Abstract-Big Data researchers are dealing with the Variety of data that includes various formats such as structured, numeric, unstructured text data, email, video, and audio. The proposed Semantic Extract-Transform-Load (ETL) framework that uses semantic technologies to integrate and publish data from multiple sources as open linked data provides an extensible solution for effective data integration, facilitating the creation of smart urban apps for smarter living.
With the increasing popularity of Web services and Service-Oriented Architecture, we need sophisticated infrastructure to discover and compose Web services. Dynamic Web service Composition will gain wider acceptance only when the users know that the solutions obtained are comprised of trust-worthy services. In this paper, we present a framework for a Trustbased Dynamic Web service Composition that not only uses functional and non-functional attributes provided by the Web service description document but also filters and ranks solutions based on their trust rating. With the increasing popularity of Web-based Social Networks like Linkedin, Facebook, Orkut, and Twitter, there is great potential in determining the trust rating of a particular service provider or service provider organization using Social Network Analysis. We present a technique to calculate a trust rating per service using Centrality measure of Social Networks. We use this rating to further filter composition results to produce solutions that are comprised of services provided by trusted providers.
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