Semantic Web challenges 2009

Here are my current thoughts about the challenges facing the Semantic Web, vintage January 2009:

• Mind the Gap
• Thesis: There is a dramatic semantic gap between how users think and communicate about knowledge and the mechanisms that the Semantic Web supports for organizing knowledge.
• Superset of the semantic data mining problem
• How to jump from comfort with natural language to comfort with the Semantic Web
• Extent to which the user "sees" the Semantic Web as opposed to the Semantic Web simply being more power "under the hood" in a completely transparent manner
• Mind the Gap II
• How do we map and transition between natural language and the Semantic Web
• How to represent natural language in the Semantic Web
• Concepts, statements, reasoning, processes, prose passages, stories, outlines
• Semantic search engines
• Not just raw text, semantic inferences as well
• No single best form for database, need open access to create specialized databases
• Inference Broker
• Need for inference brokers to mediate between creators of knowledge and users of knowledge. Due to:
• Desire for privacy
• Protection of intellectual property
• Massive scalability requirements - divide and conquer
• Division of labor, factoring large problems into smaller problems
• Social structure of knowledge
• Individuals have only some of the puzzle pieces of knowledge
• Propositions of uncertain classification
• Social groups aggregate and classify knowledge
• A medium for intelligent agents
• Software agents can act more intelligently with a richer, knowledge-centric information stream
• Statements that are not strict, objective facts
• Personal facts, opinions, speculation, gossip, questions
• "Creations" - text, graphics, images, audio, video [? Separate challenge?]
• False statements
• May be outright lies, deceptions, misunderstandings, misstatements, changed information
• Medical record difficulties
• Pen on paper still most convenient for input
• Quick human scan of paper still most convenient for browsing
• Input decision process still far too intrusive
• Semi/un-structured data still far too inconvenient
• Distributed resource storage
• Extremely diversified storage to assure timely and efficient access
• Needs to be part of net infrastructure that is automatic and not subject to human whim and error
• Robust personal and organization identity, as well as roles and interests
• Authority and provenance identification and tracking
• The cost of knowledge engineering, especially maintenance and testing
• Who can really afford it?
• Semantic matching challenges
• Apparent differences that are easily bridged by a human
• Subtle or apparently insignificant distinctions that a human would say are too significant for a match
• For example, improper reuse of a resource for a different "meaning"
• Incomplete matches due to cultural differences
• Concept matches but with differences in contractual commitments (for services)
• Distributed semantic matching/mapping services
• Manual creation of libraries of semantic "logic" services for bridging semantic gaps - hide the details for how to get from "A" to "B"
• Support for time and version dimensions of information

-- Jack Krupansky