The Rule Markup Initiative

The participants of the RuleML Initiative constitute an open network of individuals and groups from both industry and academia. We are not commencing from zero but have done some work related to rule markup or have actually proposed some specific tag set for rules. Our main objective is to provide a basis for an integrated rule-markup approach that will be beneficial to all involved and to the rule community at large. This shall be achieved by having all participants collaborate in establishing translations between existing tag sets and in converging on a shared rule-markup vocabulary. This RuleML kernel language can serve as a specification for immediate rule interchange and can be gradually extended - possibly together with related initiatives - towards a proposal that could be submitted to the W3C.

Rules are being used for many interconnected purposes, capturing regularities in application domains such as the following: Engineering: Diagnosis rules (also model-based approaches appreciate and combine with rules, as described by Adnan Darwiche in Model-based diagnosis under real-world constraints, AI Magazine, Summer 2000) Commerce: Business rules (including XML versions such as the Business Rules Markup Language (BRML) of IBM's Business Rules for Electronic Commerce project) Law: Legal reasoning (Robert Kowalski and Marek Sergot have been formalizing legal rules in an Imperial College group) Internet: Access authentication (Tim Berners-Lee proposed registration engines that use authentication rules such as the following: Any person who was some time in the last 2 months an employee of an organization which was some time in the last 2 months a W3C member may register.) Rather than reinventing rule principles and markups in each such community, the idea of RuleML is to 'package' the rule aspect of these domains and and make it available as an (XML) namespace, .../RuleML, which can be mixed with a namespace for natural-language (XHTML) texts and possible domain-specific namespaces (much like MathML is mixed into such domain texts).

Rules can be stated (1) in natural language, (2) in some formal notation, or (3) in a combination of both. Being in the third, 'semiformal' category, the RuleML Initiative is working towards an XML-based markup language that permits Web-based rule storage, interchange, retrieval, and firing/application.

Markup standards and initiatives related to RuleML include: Mathematical Markup Language (MathML): However, MathML's Content Markup is better suited for defining functions rather than relations or general rules DARPA Agent Markup Language (DAML): While the contributing SHOE project has permitted Horn rules and a DAML-RULES is planned, the current DAML+OIL (March 2001) does not yet include a specification of explicit inference rules Predictive Model Markup Language (PMML): With this XML-based language one can define and share various models for data-mining results, including association rules Attribute Grammars in XML (AG-markup): For AG's semantic rules, there are various possible XML markups that are similar to Horn-rule markup Extensible Stylesheet Language Transformations (XSLT): This is a restricted term-rewriting system of rules, written in XML, for transforming XML documents into other XML documents

The RuleML Initiative consists of the participants represented here by their logos.

2001-05-11: "RuleML, the emerging standards effort on XML Rules knowledge representation, continues to progress in its design -- and also in its acceptance; notably, IBM this past month joined as participant and publicly disclosed that it is prototyping support for RuleML. Presentation materials from two recent W3C meetings, and a new short overview conference paper, are now available: see http://ebusiness.mit.edu/bgrosof/#XMLRules." (Also see: alphaWorks Posting. Contact: Hoi Chan.)

Some initial steps taken by the RuleML Initiative have been to structure the area of rule markup, to raise issues and identify tasks, and to propose tentative rule tags/attributes.

The current RuleML design shows the big picture of how we conceive and formalize rule markup; this has been the basis of much of our more specific work.

2001-01-31: A preliminary RuleML DTD has been released: RuleML DTD Version 0.7.

2001-07-11: A revised DTD version has been finalized: RuleML DTD Version 0.8.

2001-09-25: A preliminary XML Schema for a Datalog subset of RuleML has been released: RuleML Schema Version 0.8.

2002-04-02: A query DTD version has been realized (cf. Queries): RuleML DTD Version 0.8.

2004-01-28: A revised DTD/XSD version has been released: RuleML Version 0.85.

2004-07-15: A stable XSD version has been released: RuleML Version 0.86.

2004-08-12: A new XSD version has been released: RuleML Version 0.87.

2004-11-02: A monolithic DTD version of FOL RuleML 0.9 has been released: FOL RuleML Version 0.9.

2005-03-01: A new XSD version has been released: RuleML Version 0.88.

2005-05-27: A new XSD version has been released: RuleML Version 0.89.

2005-11-09: A new XSD version has been released: RuleML Version 0.9.

2006-08-24: A new XSD version has been released: RuleML Version 0.91.

As in many deduction approaches, RuleML queries are regarded as headless implications, symmetrically to regarding facts as bodiless implications. They enumerate the bindings of all their free (existentially interpreted) variables.

Queries were added to RuleML 0.8 as a third top-level element of rulebases besides facts and imps (since this extension is purely additive, all queriless RuleML 0.8 rulebases should still validate). This gives us "for free" all refinements of RuleML's existing system of sublanguages via the _body role of queries: because of RuleML's DTD inheritance, additions were only required for ruleml-datalog.dtd (ruleml-datalog.dtd.txt) and urcbindatagroundfact.dtd (urcbindatagroundfact.dtd.txt). In particular, ruleml-datalog.dtd's query-extended rulebase definition is inherited by ruleml-hornlog.dtd, where queries in datalog use only inds and vars but queries in hornlog automatically also permit cterms (because hornlog atoms permit cterms).

RuleML queries are illustrated by our business-rule example discount.ruleml (discount.ruleml.txt) and by Eric Prud'hommeaux's RDF Query example wsdl-rdf-query.ruleml (wsdl-rdf-query.ruleml.txt).

This query incorporation into RuleML assumes that the sublanguage expressiveness should be the same for 'assertions' (facts and imps) and for the 'requests' (queries) on them. So, it cannot, e.g., express queries on ground triples (containing no variables) via non-ground triples (containing variables): creator.ruleml (creator.ruleml.txt). However, users can still employ one rulebase (module) with its DTD for 'assertions', and another rulebase (module) with a different DTD for 'requests'.

Via Object-Oriented RuleML (OO RuleML) frame-like knowledge representation with facts (instances) and rules (methods) is now directly supported.

ASP RuleML defines a sublanguage of RuleML for answer-set programs in XML Schema. This variant facilitates the specification of a number of ASP-related constructs in a general manner. Moreover, it constitutes a base language for specific ASP extensions, such as HEX-programs.

An experimental RDF translator for a subset of RuleML 0.7 is available in XSLT: RuleML in RDF Version 0.2. RuleML 0.8 now stands in the direct Context of RDF.

2001-06-20: Michael Sintek has implemented a (Java) parser for an RDF version of the Horn-logic subset of RuleML 0.8; it reflects an RDF RuleML syntax by (Java) classes that currently generate textual Horn clauses but could be adapted for generating the XML RuleML syntax: The FRODO rdf2java Tool. A converse translator from XML RuleML 0.8 to RDF RuleML 0.8 should be easier to write in XSLT than was possible for the above-linked RuleML 0.7 translator.

RuleML Lite has been developed basically as a RuleML subset compatible with RDF and OWL-DL that covers webized unary and binary Datalog facts, rules, and queries. The RuleML Lite design has interacted with the SWRL design via the Joint Committee.

The FOL RuleML language has been developed in interaction between the RuleML Steering Committee and the Joint Committee, with input from Simplified Common Logic (SCL). FOL RuleML shares/reuses most of the earlier RuleML LP syntax, incorporating First-Order-Logic quantifiers and disjunctions as well as equivalence and negation. FOL RuleML strives for a strict separation of declarative content from procedural (Assert, Query) performatives, as pioneered by KQML. This and further changes to the current RuleML 0.87 will also benefit other sublanguages towards RuleML 0.9, in particular the Horn logic subset. FOL RuleML is the rule component of SWRL FOL and a proposed FOL content language for SWSI. It can be viewed as a generalization of SWRL FOL in that it is an XML form of full FOL, with n-ary relations (predicate symbols) and constructors (logical function symbols).

2004-11-02: FOL RuleML 0.9 has been released, using a monolithic DTD specification.

2004-11-14: An FOL RuleML announcement has been sent.

The FLIP Group uses RuleML in machine learning: About using RuleML for expressing machine learning knowledge. In the LispMiner project work with RuleML is directed towards statistical association rules.

Since RuleML should help rule-system interoperation, (XSLT, ...) translators for RuleML rulebases are rather important. Please send us further translator pairs between your system and RuleML -- even if your translators are (still) partial.

In February 2001 Mike Dean created the first operational RuleML rulebase, GEDCOM, with rules on family relationships (child, spouse, etc.) run via XSLT translators to the XSB, JESS, and n3/cwm engines.

2001-09-17: Harold Boley has specified XSLT translators between the Horn-logic subsets of RuleML and RFML. These can make implementations of both systems available to each other and permit, e.g., a preliminary HTML rendering of RuleML rulebases. The XSLT stylesheets may also serve as blueprints for specifying further translators to/fro RuleML.

2001-09-19: Andreas Eberhart implemented an alpha version of OntoJava. The basic idea is to automatically map Protégé ontologies, instances defined in them, and RuleML rules into a sinlge Java main memory DB / rule engine that can then be used as the basis of an application. He is looking forward to hearing of your ideas and input.

2002-02-04: Andreas Eberhart extended OntoJava by reaction rules: runtime.Loader.load("http://localhost:8080/servlet/SearchGate?flight=" + F.name, false); ]]> This example loads RDF info into the DB, which comes from a kind of Web Service. So emails can be sent as well, etc. While this is not 'cross-platform', it should be interessting from an engineering point of view.

2002-07-08: Said Tabet created an XSLT stylesheet for transforming from a version of RuleML to Jess. The full Java environment for running this is available from Said Tabet.

2003-08-26: Stephen Greene has specified XSLT translators between Positional and Object-Oriented RuleML.

2004-08-12: David Hirtle has created an XSLT translator between RuleML 0.86 and 0.87 as part of the 0.87 release.

2005-03-01: David Hirtle has created an XSLT "upgrader" to translate between RuleML 0.87 and 0.88 as part of the 0.88 release. An XSLT "normalizer" for reconstructing all skipped role tags to achieve a fully-expanded, normal form is also included with this release.

2005-05-27: The XSLT "upgrader" from 0.88 to 0.89 has been created as part of the 0.89 release. An updated XSLT "normalizer" for achieving a normal form is also included.

2005-09-13: Jie Li has updated an earlier translator from RFML to RuleML as part of the ChemXelem use case.

One or more rule engines will be needed for executing RuleML rulebases. On 2000-11-15, the RuleML Initiative thus joined forces with the Java Specification Request JSR-000094 Java Rule Engine API. This cooperation will enable a direct cross-fertilization between the complementary specifications of the open XML-based Rule Markup Language and of the Java runtime API for rule engines.

2001-06-04: Jens Dietrich implemented the first complete input-processing-output environment for RuleML. To download the api (source code) click Mandarax RuleML. Any feedback is welcome! If you have problems, don't hesitate to contact Jens for assistance.

2002-03-08: Jens Dietrich has finally published Mandarax 1.6 with major improvements, including new docs and all the features discussed in the Mandarax Dagstuhl Talk. One of the new packages is xkb_b1.jar -- it contains a modular driver to translate rule bases to XML and vice versa. I.e., there are tiny adapter objects responsible for exporting/importing rules, facts, terms etc. This should enable us to set up a reference application for any new standard in hours.

2001-06-26: Michael Sintek has implemented a small XSB-based engine that can also be looked at as the first RuleML querying agent. It's a servlet (running in Tomcat) that receives RuleML rulebases in RDF RuleML syntax (since he uses The FRODO rdf2java Tool) together with some queries, evaluates them with XSB Prolog (in auto-tabling mode, which should be equivalent to bottom-up evaluation!), and returns the result as an HTML page containing the bindings as facts of instantiated queries. A future version must, of course, return a RuleML file. Simply try this URL. Click on 'example' and paste the RDF RuleML popping up into the input window (note that pasting XML/RDF cannot be directly done in IE, only in Netscape; use "view source" in IE). Alternatively, you can use the Prolog parser and RDF translator to generate the RDF RuleML. Since we cannot guarantee that the above URLs always work (server reboots etc.), this picture shows the agent in action. Any feedback is welcome! If you have problems, don't hesitate to contact Michael for assistance.

2002-02-06: Bruce Spencer further refined The Design of j-DREW, a Deductive Reasoning Engine for the Semantic Web.

2005-05-06: Marcel Ball [maball AT gmail DOT com] revised the documentation of OO jDREW, summarized in the Position Paper Implementing RuleML Using Schemas, Translators, and Bidirectional Interpreters of the W3C Workshop on Rule Languages for Interoperability.

2007-07-26: Benjamin Craig [ben.craig AT unb DOT ca] has been continuing the development of OO jDREW with a series of extended releases, and is developing the OO jDREW part of Rule Responder.

2008-06-30: A team led by Nick Bassiliades, Grigoris Antoniou and Guido Governatori has released a new version of DR-Device (version 0.81) with support for modalities and proof exporting. DR-Device is a defeasible logic reasoning system with priorities among rules, two types of negation (strong, default) and conflicting (mutually exclusive) literals. The system is implemented on top of CLIPS and has been extended to introduce rule modes that determine the modality of the conclusion and modalized literals in the premises of rule bodies. Furthermore, the system exports in a formal RuleML-like representation an explanation for the proof of the rule program conclusions. The aim is (a) to take advantage of the expressive power of modal logics to define various agent behaviors, and (b) to to increase user/agent trust towards rule-based Semantic Web applications.

The Positional-Slotted presentation, shorthand, and exchange syntax for rules (POSL) merges Prolog's positional and F-Logic's slotted syntaxes. Its need has emerged from discussions on ASCII syntaxes in the Joint Committee.

RuleML Participant Jens Dietrich's Oryx (version 2.1) has a graphical Knowledge Editor for business rules and a Repository that contains the description of predicates, functions, and database connections. "Oryx works with open XML based formats, support for the emerging RuleML standard and the open source Mandarax XKB 1.0 format is included." (http://www.jbdietrich.com).

Michael Sintek has implemented a Prolog parser and RDF translator to generate RDF RuleML.

Andreas Eberhart wrote a small tool that allows you to convert Prolog (currently, Datalog) rules to RuleML. This Prolog2RuleML tool is available both online and as a command line version.

2005-12-13: A team led by Nick Bassiliades and Grigoris Antoniou has released VDR-Device (version 0.27). VDR-Device is a visual environment for developing defeasible logic rule bases for the Semantic Web. VDR-Device integrates a graphical RuleML-compliant rule editor and a defeasible reasoning system that processes RDF data and RDF Schema ontologies. The rule editor constrains the allowed vocabulary after analyzing the input RDF Schema ontologies, preventing potential syntactic and semantic errors. The reasoning system supports all defeasible logic rule types, priorities among rules, two types of negation and conflicting literals.

2006-04-28: A Java Web Start application called TRANSLATOR has been developed by David Hirtle for translating from Attempto Controlled English to RuleML. The reverse direction, RuleML to English, is a planned extension.

A library of RuleML rulebases is being accumulated here as a collection of use cases for further design discussion and as examples for practical rule exchange (RuleML Library). The highest version of RuleML (currently 0.86) should be used whenever possible. If you have an entry, please send us its pointer. The discounting business rules example introduces some of the features: discount.ruleml (discount.ruleml.txt). 2002-03-06: Mike Dean's GEDCOM rulebase GEDCOM RuleML 0.7, with rules on family relationships (child, spouse, etc.), has been made available: GEDCOM RuleML 0.8 (View | Page Source).
This is Elina Hotman's result of having GEDCOM RuleML 0.7 (local copy: GEDCOM RuleML 0.7), first transformed by the XSLT stylesheet ruleml2rfml_gedcom.xsl (a translator version of ruleml2rfml.xsl) to the -- likewise positional -- RFML form GEDCOM RFML 0.8, and then having that further transformed by the XSLT stylesheet rfml2ruleml_gedcom.xsl (a translator version of rfml2ruleml.xsl) to the -- role-using -- RuleML 0.8 form GEDCOM RuleML 0.8.
Coincidentally, Jos De Roo used GEDCOM RuleML 0.7 to generate GEDCOM N3, from which Jonathan Borden generated GEDCOM RDFxt (www-webont-wg -- LANG: GEDCOM N3 as RDFxt). Thus, GEDCOM looks like a good benchmark for transforming between RuleML and related systems (future transformers should directly start off from GEDCOM RuleML 0.8 or higher). A draft specification for the original GEDCOM XML is available. 2002-06-24: Sabrina Scherer and Benjamin Olschok, University of Saarbrücken, in cooperation with Harold Boley, DFKI, have completed the prototype of a Rule-Applying Comparison-Shopping Agent, RACSA, which takes into account various (discount-like) rules for computing the special price a customer will be offered. RACSA is based on RuleML, Mandarax, and Java; it is currently being developed for comparing refrigerator end prices in the German and European market, but can be easily adapted to other products and/or markets. A RACSA servlet and the comparison-shopping rulebases will soon be made available here for testing. 2002-07-08: Said Tabet created an XSLT stylesheet for transforming from a version of RuleML to Jess. This is exemplified by an animal rulebase transformed from its neutral RuleML version (rules1.xml.txt) into a forward-reasoning Jess version. The full Java environment for running this is available from Said Tabet. 2004-02-27: The New Brunswick Business Knowledge Base, NBBizKB, was created as a major use case for OO RuleML. 2004-05-15: Based on the RuleML and Cofi projects, the Rule-Applying Collaborative Filtering System (RACOFI) has meanwhile led to a portal for publishing, searching, and rating independent music in MP3 (inDiscover). 2005-09-13: The ChemXelem use case consists of a RuleML knowledge base about the Periodic System of the Elements generated from a non-XML source.

If you are interested to join the RuleML Initiative, please send a link describing your work related to rule markup to Harold Boley and Said Tabet; same for general RuleML questions/suggestions. Depending on your specific RuleML interests, you may also contact some RuleML Technical Group (select above) or some RuleML Participant (select above). You are encouraged to subscribe to our main mailing list: ruleml-all.