1 / 4

Languages & Inference

Explore the need for logic, legacy data storage, inference services, modeling styles, and industry involvement for the Semantic Web. Identify urgent needs, low hanging fruit, and killer applications. Discuss infrastructure development vision and funding models.

ldisalvo
Download Presentation

Languages & Inference

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Languages & Inference • Appropriate layeringDo we need a logic?Do we need Description Logic? • Legacy data; database storage vs inference • Tolerant/anytime inference Which reasoning services to support • Support for modelling styles Strategy Tool building • Education & outreach • XML vs. RDF (role of XML Schema) • Consensus building • Ontologies vs. web-services • Industry involvement/adoption • Usability (end-users & developers) • Identify “low hanging fruit” • “killer applications” • Transition/bootstrap strategies • Maintaining common vocab’s • Identify urgent needs • Identify “low hanging fruit” • Identify usage scenarios • Infrastructure development

  2. vision urgent • Interoperability (= main goal of Semantic Web) • Why semantics? (interoperability “the next level up” from TCP/IP, HTML, XML, …?) • Defined w.r.t. set of operations, w.r.t. identity • common standards or translations and mappings • Multiplicity of languages, • too high step-in cost • layering of languages (*, +), • opportunities for merging? (workshop series)(e.g. XML Schema, RDF Schema, Topic Maps)(ditto for query lang’s, tranformation lang’s, path models). • Reconciling modelling styles/paradigms • Axioms-style/frame-style(*, +) / constraint-style / rule-style • Formal differences and community aspects • Combining Knowledge Repr approach and Database approach • Different reasoning services • Querying, consistency(*), inheritance(*), matching, similarity/difference, classification/type-inference, object-identify, cycle-detection(*), anomaly-detection(*) • Tolerant inferences, levels of tolerance (some *’s) • pragmatic levels • Complexity levels • Anytime, gradual, resource bounded, continous, streaming • Notion of identity • Globally unique names, • Semantics of URI identity • Scoping, modularity, namespaces • Use-mention distinction • Rigid designators/temporal identity Easy picks(*) + longer term(+ = workshop + followup)

  3. Funding models • Needs intercontinental funding • Needs funding for production of • reports, • Teaching/PR/evangelism/proselytising • … • Project-oriented funding does not suffice Slogans/mantra’s for the Semantic Web • Low entry barrier • Construction by example (copy/paste/edit) • Incremental formalisation

  4. Relevant communities • AI/KR/KE • DB • Computational Logic

More Related