Responsibilities

All three of us will be involved in design of visualization and determining whether the design resembles expectation.  We are planning to meet several times during next coming days. We expect to use these joint session for helping each other decide on readings and implementation, brainstorming ideas and planning next actions. David and Faisal will be doing most of the implementation. They will try to divide it equally among them. Ye (Alex) will be able to read their code and use any of the tool (custom built or off the shelf) for experimentation and analysis. He will do more readings for equal contribution.

Out Expectations

Applying the methods learned in the class to solve a practical problem.

Being able to answer the questions posed in the challenge.

Understanding of the process involved in the design of visualization and the evaluation of it.

Knowing how to handle large data sets in visualizations.

General understanding of opportunities, challenges involve in the field of visual analytic.

Hopefully interacting with some domain expert (epidemiologist) to gain insight into how the epidemics are studied.

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