A Web Rules WG Charter Focus

Strawman ProposalVersion 1.1, April 30, 2005

This Version Prepared by:Benjamin Grosof, Harold Boley, Michael Kifer, and Said Tabet

of The RuleML Initiative (http://www.ruleml.org).Incorporating Comments by Ed Barkmeyer.

***Further revisions to be incorporated from community discussion.***

Modified from earlier version in RuleML Position Paper [96] of the W3C Workshop on Rule Languages for Interoperability, 27-28 April 2005.

Responsive to the discussion from that Workshop, and from the WSMO-RuleML-SWSI Face-to-Face Meeting of 26 April 2005.

“WG” above = W3C Working Group

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The Web Rule Language in its Context

XML

URIUnicode

RDF(S)

OWLRules

FOL++

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Semantic Interoperability Principles - high level

• Conclusions sanctioned do not depend on how executed, e.g., forward chaining has same semantics as backward chaining

• “Reaction” rules, that perform side-effectful actions, have a semantics which cleanly extends the basic case of rules that do not.

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Focus Overall of WG• Kernel based on logical KR

– Semantics, syntax, layering: for that kernel– Rudimentary rule management: e.g., queries, answers, premises, conclusions, updates to

premises, ruleset definition, importation of rules, simple versioning, simple provenance

•Use Cases from Business Processes, Services– Policies, in particular– Support Semantic Web Services requirements, in particular

• Integrate Rules and Ontologies– Interoperate with OWL, in particular– Represent Ontologies as Rules, in particular

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Rule Communities Served

• Semantic Web – general, using XML and/or RDF encoding

– RDF- and OWL-centric, in particular– Logic Program based, in particular

• Business Rules– general, based on existing rule-based– Production Rules, in particular

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Kernel KR FocusDeclarative Logic Programs expressiveness including 1. Datalog Horn LP (N-ary predicates supported)

2. + scoped default negation applied to atoms a. simple extensional

b. more general (allowing inferential chaining to establish the atom in question -- subset of, or full, Well Founded semantics)

3. + procedural attachments (external calls) a. actions (side-effectful – external) b. tests (side-effect-free queries) 4. + logical functions, incl. for object creation, skolemization

a. limited initially (to ensure finite/tractable forward inferencing)

b. more general (e.g., for backward chaining, “sugar” features)

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Kinds of Rules & Rule Systems Translatable/Reducible to Kernel

Most other wish-list features can be expressively reduced to this core KR abstraction, for which

Situated Ordinary Logic Programs can provide the semantics theory

• OWL: large subset, • OWL ontology integration via overlap of LP with Description Logic (e.g., use Description Logic Programs V2, with integrity constraints, skolemization, equality, passing of derived facts)• SWRL: large subset • Production Rules cf. PRRuleML: large subset (Production Logic Programs)• Decision trees• Decision tables• “Sequential” rules cf. PRR: [**probable, need to understand

better]• Prolog: the pure subset (which is large)• SQL relational databases: large subset (incl. all core)• Event-Condition-Action rules: large subset

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Those are translatable/reducible because the following are …

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Additional “Sugar” Features that are

Translatable/Reducible to KernelMost other wish-list features can be expressively reduced* to this core KR abstraction, for

which Situated Ordinary Logic Programs can provide the semantics theory (* with tractability, known techniques).

E.g., much or all of the expressiveness in the following.

•RDF facts •Frame syntax•Slotted syntax•Lists•(N-ary predicates if restrict core to 2-ary)•RDFS-DL simple ontologies•Datatyping: basic

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Sugar Features II•“Else” part of if-then-else•Courteous prioritized defaults, incl. declarative priorities, limited strong/classical

negation, prioritized conflict handling, paraconsistency

robustness

•Default inheritance cf. Object Oriented programming, “frame” languages

•“Hilog” – quasi higher order syntactic sugar•Lloyd-Topor•Integrity constraints that report violations•Anonymous existentials, blank-nodes, limited

skolemization•“Crud” – create update delete, cf. Production Rules (restricted)

•“Assert”, and basic “retract”, cf. Production Rules (restricted)

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Sugar Features III

•Reification, basic•User equality, basic aspects •Equations, basic•Built-ins (side-effect-free functions/operators, read/write)

•Access to surrounding object-oriented data environment, cf. OO Production Rules

•Ontological context translation & mediation•Contextual selection conditions for whole rulesets•“Rules flow”: some (e.g., sequencing of rule groups)

•… probably some more things we forgot to list here …

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The Web Rule Language in its Context

XML

URIUnicode

RDF(S)

OWLRules

FOL++

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Layering Relationships wrt existing Semantic Web Standards

subsumes (expressively) layers-on (makes use of) overlaps-with (expressively)

RDFS-DL

XML

OWL-DLDLP

Rules KernelSWRL

overlaps

RDF

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Sugar Features vs. Kernel

•“Sugar-enhanced” Languages can be translated into the kernel.– I.e., Sugar Features can be implemented/supported

via translators– Including as “best practice”, etc.

•Could consider doing some of them as part of WG proper– E.g., basic set of datatypes

•… But it’s not as crucial

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Deliverables Desired

•Abstract syntax•Semantics•Layering definitions: e.g., Datalog Horn layer

•Concrete syntax: – Markup syntax in XML– RDF (e.g., RDF/XML) – Human-readable presentation (non-XML) syntax

•UML/MOF metamodel•Some light ontology about rudimentary rule

management, incorporated into the above– E.g., to enable representing provenance, or expressive

restrictions met, about a particular rulebase

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Supported Tasks & Kinds of Knowledge

•Policies: authorization, contracting, security, privacy, monitoring, advertising, regulations, governance, …

•Validation: integrity, notification, …•Business Processes, Workflows, Protocols, …

– Process modeling: Abstract State Machines, Pi-Calculus, …

•Semantic Web Services•Ontologies•Mediation: map between ontologies/contexts •…