Georgia Tech
CSE-6242 / CX-4242: Data and Visual Analytics
Spring 2014 - Duen Horng (Polo) Chau

PROJECT INFORMATION

Preliminaries

Graded parts of the project:

1. Proposal (10%)
2. Proposal presentation (10%)
3. Progress report (15%)
4. Final presentation (15%)
5. Final report (50%).

Choosing a Topic

• Pick your own topic:
  • you will need to justify that the topic is interesting, relevant to the course, of suitable difficulty.
  • necessary components: (1) data, (2) some sort of algorithms/computation (e.g., clustering, classification), and (3) a user interface (e.g., visual, voice-controlled, gestured controlled) that interact with the algorithms.
• Harder way:
  
  • Joint projects with other courses are also negotiable. In that case, you will need the approval of the instructor, and you also need to clarify exactly what steps will be done for our course, as well as for the other course.
  • Projects related to your dissertation/master-project are also possible, as long as there is no 'double-dipping', i.e., you clearly specify what the project will do, in addition to what you were planning to do for your thesis anyway.
• If you need help with ideas, come talk to me; I'll give you some.
  

Once you have selected a topic, you should do some background reading so that you are capable of describing, in some detail, what you expect to accomplish. For example, if you decide that you want to implement some new proposal for a multidimensional file structure, you will have to carefully read the paper that proposes similar structures, pinpoint their weaknesses, and explain how your approach will address these weaknesses. Once you have read up on your topic, you will be ready to write your proposal.

Proposal

Your proposal should answer Heilmeier's questions (all 9 of them) whenever possible; for the questions that may not be very relevant (e.g., "How much will it cost?"), briefly explain why they aren't. In other words, your proposal should describe what you plan to do (the probelm to address), why you want to do it, how you will do it (what tools? e.g., SQLite, PostgreSQL, Hadoop, Kinect, iPad, etc.), how your approach is better than the state of the art, why it may succeed, and when it does, what differences will it make, how you will measure success, how long it's gonna take, etc.

You must describe what portion of the project each team member will be doing.

Your proposal should be fewer than 800 words (excluding references, titles, etc.), 12pt font, typed (e.g., latex/pdf/msword), and with pictures if useful. It should be self-contained. For example, don't just say: "We plan to implement Smith's Foo-Tree data structure [Smith86], and we will study its performance." Instead, you should briefly review the key ideas in the references, and describe clearly the alternatives that you will be examining.

Grading scheme & Submission instructions

• 60% for the survey
• 30% for innovation
• 10% for plan of activities
• For every Heilmeier question that's not mentioned, deduct 5%.
• You may consider organizing your proposal based on the Heilmeier questions (e.g., each section addresses one question)
• Your survey should have at least 3 papers or book chapters per group member (outside of the reading list).
  • Short papers, like PNAS, Nature, Science papers, count as 0.5.
  • Copying the abstract of the papers is obviously prohibited, constituting plagiarism.
  • For each paper, describe
    
  • (a) the main idea,
    
  • (b) why (or why not) it will be useful for your project, and
    
  • (c) its potential shortcomings, that you will try to improve upon.
• Clear problem definition: give a precise formal problem definition, in addition to a jargon-free version (for Heilmeier question #1).
• Provide a plan of activities and time estimates, per group member. List what each group member has done, and will do.
• Submit a hardcopy (keep the graded copy!) -- not applicable for distance learning students
• Submit a softcopy via T-Square
  

Proposal Presentation

6 min per team. See T-Square for your team's presentation date and time.

• 5 min maximum for presentation
• 1 min for Q&A + transition to next team

Time limit strictly enforced! You'll be booted off the podium when time is up.

Don't use too many slides; less is more! Fewer slides mean it's less likely that you will overrun. Being succint is hard, so practice your timing and delivery!

Make sure you answer Heilmeier questions, briefly mention your survey, expected innovation, plan of activites, etc. Presentation will be graded similarly as the proposal writeup.

Progress Report

This should be fewer than 1500 words, 12pt font, typed.

It mainly serves as a checkpoint, to detect and prevent dead-ends and other problems early on.

It should consist of the same sections as your final report (introduction, survey, etc), with a few sections "under construction", describing the work performed up to then, and the revised plans for the whole project.

Specifically, the introduction and survey sections should be in their final form; the section on the proposed method should be almost finished; the sections on the experiments and conclusions will have whatever results you have obtained, as well as `place-holders' for the results you plan/hope to obtain.

Grading scheme & Submission instructions

Final Presentation

6 min per team. Time limit strictly enforced! See T-Square for your team's presentation date.

• 5 min maximum for presentation
• 1 min for Q&A + transition to next team

Don't use too many slides; less is more! Fewer slides = less likely to overrun. Being succint is hard, so practice your timing and delivery!

Your presentation should cover:

• Motivation/Introduction: remind us what you're doing, why it's important and why we should care
• Your approaches (algorithm and visualization): what it is, its intuition, why does it work, etc.
• What's your data: where you got it, what's its characteristics (e.g., size on disk, # of records, temporal or not, etc.)
• Experiment and results: how did you evaluate your approaches? What are the results? How do you methods compare to other methods (if any)?
• Conclusions (and optinally future work/discussion)

Grading scheme: 2% for each of the above points, plus 5% for presentation delivery (e.g., good slides? Did you practice?)

Final Report

It will be a detailed description of what you did, what results you obtained, and what you have learned and/or can conclude from your work.

Components:

1. Writeup: fewer than 2500 words, 12pt font, typed. Describe in depth the novelties of your approach and your discoveries/insights/experiments, etc.  
2. Software: packaging, documentation, and portability. The goal is to provide enough material, so that other people can use it and continue your work.

Grading scheme & Submission instructions

• Writeup
  • [2%] Introduction - Motivation
  • [3%] Problem definition
    
  • [5%] Survey
  • Proposed method
    • [10%] Intuition - why should it be better than the state of the art?
    • [35%] Description of your approaches: algorithms, user interfaces, etc.
  • Experiments/ Evaluation
    • [5%] Description of your testbed; list of questions your experiments are designed to answer
    • [25%] Details of the experiments; observations (as many as you can!)
  • [5%] Conclusions and discussion
• Software + writeup softcopy [10%]; create a zip file that contains:
  • a concise, short README.txt file, corresponding to the "user's manual". This file should describe the package in a few paragraphs, how to install it, how to use it, and how to run a demo.
  • a DOC directory, with your writeup, and your presentation slides (in your favorite form: latex, pdf, powerpoint, ms-word)
  • make sure that your package includes only the absolutely necessary set of files!
• Submit a hardcopy of your writeup (with graded proposal and progress report attached) -- not applicable for distance learning students

Due Dates

As announced on the course homepage

Based on materials by Prof. Christos Faloutsos