Summary of Response to 5 Research Challenges of the Semantic Web

• Lack of Metaphorical Speech and Time
• Infrastructure
• Usability (2 mentions)
• Schema / Ontology Mapping
• Trust / Privacy (2 mentions)
• Data Linking & Maintenance
• Data Management
• Getting SPARQL as stable, useful and ubiquitous as SQL ASAP
• Usable User Interfaces
• Multi-endpoint queries
• Agency-ready ™ development tools

Knowledge System Architecture Vision – Some Points for Consideration

1. The idea is to capture all the knowledge that has been generated in a particular domain in a way that it can be accessed by both humans and machines.

2. We also want to create tools that will allow new knowledge to be added as it is generated.

3. Maybe at some point in the future dissertations, theses, and textbooks actually are generated from the system as output rather than inputs.

4. Yellow shading in the sketch indicates the sources of data, information and knowledge that will be considered as sources to begin to populate the knowledge base.

5. The ontologies represented in dark green will provide the structure that is used in the knowledge base, and will be used in the knowledge extraction and knowledge organization modules.

6. The two modules in light green are sets of tools that need to be developed.

7. The Knowledge Extraction module involves methods and techniques to be used to extract the knowledge from the different sources and put it in a form that the Knowledge Organization module can handle. It is likely that because of the diversity of the sources that several tools will have to be developed.

8. The Knowledge Organization module is a tool that will organize the knowledge that is extracted and converts it to the form for it to reside in the Knowledge Base.

9. The Knowledge Base is organized using the structure provided by the ontologies and is in a form that it can be queries by humans or by intelligent agents.

10. Query tools will be developed for both humans and intelligent agents.

11. Tools will be developed to generate university courses and short courses to specifications.

A Vision for a Knowledge System Architecture

The explosion of data availability, the need to bring relevant data and knowledge to decision-making, the scarcity of technical professionals in the engineering disciplines dealing with Energy and the developments towards the Semantic Web make for a “perfect storm” of opportunity for the development of an Ontology-based Intelligent Energy Knowledge Management System.

The purpose of this brief note is to present a sketch of an architectural vision so we can begin to discuss the various tools that need to be developed over time to achieve our vision.

I present the sketch and nothing else at this point to invite contributions and comments on the architecture itself as well as the developments necessary to make the vision a reality.

The sketch is in the form that can be used in any discipline. We intend to use it in the Energy industry.

 Emilio J. Nunez
Enunez23@gmail.com