Enterprise Integration course (CSCI 8350)Projects for Fall 2003

Title SQUID-WS: Semantically Querying the UDDI for Discovering Web Services
Authors Preeda Rajasekaran, Rohit Aggarwal, Frederick Maier, Matt Ross
Keywords Web Service Discovery, Semantic Web, Semantic Annotation, UDDI, WSDL, Ontologies, OWL
Project Links Project Page           Final Report
Abstract SQUID-WS is a system utilizing semantic annotation of web services to increase the accuracy of web service discovery. Service providers and requestors specify characteristics of web service operations using a common ontology (OWL ontologies are used), and a matching engine is used to match specifications. An inference engine is used to determine whether service advertisements meet additional constraints detailed by the requestor.
   
Title TRAKS1: Terrorist Related Assessment using Knowledge Similarity
Authors Boanerges Aleman-Meza, Chris Halaschek, Satya Sanket Sahoo
Keywords Anti money laundering, semantic similarity, templating, terrorist detection, early warning system, similarity, semantic Web
Project Link Project Page          Final Report
Abstract With the advent of current technology, data is now being semantically annotated. Hence, there exist many sources that describe different characteristics of a given entity in diverse domains. We plan to use (and if needed extract) semantically marked up data along existing data from interested institutions to find potential terrorist activities. Our proposed approach will employ past known money laundering, id theft, and terrorist attack models/templates to discover potential threats in the knowledge base based on novel semantic similarity algorithms that we will develop. An example data source for past real money laundering operations is available at http://www1.oecd.org/fatf/ . We aim to showcase these capabilities with a prototype that makes use of data represented in RDF or possibly OWL.
   
Title SEMPL-A SEMantic PortaL for the LSDIS Lab
Authors Matt Perry, Eric Stiles, Deepti Chafekar, Cary Pennington, Chris Bennett
Keywords Semantic Web, Semantic Portal, Ontology, Metadata
Project Link Project Page            Final Report
Abstract Semantic web technology is intended for the retrieval, collection and analysis of meaningful data with significant automation afforded by machine understandability of data. As one illustration of semantic web technology in action, we present SEMPL, a semantic web portal for the LSDIS lab at the University of Georgia. SEMPL uses an ontology driven approach to provide semantic browsing and querying information in the Semantic Web area and LSDIS lab. By using the ontology based information integration technique, SEMPL can specify the context of a particular piece of research information, annotate web pages and provide links to semantically related areas enabling rich contextual retrieval of information. Through ontology-based browsing at the schema level, users can see a clearly organized and easily traversable presentation of all the content in the portal. Advanced searches based on domain specific attributes defined in the ontology provide users with more precise and relevant information than would be provided with traditional keyword-based searches. Also, when documents are viewed, links to other relevant resources are presented that are based on precisely defined relationship instances in the ontology. This paper describes features of SEMPL, its implementation details, and a brief description of some of the technologies used.
   
Title PerCuro-A Semantic Approach to Drug Discovery
Authors Meenakshi Nagarajan, Karthik Gomadam, Hongyu Yang
Keywords Drug Discovery, Drug, Target, Pathogen, Chemical compound, molecules, functional group, Multi-Ontology, RDF, RQL
Project Link Project Page           Final Report
Abstract Drug Discovery is a domain that presents an excellent case for the application of semantic techniques in Bioinformatics. The domain is one of the most ancient characterized by rich voluminous data. All the information in this domain serves as a basis for making decisions to advance and prioritize potential leads in the process of
discovering a drug. Clearly, capture and integration of such information of a varied nature has been increasingly critical. The process of discovering a drug is therefore very complicated and requires investment of time, money and effort. The possible use of semantic techniques as a way to speed up the process of target identification has been our primary motivation for this project. Here we present a small prototype system, wherein we exploit the relationships between various domains in drug development while trying to answer questions significant to speeding the process of
drug discovery. The software has been named PerCuro, which in Latin means to Cure.
   
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