1. A Web Rules WG Charter Focus Strawman Proposal Version 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 Grouphttp://www.ruleml.org96

2. 1 The Web Rule Language in its Context XML URIUnicode RDF(S) OWLRules FOL++

3. 2 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. 3 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. 4 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. 5 Kernel KR Focus Declarative 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. 6 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

8. 7 Those are translatable/reducible because the following are …

9. 8 Additional Sugar Features that are 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 (* 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

10. 9 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)

11. 10 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. 11 The Web Rule Language in its Context XML URIUnicode RDF(S) OWLRules FOL++

13. 12 Layering Relationships wrt existing Semantic Web Standards subsumes (expressively) layers-on (makes use of) overlaps-with (expressively) RDFS-DL XML OWL-DL DLP Rules Kernel SWRL overlaps RDF

14. 13 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 its not as crucial

15. 14 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

16. 15 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 …