Resource Capability Discovery / Description Management System-Labeling Anonymous Dataset for Web Data Integration Emdad

Formulating and executing queries over distributed, autonomous and heterogeneous resources is an important topic within e-Science in general and Bioinformatics in particular. The advent of the Internet and the Web and their subsequent ubiquity have brought forth opportunities to connect Biological information sources across all types of boundaries. Examples of such information sources include databases, XML documents, and other unstructured sources. Uniformly querying those information sources have been extensively investigated in this research. We have surveyed the current research on the fundamental problems to efficiently process queries of Web Data integration systems. Bioinformatics domain has been chosen to illustrate the query processing capabilities over the heterogeneous information sources. Although our application domain is Bioinformatics, our approach is not limited to a specific domain. We surveyed different approaches to data integration such as warehouse, mediator-based, navigational, vertical integration and horizontal integration. The ontology is also central to the query processing and reconciliation of heterogeneities. For efficient query processing, we advocate for the selection of relevant information sources and the use of meta data. We propose that the current data integration approaches should be enhanced by ontological knowledge and ISA relationships and inter-ontology mappings in ontologies should be explored. The transition of the World Wide Web from a paradigm of static Web pages to one of dynamic Web services provides new and exciting opportunities for Bioinformatics with respect to data dissemination, transformation, and integration. Integration of data and service from heterogeneous sources demand significant advances in middleware system, which we plan to implement. The web document can be seen as a structure composed of different types of information units (such as forms, tables, titles and paragraphs). Increasing amount of data on the web highlights the need for its efficient and effective management. In this light, numerous researchers have proposed to use RDBMSs to store and query web data using the SQL language. Using relational database technology as a basis for storing and querying web data is a reasonable choice as this technology is well understood and known to have good performance. Scientific workflows in Life Sciences are usually complex as they use many online databases, analysis tools, publication repositories and customized computation intensive desktop software in a coherent manner to respond to investigative queries. Most often, these investigative queries are ad hoc, and ill formed or even one time queries. In such cases, developing customized workflows becomes a major undertaking which is truely expensive, prohibitive and resource intensive. High development costs often act as deterrent to many interesting queries and thus act as barriers to promising ontime scientific discoveries. In this research proposal, we introduce a new paradigm, resource capability discovery/ description in complement to our new scientific workflow query language, called BioFlow, that exploits many recent developments in Internet communication, database features, wrapper and mediator technology, ontology, scientific workflow and web data integration. We will demonstrate that fairly complex web-based workflows can be effortlessly and declaratively expressed in an ad hoc fashion. We also report a prototype implementation of the system in Java that features most of the systems powerful features as a proof of feasibility of our approach. We have been working toward developing a framework for automated information extraction from Internet documents. Specifically, we are developing an intelligent column name assignment algorithm for online table wrappers. In most web documents, information is generally displayed