Retrieving, Integrating and Discovering Scientific Knowledge using the Semantic Web

Lecture: 
Yes
Date: 
Thu, 2011-12-15 14:00 - 15:00
Place: 
Cyber-ShARE Center of Excellence, Classroom Bldg., Room 402

Presenter: Dr. Natalia Villanueva-Rosales
Topic:
The World Wide Web provides a platform for sharing and navigating an enormous amount of information. However, using it to answer sophisticated questions involving complex background knowledge is not currently possible. The principal reason behind this limitation is that digital information (e.g. sentences, tables, images), while machine processable, is not machine understandable. In contrast, the Semantic Web leverages current web architecture and provides the means by which explicit semantics can be assigned to raw data through ontologies that explicitly describe and relate objects using formal, machine understandable representations.
In this talk I will illustrate the use of ontologies for integrating and discovering scientific knowledge along with the challenges of manually designing such ontologies. I will further discuss an alternative approach to automatically create ontologies that represent the semantics of data stored in relational databases.
Efforts to expose the rich content currently stored in thousands of databases using the Semantic Web will allow users, in particular scientists, to be more effective in retrieving information that supports their scientific endeavors.

Biography:
Natalia Villanueva-Rosales recently completed her PhD in Computer Science at Carleton University (Canada), where she is also an ontologist researcher. She holds an MSc in Artificial Intelligence from the University of Edinburgh (Scotland), and a BEng in Computer Science from the Panamerican University (Mexico). Her current research focuses on bridging databases and the Semantic Web. Her experience includes designing ontologies, populating ontologies from heterogeneous sources (data mashups) and question answering mostly in Life Sciences domains. She has participated/supervised several projects in the areas of automated reasoning, data mining, data integration and exchange. She is passionate about improving the way that scientists retrieve and discover increasingly sophisticated knowledge.

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