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Mission Statement: To develop RuleML as the canonical language family for Web rules through XML serialization, formal semantics, and efficient implementations.

The overarching, modular schema specification of the RuleML family covers both derivation rules and reaction rules. RuleML is thus used to exchange knowledge bases and queries across rule-based systems, map between Web ontologies, and interoperate dynamic network behaviors of workflows, services, and agents. Read more...

RuleML Inc. is a non-profit organization that drives the specification of standard semantic-technology & business rules, coordinates rule research and development, and holds international meetings.

The standards effort of RuleML Inc. connects Web rule efforts across academia, standards bodies, and industry, and dovetails with Web ontology efforts as part of the semantic technology stack. The XML syntax known as "RuleML" provides a de facto standard for Web knowledge representation that served as the main XML-based input to RIF and provides bridges between SWRL, SWSL, and LegalRuleML. The current Specification of RuleML is Version 1.0.

RuleML Inc. functions as the organizational lead of the RuleML Initiative. Foundational RuleML technology developed by the RuleML Initiative includes user and serialization syntaxes, transformations, model-theoretic semantics, and engines.

The annual RuleML Symposium has taken the lead in bringing together delegates from industry and academia who share this interest focus in Web rules.

See Introducing RuleML for more detail and links to slides.


  • 2014-04-04: Announcement of the Public Review of Deliberation RuleML 1.01 (including the MYNG 1.01 GUI).
  • 2014-04-02: Announcement on student travel support.
  • 2014-03-21 Keynote Announcement: RuleML2014 Keynote Talk: "Rules, Events and Actions" presented by Prof.dr. Adrian Paschke.
  • RuleML 2014, the 8th International Web Rule Symposium will be held on August 18-20, 2014 in Prague, Czech Republic, in conjunction with ECAI 2014, the 21st European Conference on Artificial Intelligence. RuleML 2014 will host: the 8th International Rule Challenge, the 4th RuleML Doctoral Consortium, the Rules and Human Language Technology, the Learning (Business) Rules from Data, and the Legal Rules and Norms special tracks, as well as the OASIS Legal RuleML Meeting. Important dates:
    • Abstract submission (Extended): April 14, 2014
    • Paper submission (Extended): April 22, 2014
  • The RuleML Website Redesign achieved another milestone on 8 December 2013 as the URL of the RuleML Home Page now redirects to, the main page of the RuleML Wiki. The new MediaWiki-based design includes a Category-based Sitemap, syntactic search across all Wiki-based RuleML pages, and improved connectivity through the left sidebar and footer. In addition, much of the content has been brought up-to-date and some extensions have been made. RuleML Community members are encouraged to further improve the content, e.g. add News, through the Wiki editing system -- all that is required is a Wiki user account. If you need an account or any kind of help, please let us know -- see Contacts for contact information.
  • The Grailog Initiative, aligned with the Web-rule industry standard RuleML, was invited to present Grailog 1.0 at the ISO 15926 and Semantic Technologies 2013 Conference, at Ontolog's RulesReasoningLP mini-series, and at Decision (boot) CAMP 2013. The Grailog page includes the Loan Processor Suite for visualizing Datalog RuleML decision rules in Grailog 1.0/SVG. Visual Grailog feedback (LoanProcessor.svg) has helped improving its data & knowledge sources (LoanProcessor.txt). Grailog is a systematic combination of generalized graph constructs for visual data & knowledge representation. It enables analytics for humans in the loop of data & knowledge elicitation, specification, validation, as well as reasoning.
  • Ontolog's "Ontology, Rules, and Logic Programming for Reasoning and Applications" (RulesReasoningLP) mini-series has many interesting virtual Thursday 12:30pm Eastern sessions, some including RuleML contributions (new Ontolog participants should send RSVP to peter.yim AT
  • Decision CAMP 2013 is a free event, 4-6 November 2013, for Business Analysts and Software Architects looking to automate and improve decisions (Agenda), with a participant-driven "unconference" where you can network with, learn from, and teach one another in a collaborative environment. Decision CAMP is in partnership with RuleML, the inaugural 2013 meeting being hosted by eBay in San Jose, CA.
To add News to this index, please login and navigate to News:Master. All listings, including obsolete and draft items, are maintained at that page. To obtain an account, Contact Us.

1 Uses of Rules

Rules describe the general association of causes with effects ('laws'), situations with actions ('triggers'), premises with conclusions ('implications'), and so are used to represent physical, chemical and biological processes, medical guidelines, business and legal policies, conditional equations, probabilities and preferences, grammars, logics, and computer programs. Very special (constantly-true-premise, i.e. premiseless) implications are data records, including relational and object-centered ones (PSOA RuleML). Other special (single-premise, unary-predicate) implications in rulebases are equivalent to taxonomic subsumptions in ontologies (DistriSemWeb), more general rules can be used to extend ontologies, and rules provide transformation and implementation techniques for ontologies. Different and incompatible rule notations had emerged. RuleML has been established as a family of Web rule languages that allow all of these uses to be uniformly and precisely defined. Since rules are both descriptive and operational, a rule specification can be directly executed and debugged as a program. Since rule implications are formulas of a logic, a rule specification can be directly proved correct. Using the XML-based RuleML, specifications can interoperate across heterogeneous applications. Read more...

2 RuleML as a Bridge

RuleML (Rule Markup Language, which has also become a Rule Modeling Language) is a unifying family of XML-serialized rule languages spanning across all industrially relevant kinds of Web rules. As a research-based language family, RuleML acts as the connector between RIF -- via the emerging RIF RuleML subfamily -- and Common Logic -- via the planned CL RuleML subfamily. As an industry-focused de facto standard, RuleML has become the overarching specification of Web rules cross-fertilizing with corresponding OMG specifications (mainly SBVR and PRR) and constituting the foundation of an OASIS specification (LegalRuleML). Through its participation in SWRL and SWSL, RuleML has already accommodated and extended other rule languages, building interoperation bridges between them.

3 Scope of RuleML

The scope of RuleML is characterized here in the following dimensions: Natural and formal languages; deliberation and reaction rules; XML serialization, presentation syntaxes, and default semantics; internal/external translators and reference engines; as well as horizontal and vertical standardization. Read more...

4 The Initiative

RuleML Inc. is an international non-profit organization covering all aspects of Web rules and their interoperation. Its organizational structure and technical groups center on RuleML specification as well as tool and application development. RuleML Inc. functions as the organizational lead of the RuleML Initiative. The RuleML Initiative is an open network of individuals and groups from both industry and academia that has emerged around a shared interest in current rule topics, including the interoperation of Semantic Web rules. The RuleML Initiative has been collaborating with OASIS on Legal XML, Policy RuleML, LegalRuleML, and related efforts since 2004. The Initiative has further been interacting with the developers of ISO Common Logic (CL), which became an International Standard, First edition, in October 2007. RuleML is also a member of OMG, contributing to its Semantics of Business Vocabulary and Business Rules (SBVR), which was released as Version 1.0 in January 2008, and to its Production Rule Representation (PRR), which was released as Version 1.0 in December 2009. Moreover, participants of the RuleML Initiative have supported the development of the W3C Rule Interchange Format (RIF), which attained Recommendation status in June 2010 and published a Second Edition in February 2013. Read more...

5 Related Efforts

Conceptual, semantic, syntactic, serialization, and implementation efforts related to RuleML have been pursued at W3C, OMG, OASIS, and other standards bodies, as well as by universities, government initiatives, and industrial consortia. Some of these are listed here (please let us know of any updates and additions).  Read more...

6 Participant Systems

Besides co-evolving with Related Efforts, the RuleML Initiative has been based on systems by its participants, including some of the following systems of the participants listed in parentheses.  Read more...

7 Architecture

The overall architecture of RuleML comprises a metamodel, semantic principles (e.g., the use of a default and variant semantics) and serialization principles (e.g., the use of 'striped' XML), a systematics of language features for modular language customization (in MYNG), a family of languages defined semantically (e.g., via model theory) and serialization-syntactically (via schema languages such as XSD and RNC), and normalizers defined as (XML-serialization) transformers (e.g., via XSLT). Read more...



The RuleML Primer has its current focus on the Datalog sublanguage, developing the discount example from its parts.

Mailing Lists
  • Subscribe to our main mailing list ruleml-all: Archives are available to subscribers.
  • In addition to the main mailing list, where all general announcements are posted, you may want to subscribe to one of the following special topics lists:
    • Get up to date with the Fuzzy RuleML TG mailing list: fuzzy-tg.
    • Peek into the Reaction Rules TG mailing list: reaction-tg.
    • Consider to join the engine mailing list: jdrew-all.
    • Discuss Web rule-based agents on the Rule Responder TG mailing list: responder-tg.
    • Join the LinkedIn RuleML group or some of its subgroups: LinkedIn RuleML group.
Challenge Demos

The page for RuleML Challenge Demos has been created by the research group of Yuh-Jong Hu from the Department of Computer Science at the National Chengchi University (NCCU), Taipei, Taiwan, where it is being maintained by Jack.

Archival Material

8 Specification

Version history:
Date Version
2001-01-25 -

Version 0.7 HTML

2001-07-11 -

Version 0.8 HTML

2003-12-09 -

Version 0.85 HTML

2004-06-23 -

Version 0.86 HTML

2004-08-12 -

Version 0.87 HTML

2005-03-01 -

Version 0.88 HTML

2005-05-27 -

Version 0.89 HTML

2005-11-09 -

Version 0.9 HTML

2006-08-24 -

Version 0.91 HTML

2011-09-27 -

Version 0.91 Patched HTML

2012-04-03 -

Version 1.0 HTML

2012-04-03 -

Version 1.0 Wiki

9 Translators

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.

To add Translators to this index, please login and navigate to Translators:Master. All listings, including obsolete and draft items, are maintained at that page. To obtain an account, Contact Us.

10 Engines

Various rule engines have been used to execute (queries posed to) RuleML rulebases as described in the following.

To add Engines to this index, please login and navigate to Engines:Master. All listings, including obsolete and draft items, are maintained at that page. To obtain an account, Contact Us.

11 Positional-Slotted Language

The POsitional-SLotted (POSL) presentation, shorthand, and exchange syntax for rules (original POSL spec and POSL slides) combines Prolog's positional and F-logic's slotted syntaxes. The need for it had emerged from discussions on ASCII syntaxes in the Joint Committee. The bidirectional online online translator (including Types), in Java Web Start, has enabled writing knowledge bases in the RuleML/POSL shorthand while deploying them in the RuleML/XML serialization, as well as getting RuleML/XML rendered as RuleML/POSL. Several applications have been built on POSL (see, e.g. Rulebases:Master). An updated POSL version, as described in Integrating Positional and Slotted Knowledge on the Semantic Web, was implemented along with d-POSL in CS 6795 Semantic Web Techniques, Fall 2011, Team 1. Here is the updated OO jDREW 1.0 POSL/RuleML Translator (Java Web Start). POSL inspired some of the work on Positional-Slotted, Object-Applicative RuleML.

12 Positional-Slotted, Object-Applicative RuleML

Authors: Gen Zou Harold Boley

This version: PSOA RuleML

Latest version: PSOA RuleML

Previous versions:

Positional-Slotted, Object-Applicative RuleML (PSOA RuleML) permits a relation application to have an Object IDentifier (OID) -- typed by the relation -- and, orthogonally, its arguments to be positional or slotted. The resulting positional-slotted, object-applicative (psoa) terms can be used as (positional, relation-applying) classical facts without an OID and with an -- ordered -- sequence of arguments, as (slotted, object-centered) frame facts with an OID and with an -- unordered -- multi-set of slots (each being a pair of a name and a filler), as well as in various other ways. Such psoa facts and rules over them were given a first-order model-theoretic foundation (paper, slides), blending (OID-over-)slot distribution, as in RIF, with integrated psoa terms, as in RuleML. In order to support reasoning in PSOA RuleML, the PSOA2TPTP translator was implemented, which maps PSOA RuleML knowledge bases and queries to the TPTP format, as widely used for theorem provers. With this translator, reasoning in PSOA RuleML is available using the VampirePrime prover. The composition of PSOA2TPTP and VampirePrime to PSOATransRun has been developed under an online GUI.  Read more...

13 RIF

RIF RuleML specifications are being collected here:

Convergence of RIF and RuleML is facilitated by PSOA RuleML.

14 RDF

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

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.

Taking newer RDF-rule developments such RIF In RDF into account, these tools should be updated for RuleML 1.0.

15 Graph Inscribed Logic

The Graph inscribed logic (Grailog) is a systematic combination of generalized graph constructs for visual data & knowledge representation ranging from (binary and n-ary) relational logic to Horn logic, description logic, object/frame logic, higher-order logic, and modal logic. Grailog thus provides a framework enabling analytics via 2-dimensional graph-logic visualization for humans in the loop of data & knowledge elicitation, specification, validation, as well as reasoning. Such Grailog visualization also serves as a teaching vehicle for making central (description- and Horn-)logical notions of ontologies and rules accessible to students of AI, Semantic Technologies, and related areas, as initiated for Logical Foundations of Cognitive Science. The Grailog Initiative for data & knowledge visualization is aligned with the Web-rule industry standard RuleML, where co-development is giving rise to synergies.  Read more...

16 User Interfaces

User interfaces, particularly editors, for RuleML are described here.

  • Rawe: Editor for rule markup of legal texts and conversion to LegalRuleML based on Akoma Ntoso markup

To add Editors to this index, please login and navigate to Editors:Master. All listings, including obsolete and draft items, are maintained at that page. To obtain an account, Contact Us.

17 Induction

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.

18 Rulebase Library

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 (e.g., library and examples). The highest version of RuleML (currently 1.0) 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).

To add Rulebases to this index, please login and navigate to Rulebases:Master. All listings, including obsolete and draft items, are maintained at that page. To obtain an account, Contact Us.

19 Papers-Publications

RuleML maintains a bibliography about RuleML syntax, semantics, reasoning, and applications, as well as studies directly supporting the RuleML language.

To add Publications to this index, please login and navigate to Publications:Master. All listings, including obsolete and draft items, are maintained at that page. To obtain an account, Contact Us.

20 Structure

RuleML Inc. is a non-profit, open-source organization managed by a Steering Committee, with input from Technical Groups, Partners, and AffiliatesRead more...

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