Semantics: What it Means for Data Professionals

Semantic Technology is about to explode in the marketplace: independent projections suggest a $60 billion industry by the year 2010. The good news for the DAMA community is that people with Data Modeling and Analytic skills are in the best position to capitalize on this trend.

Semantics is the study of meaning. Semantic Technologies are those that take advantage of a more formal, and computer interpretable, expression of the meaning of the information stored in our systems. With Semantic Technology we will be tagging meta data as well as instance data with ontologically agreed terms, in a way that our systems can use to improve search, integration and more. This tutorial is designed to bring data professionals up to speed on Semantic Technologies and how they will transform pretty much all of the technologies we use.

The tutorial will cover:

• What are semantics, and why should I care?
• Taxonomies and Ontologies: foundational technologies
• RDF and OWL: the open standards for the Semantic Web
• Semantic Brokers: how they are changing the face of EAI
• Semantic Search: getting beyond keywords
• Structured and Unstructured information: how to bridge the gap.
• Underlying Semantic Disciplines, including Category and Prototype Theory

This tutorial is meant to provide some insights that can be applied immediately by any data professional who deals with semantics (and all of us do). It is aimed at changing the way you think about information.