My plan for computer science research includes applying a solid experimental research methodology to database systems projects. This document describes my research methodology, includes a link to the publications from my research, and lists some general research interests.

Research Methodology

"The fundamental principle of science, the definition almost, is this: the sole test of the validity of any idea is experiment." -- Richard P. Feynman

A survey of reputable scientific journals found that computer science publications contain far fewer valid, reproducible experiments than do journals from other science fields [LHP+95]. If we, as computer scientists, are to be as effective in scientific research as are scientists from such well-established fields such as physics, biology and chemistry we must follow the scientific methods that have been developed over the centuries in the other experimental sciences. These time-proven methods include the following steps:

• Observe. Study the world. Find problems to solve that matter by looking at existing systems or develop prototypes of future systems.
• Hypothesize. Formulate scientific questions to ask. Phrase the questions in such a way that valuable information can be obtained whether the hypotheses are found to be correct or incorrect.
• Design. Define and build the experimental system. Choose the independent and dependent variables. Perform pilot tests to determine the effectiveness of the experimental system design.
• Experiment. Run the experiment under controlled conditions. Modify the parameters in such a way as to test the hypotheses.
• Analyze. Thoroughly examine the results of the experiment by applying rigorous statistical analysis on the data. Determine the validity of the hypotheses.
• Report. Communicate the research results to other scientists. Use established methods of data presentation. Present the entire experiment such that the results can be reproduced by other computer scientists.

I incorporate a strong experimental component to all my computer science research starting from laying out a clear hypothesis to perhaps the most difficult step: the setup and the running of the experiments.

Research Interests

Heterogeneous Databases Systems: design, implementation and performance of (a) algoritms for schema matching and schema integration; (b) global schema modeling; (c) querying of heterogeneous systems

Data Streams and Querying Systems: design, implementation and evaluation of querying systems for data streams

Bio-informatics: design, implementation and querying of semantically integrated databases. Includes the building of algorithms for semantic integration and querying.

Software Systems: design of software architectures that help support the automated integration and maintenance of software components.