Automatic Discovery and Inferencing of Complex Bioinformatics Web Interfaces
The World Wide Web provides a vast resource to genomics researchers in the form of web-based access to distributed data sources--e.g. BLAST sequence homology search interfaces. However, the process for seeking the desired scientific information is still very tedious and frustrating. While there are several known servers on genomic data (e.g., GeneBank, EMBL, NCBI), that are shared and accessed frequently, new data sources are created each day in laboratories all over the world. The sharing of these newly discovered genomics results are hindered by the lack of a common interface or data exchange mechanism. Moreover, the number of autonomous genomics sources and their rate of change out-pace the speed at which they can be manually identified, meaning that the available data is not being utilized to its full potential. An automated system that can find, classify, describe and wrap new sources without tedious and low-level coding of source specific wrappers is needed to assist scientists to access to hundreds of dynamically changing bioinformatics web data sources through a single interface. A correct classification of any kind of Web data source must address both the capability of the source and the conversation/interaction semantics which is inherent in the design of the Web data source. In this paper, we propose an automatic approach to classify Web data sources that takes into account both the capability and the conversational semantics of the source. The ability to discover the interaction pattern of a Web source leads to increased accuracy in the classification process. At the same time, it facilitates the extraction of process semantics, which is necessary for the automatic generation of wrappers that can interact correctly with the sources.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15020371
- Report Number(s):
- UCRL-JRNL-201611; TRN: US200517%%529
- Journal Information:
- World Wide Web, Journal Name: World Wide Web
- Country of Publication:
- United States
- Language:
- English
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