Presentation on theme: "The Business Significance of Upper Ontology Mills Davis Project10X"— Presentation transcript:
The Business Significance of Upper Ontology Mills Davis Project10X
1/26/ Copyright MILLSDAVISPage 2 Topics What are semantic technologies? Why now? What capabilities make semantic technologies different? Where is the market going? Role of upper ontology
1/26/ Copyright MILLSDAVISPage 3 What are Semantic Technologies? A shift in paradigm, technology & economics
1/26/ Copyright MILLSDAVISPage 4 Semantic Technologies: Representing meanings & knowledge about things so both computers and people can work with it
1/26/ Copyright MILLSDAVISPage 5 So, what do semantic technologies do?
1/26/ Copyright MILLSDAVISPage 6 Semantic technologies model knowledge about infrastructure, information, behavior, & domain expertise separately from programs and data…
1/26/ Copyright MILLSDAVISPage 7 Knowledge Plane: Semantic technologies affect all layers of the IT stack
1/26/ Copyright MILLSDAVISPage 8 Semantic Bandwidth: More m etadata, semantic modeling & knowledge representation, more reasoning capability
1/26/ Copyright MILLSDAVISPage 9 Semantic Capabilities: Meet challenges of development, infrastructure, information, knowledge, and behavior
1/26/ Copyright MILLSDAVISPage 10 Why now? Need to solve problems of scale, complexity, function, performance, and agility… SCALECHANGEMANAGEMENT COMPLEXITY
1/26/ Copyright MILLSDAVISPage 11 Why now? Need to improve economics and reduce risks across all stages of the solution lifecycle
1/26/ Copyright MILLSDAVISPage 12 Why now? Issues of national significance demand solution Examples: Scientific method for in silico research Semantic interoperability of systems and information Multi-lingual computing
1/26/ Copyright MILLSDAVISPage 13 Where are we headed? Value gains from two-fold to more than 100 times
1/26/ Copyright MILLSDAVISPage 14 Conclusion Where we are Today, semantic technology is a tiny fraction of the $1.2T ITC market. Information technologies, stack architecture, and procedural algorithmic programming paradigms dominate. Where were going Near-to-mid-term, look for rapid uptake of semantic web and related open standards to solve system plumbing and information interoperability problems. Focus is net-centric infrastructure, knowledge work automation, subject ontologies, and social networks. Still issues of scale and complexity. Where were really going Over the next decade, towards universal knowledge technology, executable domain knowledge, & systems that know and learn.