a web rules wg charter focus strawman proposal version 1.1, april 30, 2005 this version prepared by:...

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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

2

The Web Rule Language in its Context

XML

URIUnicode

RDF(S)

OWLRules

FOL++

3

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.

4

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

5

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

6

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)

7

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 …

12

The Web Rule Language in its Context

XML

URIUnicode

RDF(S)

OWLRules

FOL++

13

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

15

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 •…

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