Showing papers by "José Luis Ambite published in 2004"
TL;DR: This paper discusses about retrieving and semantically integrating heterogeneous data from the Web and its uses in semantic Web technologies.
Abstract: Building Finder uses semantic Web technologies to integrate different data types from various online data sources. The application's use of the RDF and RDF data query language makes it usable by computer agents as well as human users. An agent would send a query, expressed in terms of its preferred ontology (schema), to a system that would then find and integrate the relevant data from multiple sources and return it using the agent's ontology. We discuss about retrieving and semantically integrating heterogeneous data from the Web.
72 citations
01 Jan 2004
TL;DR: This paper introduces a novel technique termed tuple-level filtering that optimizes the execution of the composed web services by reducing the number of web service requests and combines it with a technique that includes additional webservice requests in the composition in order to improve filtering and further optimize the execution.
Abstract: In this paper we show how data integration techniques can be used to automatically compose new web services from existing web services. A key challenge is to optimize the execution of the composed web services. We introduce a novel technique termed tuple-level filtering that optimizes the execution of the composed web services by reducing the number of web service requests. Moreover, we combine the tuple-level filtering algorithm with a technique that includes additional web service requests in the composition in order to improve filtering and further optimize the execution. Our initial experimental evaluation shows that our optimization techniques can reduce the execution time of the composed web services by up to two orders of magnitude.
57 citations
24 May 2004
TL;DR: In this work on the Argos project, techniques to automatically create computational workflows in response to user data requests are developed, which represent both data access and data processing operations as web services.
Abstract: Many scientific problems can be modeled as computational workflows that integrate data from heterogeneous sources and process such data to derive new results. These data analysis problems are pervasive in the physical and social sciences, as well as in government practice. Therefore, techniques that facilitate the creation of such computational workflows are of critical importance. In our work on the Argos project we are developing techniques to automatically create computational workflows in response to user data requests. As a unifying paradigm, we represent both data access and data processing operations as web services.
15 citations