CS 4250: Introduction to Database Management Systems

Project Overview

General Description

• Identify an application area,
• Model the data stored in the database,
• Design, normalise, and perfect the relational database schema,
• Write the SQL commands to create the database, find appropriate data, and populate the database, and
• Finally, write the software needed to embed the database system in the application.

A group of two to four students (ideally, three) should do each project. You are free to choose your own project members; if you would like the instructor to assign you to a group, send an email. Each of the steps above will be a specific project assignment or two. You will get detailed instructions with each assignment. Each group should turn in a single solution to each assignment. Every member of the group will get the same grade.

N.B. There will be a peer evaluation component of project grades. For every component of the project, each group will be required to specify what each of the members of the group contributed to the group work.

Project Ideas

1. Books Database: This domain is a popular one. Just look at barnesandnoble.com or amazon.com for excellent examples. You could model entities such as books, their authors, topics (which may be a complex hierarchy). You may also model various attributes of the authors and the institutions they belong to. You can support a service for buying and selling used books or books used in specific university courses. Your system can build a personal profile of people (and the books they like) and your database application could form the basis for a "recommender system", such as those supported by the commercial sites. The goal here is to "cluster" similar preferences together and the system can then make recommendations: "Since you liked Shakespeare's Romeo and Juliet, I recommend that you try Shakespeare's Antony and Cleopatra".
2. Movies (or Television Shows) Database: There are several excellent movie resources on the web, such as the hollywood.com movies site or the Internet Movie Database. You could model entities such as movies, their actors, directors, genres, playing times, and reviews. There are several sources on the web from which you could get data to populate such a database. You can support various queries such as finding specific playing times, or finding movies playing in Turlock directed by a given director. You can also support updates to the reviews section of the database (e.g., viewers giving their own opinions). Another functionality is to provide personal profiles of people (i.e., the movies they like) and then try to recommend movies to them based on profiles of viewers with similar tastes. You could also create a database of Oscar or Golden Globe nominations and awards and answer queries such as "Find all the sitcoms that have been nominated three years in a row".
3. Research Literature: This domain involves modeling research publications. You need to identify the title of the publication, the forum it was published in, the authors, topics, keywords and related subtopic areas. This is a big business now (under the name of digital libraries). For example, the ACM Digital Library provides a beautiful searchable index (and retrievable repository, but that is beyond our scope) of nearly all of the publications of ACM. If you use this domain, then there are a lot of available resources for you to use. The ACM Computing Classification System provides a convenient hierarchial meta-index that you can use to organize your class hierarchy etc. If you are interested in a smaller domain, then the DBLP Bibliography Site provides a searchable facility for publications related to the database and programming communities. At the end of the day, you could identify papers written by a particular person at a particular place or ones in a narrowly defined area.
4. Research Literature, the Dark Side, aka Retraction Watch: This domain involves modeling retracted scientific publications -- the mistakes, misunderstandings, and occasional outright fraud that can occur in any competitive publication field. The Retraction Watch web site gathers information on cases where a scientific publication was declared "unpublished" and documents why the publishers retracted the paper. The Retraction Watch web site once received a generous grant to help them create a database of scientific paper retractions. You could try to design that database.

   Or you could find another web site that gathers up socially useful information and try designing a database for their worthy cause. Possibilities include a database of adoptable stray animals, of endangered animal sightings in the wild, of homeless shelter locations, of food banks for humans, of locations of weeds in the wild that are food sources for endangered creatures (like Monarch butterflies), of museums that store old computers, ...

5. Municipal Data: A number of different cities and counties, like Santa Clara County, Los Angeles County, and Sonoma County, are putting municipal data on-line for anyone to access. Data on business, education, health, the environment, transportation... all the information governments use to help their areas thrive. You could model an open data web site, and include in your model the types of data available, areas of the county / city the data applies to, the people and projects that generate the data sets, existing applications available to analyze some of the data sets, and so on.
6. Apartment Homes: This domain would require modeling apartments and their attributes, areas of town and their various characteristics (e.g., Modesto Area Express bus lines, crime rates, distance from various landmarks). You would provide an interface for offering apartments for rent, finding apartments based on various requirements ("pets allowed + rent less than $800 + close to campus").
7. Others: Of course, there are a whole host of other ideas such as personal photo collections, bank accounts, Olympic Games data, World Cup data, election results, Senate demographics, car rentals, auto insurance, consumer products, silly statistics, "match-making services" and so on. Use your imagination.

Credit and thanks are due to Dr. Murali at Virginia Tech for inspiration and documentation.

Last modified: Aug 2024