Biological Data Extraction and Integration — A Research Area Background Study

My research field is highly diverse. It interweaves many different areas in information technology and bioinformatics. The system I propose to implement can automatically locate, understand, and extract online biological data independent of the source and also make it available for Semantic web agents. This research field requires background knowledge from (1) Information Extraction, (2) Schema Matching, (3) the Semantic web, (4) Data Integration, and (5) Bioinformatics. 1 Information Extraction Currently, with the fast development of the internet, both the amount of useful data and the number of web sites are growing rapidly. The web is becoming an increasingly useful information tool for computer users. However, there are so many web pages that no human being can traverse all of them to obtain the information needed. Even in the narrow domain of molecular biological data, no human can traverse all the pages that may be of interest for finding needed information. A system that can allow users to query web pages like a database is becoming increasingly desirable. One possible strategy is to extract useful information from different web pages to populate databases for further handling. I survey information extraction techniques in the following three categories: (1) traditional information extraction; (2) hidden web crawling; and (3) biological data extraction. • Traditional information extraction. For traditional information extraction, I present five major data extraction tools. Each tool represents a different major way of doing information extraction. Lixto [BFG01] is a tool for supervised wrapper generation and automated web information extraction. It generates wrappers semi-automatically and interactively by creating patterns in a hierarchical order. The user can define extraction patterns