One of the major components of this class is the project. The point
of this project is to delve further into some aspect that we have
been studying. You may do your project either alone or in groups of
two to three. The amount of work expected from the project is
commensurate with the number of people working on it (i.e., you
personally are expected to put in the same amount of work on a project
regardless of whether you're working alone or in a group). Keep in
mind that I do not require that this project be an
implementation. A literature survey is a perfectly fine project.
This project should not eat your life.
- September 27: 1-page proposal due. This should include:
- What problem(s) you want to solve,
- What is going to be new and challenging about it,
- How you will try to solve the problem(s)
- What problems you don't consider to be part of the project (i.e.,
- What resources you need that you don't already have
- Who is on your team if you are working in a team. Teams are
- Week of October 4: feedback on proposal returned to you
- October 27: 4-page midterm status report due; this should
describe what you have done, what you have left to do, roadblocks
you've encountered, interesting or unexpected questions or issues that
uncovered, etc. Included in this report should be 1-2 pages of
literature search for related work; this should include both a written
component comparing your project to related work, as well as a
bibliography. Note that this checkpoint is largely a chance for
you to get the feedback that you need. While it is not graded,
students who have not made a good effort on this checkpoint often wind
up not making good effort on the project overall and thus not doing well.
- Week of November 1: feedback on status report returned to you
- November 22 - December 1: Project presentations. Precise schedule TBD
(it's first come first served via requests that are e-mailed to me ---
requests only accepted after proposals are turned in),
but everyone should be prepared for November 22. Your presentation
should be ~25 minutes long - with at least 5 minutes of that time
reserved for questions and answers. Here is what I expect out of the
presentation (not necessarily in this order):
- A good description of what the project is (inputs, outputs, etc.)
- The motivation for why this project is interesting - why did
you choose to do it, and why should we care about the problem
- A discussion of what makes this project non-trivial (especially
for the more research-oriented projects)
- A description of how the project fits into the context of the class
- A presentation of the results thus far
- A discussion of what results you expect to get by the project
- A discussion of the difficulties or surprises that you had when
working on the project
- If your project is in a group, everyone must speak.
- Tuesday, December 7 - 5:00pm
Final report due. Your final project report is due, along with a
group evaluation for those working in groups (see below). The final
report must be a full-length conference-style paper discussing your
project. (It should be roughly equivalent to 10-14 single column
pages. Note that this is a rough guideline. It is okay to go a
bit over this, particularly if you're working in a large group - this
is just meant to help you decide if you're in the right ball park.)
You should model your paper on some of the papers we've read this
term. Either PDF by e-mail or a hard copy in my box is fine. If you
give a hard copy, I'd appreciate an e-mail letting me know that you've
turned it in. Note that I don't care about the format; I only specify
the length in single column pages because otherwise people ask if I mean
single or double column pages.
The goal of saying "conference style paper" is that I want
you to include things like:
Note that some of you won't actually create a solution, but just
explore the literature, which is fine. In this case, your job is to
explore the strengths and weaknesses of the approaches, and, if you
feel like there's an obvious choice, say what you would do if you were
going to implement a solution to the problem. Note that I do not care
about the layout.
- Motivate the problem that you're working on
- Provide an example of a scenario where you'd use your solution
- Tell me about the solution that you've created, this includes telling me about what makes the problem interesting
hard. If you'd like, you can interpret this as telling me what
problems you ran into.
- Relate it to related work
- Tell me about potential future work - even if you have no
intension of ever doing it. Just like in a real conference paper, the
goal is for you to show that you know what some of the flaws are with
your system, even if you have no intension of solving them. ;)
In addition to the report, I want each person who is working
on a project in a group to SEPARATELY turn in a report on how they
felt that all of the group members (yourself included) contributed to
the project. Useful information is: what parts of the project you did
(e.g., if you divided the work by sections, who did what section), how
many hours you estimated that you worked, and how well you feel like
you and the other people in the project did.
Here are some ideas that would be appropriate for the course project.
The best project ideas are likely to come from you; however, here are
some that you can use as is or use to think of new ones. The projects
can run the gamut from all theory to having a heavy implementation
component. I'll add more project ideas as I come up with them.
- Most database research topics that you would like to pursue. Keep
in mind that I do mean research topics; implementing a database
application does not qualify. Feel free to send me mail or come by to
talk about what qualifies as a good project.
- Implement a Datalog to SQL converter. Detail can be found here, and some code that might help can be found here
- My students and I often need to match schemas. There are a
number of papers that do this, along with some open source
implementations of the ideas of these papers. Look at some of the
papers and/or implementations that are available, and find some
algorithms to implement/install on one of the machines in the Data
Management and Mining lab and compare and contrast how actually
using one of these systems works.
- I am working on a project to build data warehouses top down. As
part of this, we have a number of sub-tasks that are of about the
right size for a course project for 504. Note that each of
these is about the right size for a project - there's no reason to do
all of them!
- We are building the storage system for our data warehousing
project on top of Mondrian. In the setup files,
there is a file "FoodMart.xml" which describes the schemas
of the tables in the ROLAP. In our project, we have our own Storage
Data Layer (SDL) which describes the schema of the tables in the data
warehouse. Find the code in Mondrian which parses this XML file and
creat a new class to parse SDL.
- Mondrian has a structure to describe the parsed parts of MDX.
Track the code to know how this structure is translated to SQL with
the schema "FoodMart.xml". Collect the related SQL queries
and show how they are generated.
- Do a survey on the query processing of MultiDimensional
Expression (MDX), especially on how to translate MDX to SQL on ROLAP
- I am starting a new project on helping users query data with
large and complex schemas. As part of this, we have a number of
sub-tasks that are of about the right size for a course project for
504. Note that each of these is about the right size for a
project - there's no reason to do all of them!
- Helping users to create an ontology or schema is a well understood
process. Explore the best methodologies for doing so, especially
focusing on open source software.
- Throughout this course, we'll talk about how the concepts
that we study relate to your data. Choose some part of your
data that is difficult to manage using current data management
techniques/software. Describe what would need to change in order for
your data to be managed effectively. Relate to readings both in class
and out of class.
A word on plagiarism
Your project, as with all of your work, is to be your work. If
you take ideas from anywhere else, you have to cite them, and
that if you take words from somewhere else, they have to be
quoted and cited (taking names of things is okay without quotes as
long as they are well cited, but if you're taking more than that, you
need to have it in quotes). Copying other people's text or figures
and claiming it as your own is not okay; it is plagiarizing.
What does this mean precisely? Let's say that this webpage is your
source . If you were writing something about the first paragraph,
it might look something like the following:
504 includes a class project which can be done either individually or
in groups . Overall, it shouldn't be too bad, in particular, "it
should not eat your life".
Note that the first sentence is paraphrased, so it has just been
cited. The second sentence contains a direct quote, so it has been
put in quotation marks along with having a citation.
If you find yourself thinking "there's no point in my writing this
differently, the source that I'm looking at has written it better than
I could", I offer you the following words of wisdom (1) I don't care
if they wrote it better,
you can't plagiarize (2) in each case where I have detected
plagiarism, the plagiarized sections are the WORST part of the paper,
since they are generally just cut and pasted from other sources
without regard to the context that the project is supposed to be about.
So do us both a favour, save us both a lot of grief, and don't do it.
You'll learn more and turn in a better result.
If you are looking for relevant papers, here are some suggestions:
For any source, you want to make sure that you're reading the best
papers. One way that will often, though not always, lead you in the
right direction, is to look at the highly rated venues. In data
management, some of those are:
is a fantastic bibliography and link to papers for database and logic
- Google Scholar also has
a search engine that can be quite helpful since it indexes more than
just the metadata about the paper
- PODS (theory)
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