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2014-11-20: Release of the RuleML2TPTP Translator from Datalog+ RuleML 1.01 to TPTP
By Meng Luan, Changyang Liu, Tara Athan, Harold Boley
The RuleML2TPTP translator was released for mapping Datalog+ Deliberation RuleML 1.01 in XML (Datalog+/XML) format to an equivalent subset of the Thousands of Problems for Theorem Provers (TPTP) format. RuleML2TPTP thus provides an initial bridge from RuleML technologies to the TPTP world. With the RuleML2TPTP tool available, Datalog+/XML specifications can now be rendered in (pretty-printed) TPTP, providing a presentation syntax for users familiar with this compact format. RuleML2TPTP also makes Datalog+/XML rulebases ready for execution in all theorem provers that can read TPTP. The tool was implemented in XSLT 2.0 and Java. RuleML2TPTP has been used, e.g., for the Datalog+ examples of the Deliberation RuleML 1.01 Release. Its binaries and sources can be freely downloaded from GitHub via the link below. For more information, see edmonl.github.io/RuleML2TPTP/, edmonl.github.io/RuleML2TPTP/RuleML2TPTP_report.pdf.
2014-11-06: RuleML/XML-to-RuleML/JSON Translation Prepared
By Harold Boley
Like for XML, there are many ways to capture data and knowledge in JSON. To specify the composition of XML tags and of JSON structures, existing schemas of XML should be reused. A page, started on 6 July 2014, has been developed to prepare round-trippable translation from a subset of RuleML/XML to the new RuleML/JSON. Corresponding slides (14-35) were presented at Decision CAMP 2014 as How Object-Centered XML Rules are Configured from the RuleML Lattice, can be Exchanged in JSON, and enable Decision Making over Object-Relational Data. For more information, see wiki.ruleml.org/index.php/RuleML_in_JSON.
2014-07-25: Release of Deliberation RuleML 1.01
By RuleML
Deliberation RuleML 1.01 has now become an official release: The RuleML Steering Committee voted to approve the Response to Public Review of Deliberation RuleML 1.01 and the release of the Specification of Deliberation RuleML 1.01. For more information, see deliberation.ruleml.org/1.01/timeline#Deliberation_RuleML_1.01_Release.  Read about it on the RuleML Blog.
2014-05-23: Adoption Of Reaction RuleML 1.0
By RuleML
The newest release of Reaction RuleML includes the new RelaxNG schema for Version 1.0. For more information, see reaction.ruleml.org/1.0.
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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 open standards effort of the organization 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 resulting Web rule specification RuleML Spec provides a de facto standard for Web knowledge representation that served as the main XML-serialization input to RIF and provides bridges between RIF, SWRL, SWSL, Common Logic, and LegalRuleML. The current Specification of Deliberation RuleML is Version 1.01 and of Reaction 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 presentation and serialization syntaxes, lattice-configurable sublanguages, 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.

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, database views, and declarative programs. While the if-then associations of imperative programs are hard-coded into a control flow, those of rule systems are 'soft-coded' into a rulebase (e.g., a set of rules) such that a rule engine can choose an appropriate rule for invocation in each computational cycle. Through transformation chains of iterated rule choices and invocations, arbitrary computations can be performed. Rules thus constitute the smallest modules for computation, which can be aggregated into rulebase modules of rules and other rulebases. 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...

Mission
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...

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...

Resources

Primer

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 (Nabble or Gmane) 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

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...

8 Specification

8.1 Deliberation RuleML

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

2014-07-25 -

Version 1.01 Wiki


8.2 Reaction RuleML

Version history:
Date Version
2005-04-15 -

Version ECA RuleML 0.01 HTML

2005-08-15 -

Version ECA RuleML 0.1 HTML

2005-10-30 -

Version ECA RuleML 0.2 (pre-release) PDF

2005-11-01 -

Version ECA RuleML 0.2 (pre-release) PDF

2005-12-15 -

Version ECA RuleML 0.2 HTML

2006-10-30 -

Version ECA RuleML 0.3 HTML

2006-11-10 -

Version (ECA) Reaction RuleML 0.1 (pre-release) PDF

2006-10-12 -

Version Reaction RuleML 0.1 HTML

2007-07-22 -

Version Reaction RuleML 0.2 HTML

2007-07-22 -

Version Reaction RuleML 0.3 HTML

2010-10-21 -

Version Reaction RuleML 1.0 (pre-release) PDF

2012-08-27 -

Version Reaction RuleML 1.0 (pre-release) PDF

2014-05-23 -

Version Reaction RuleML 1.0 Wiki


9 Editors

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

  • LIME: Editor for markup of legal texts in LegalRuleML (previously called RAWE).

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10 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.

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11 Engines

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

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12 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.

13 Positional-Slotted, Object-Applicative RuleML

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...

14 RIF

RIF RuleML specifications are being collected here:

Convergence of RIF and RuleML is facilitated by PSOA RuleML.

15 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.

16 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...

17 User Interfaces

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

  • LIME: Editor for markup of legal texts in LegalRuleML (previously called RAWE).

See all...

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

18 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.

19 Rule-Based Data Access

Ontology-Based Data Access (OBDA) -- from Ontology-Based Data Integration (OBDI) to Ontology-Based Data Querying (OBDQ) to Ontology-Based Data Management (OBDM) -- has become an active R&D topic in recent years, and is emerging as a major application area of Semantic Technologies for heterogeneous databases. OBDA ontologies encompass rule knowledge to enrich the factual data mapped -- again via rules -- to a global (homogeneous) schema from the local (heterogeneous) schemas of one or more databases. Given these and other roles of rules, we will focus on Rule-Based Data Access (RBDA) -- with a foundation in the basic Rule-Based Data Integration (RBDI), an emphasis on the central Rule-Based Data Querying (RBDQ), and some examination of the advanced Rule-Based Data Management (RBDM). For a tutorial-style introduction see "The Many Uses of Rules in Ontology-Based Data Access" (original abstract, current slides). A preprint of the paper "A Datalog+ RuleML 1.01 Architecture for Rule-Based Data Access in Ecosystem Research", presented at RuleML 2014, is available (GeospatialRBDA). For a discussion on related topics, please contact any of the authors, Harold Boley, Rolf Grütter, Gen Zou, Tara Athan, or Sophia EtzoldRead more...

20 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 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.

Deliberation RuleML 1.01

Rule-Based Data Access

  • ΔForest (simplified presentation syntax)

 Read more...

21 Papers-Publications

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

Also see results for RuleML from

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22 International Web Rule Symposium (RuleML) Events

  • RuleML-2015: Ninth International Web Rule Symposium, Berlin, Germany.
  • RuleML-2014: Eighth International Web Rule Symposium, Prague, Czech Republic.
  • RuleML-2013: Seventh International Web Rule Symposium, Seattle, USA.
  • RuleML-2012: Sixth International Web Rule Symposium, Montpellier, France.
  • RuleML-2011@BRF: Fifth International Web Rule Symposium]: Research Based and Industry Focused, Fort Lauderdale, FL, USA.
  • RuleML-2011@IJCAI: Fifth International Web Rule Symposium, Barcelona, Spain.
  • RuleML-2010: Fourth International Web Rule Symposium]: Research Based and Industry Focused, Washington, DC, USA.
  • Semantic Rules Track at SemTech 2010, San Francisco, CA, USA.
  • RuleML-2009: Third International RuleML Symposium on Rule Interchange and Applications, Las Vegas, Nevada, USA.
  • RuleML-2008: Second International RuleML Symposium on Rule Interchange and Applications, Orlando, FL, USA.
  • RuleML-2007: First International RuleML Symposium on Rule Interchange and Applications, Orlando, FL, USA.
  • RuleML-2006: Second International Conference on Rules and Rule Markup Languages for the Web, Athens, Georgia, USA.
  • Special Workshop on Reaction RuleML (Special Event at ISWC06), Athens, Georgia, USA.
  • RuleML-2005: First International Conference on Rules and Rule Markup Languages for the Semantic Web, Galway, Ireland.
  • RuleML-2004: Third International Workshop on Rules and Rule Markup Languages for the Semantic Web, Hiroshima, Japan.
  • RuleML-2003: Second International Workshop on Rules and Rule Markup Languages for the Semantic Web, Sanibel Island, FL, USA.
  • RuleML-2002: First International Workshop on Rule Markup Languages for Business Rules on the Semantic Web, Sardinia, Italy.

23 Structure

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