BRMS - Business Rule Management Systems: High-impact Strategies - What You Need to Know: Definitions, Adoptions, Impact, Benefits, Maturity, Vendors

Kevin Roebuck

Description

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A BRMS or Business Rule Management System is a software system used to define, deploy, execute, monitor and maintain the variety and complexity of decision logic that is used by operational systems within an organization or enterprise. This logic, also referred to as business rules, includes policies, requirements, and conditional statements that are used to determine the tactical actions that take place in applications and systems.

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This book is your ultimate resource for BRMS. Here you will find the most up-to-date information, analysis, background and everything you need to know.

In easy to read chapters, with extensive references and links to get you to know all there is to know about BRMS right away. A quick look inside: Business rule management system, Semantic reasoner, Bossam (software), Business rules engine, Cleverpath AION Business Rules Expert, Corticon, D3web, Drools, DTRules, Event condition action, Jess (programming language), JSR 94, Mandarax, OpenL Tablets, Production Rule Representation, R2ML, Reasoning system, Rule-based system, RuleML, StrixDB, Versata, Expert system, Expert systems for mortgages, Backward chaining, CADUCEUS (expert system), CLIPS, Dendral, EGanges, Explanation facility, Explanation module, Forward chaining, FuzzyCLIPS, Global Infectious Disease Epidemiology Network, Illyria (software), Inference engine, Internist-I, Mycin, OpenKBM, Production system, PROPHET system, Rete algorithm, Rog-O-Matic, SHINE Expert System, Shyster (expert system), Split Up (Decision Support System), Validis, Xcon ...and Much, Much More!

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Sujets

• Computers
• Informatique
• General officer
• General

Informations

• Publié par: Emereo Publishing
• Date de parution: 24 octobre 2012
• Nombre de lectures: 0
• EAN13: 9781743339008
• Langue: English
• Poids de l'ouvrage: 2 Mo

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Contents

Articles Business rule management system Semantic reasoner Bossam (software) Business rules engine Cleverpath AION Business Rules Expert Corticon D3web Drools DTRules Event condition action Jess (programming language) JSR 94 Mandarax OpenL Tablets Production Rule Representation R2ML Reasoning system Rule-based system RuleML StrixDB Versata Expert system Expert systems for mortgages Backward chaining CADUCEUS (expert system) CLIPS Dendral EGanges Explanation facility Explanation module Forward chaining FuzzyCLIPS Global Infectious Disease Epidemiology Network Illyria (software)

1 3 6 6 10 12 15 17 20 21 22 24 25 26 28 29 30 33 34 35 37 40 47 49 51 52 54 57 58 58 58 59 60 61

Inference engine Internist-I Mycin OpenKBM Production system PROPHET system Rete algorithm Rog-O-Matic SHINE Expert System Shyster (expert system) Split Up (Decision Support System) Validis Xcon

References Article Sources and Contributors Image Sources, Licenses and Contributors

Article Licenses License

61 63 65 67 68 71 72 79 80 82 85 88 89

91 93

94

Business rule management system

Business rule management system

ABRMSorBusiness Rule Management Systemis a software system used to define, deploy, execute, monitor and maintain the variety and complexity of decision logic that is used by operational systems within an organization or enterprise. This logic, also referred to as business rules, includes policies, requirements, and conditional statements that are used to determine the tactical actions that take place in applications and systems.

Overview [1] A BRMS includes, at minimum:  A repository, allowing decision logic to be externalized from core application code  Tools, allowing both technical developers and business experts to define and manage decision logic  A runtime environment, allowing applications to invoke decision logic managed within the BRMS and execute it using a business rules engine [2] The top benefits of a BRMS include:  Reduced or removed reliance on IT departments for changes in live systems. Although, QA and Rules testing would still be needed in any enterprise system.  Increased control over implemented decision logic for compliance and better business management  The ability to express decision logic with increased precision, using a business vocabulary syntax and graphical rule representations (decision tables, trees, scorecards and flows)  Improved efficiency of processes through increased decision automation Most BRMS vendors have evolved from rule engine vendors to provide business-usable software development lifecycle solutions, based on declarative definitions of business rules executed in their own rule engine. However, some vendors come from a different approach (for example, they map decision trees or graphs to executable code). Rules in the repository are generally mapped to decision services that are naturally fully compliant with the latest SOA, Web Services, or other software architecture trends. |

Related software approaches In a BRMS, a representation of business rules maps to a software system for execution. A BRMS therefore relates to model-driven engineering, such as the Model Driven Architecture (MDA) of the Object Management Group (OMG). It is no coincidence that many of the related standards come under the OMG banner.

Associated standards There is no current implementation standard for business rules defined within a BRMS, although there is a standard for a Java Runtime API for rule engines JSR-94. Other standards (under development) include:  OMG Business Motivation Model (BMM): A model of how strategies, processes, rules, etc fit together for business modeling  OMG SBVR: Targets business constraints as opposed to automating business behavior  OMG Production Rule Representation (PRR): Represents rules for production rule systems that make up most BRMS' execution targets  W3C RIF: A family of related rule languages for rule interchange Many standards, such as domain-specific languages, define their own representation of rules, requiring translations to generic rule engines or their own custom engines.

1

Business rule management system

Other domains, such as PMML, also define rules. RuleML provides a (mostly academic) family of mark-up languages that could be used in a BRMS, but are usually used for research purposes.

Products and vendors  JBoss Enterprise BRMS (open source)  OpenL Tablets BRMS (open source) [3]  Be Informed BRMS, BRE and BPM [4]  WebSphere ILOG BRMS: IBM WebSphere ILOG JRules  Bosch Software Innovations  FICO  InRule Technology  OpenRules  Pegasystems [5]  Sparkling Logic SMARTS(tm) next generation collaborative decision management system and BRMS [6]  Sapiens International Corporation eMerge Platform

References [1] Is Your Rules Engine Event-Driven? (http:/ /www.sapiens-tech.com/iDuneDownload.dll?GetFile?AppId=225&FileID=216581& Anchor=&ext=.pdf) [2] "The Hidden Value of Event-Driven Business Rules Engines" (http:/ /www.sapiens-tech.com/iDuneDownload.dll?GetFile?AppId=225& FileID=216577&Anchor=&ext=.pdf) Sapiens Whitepaper, May 2005 [3] http://www.BeInformed.com [4] http://www-01.ibm.com/software/integration/business-rule-management/jrules-family/ [5] http://www.sparklinglogic.com [6] http://www.sapiens-tech.com/

External links  Workshop summary paper: Six Views on the Business Rule Management System (http://www.e-journal-of-pbr. info/resch-six-views-business-rule-management-system)

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Semantic reasoner

Semantic reasoner

Asemantic reasoner,reasoning engine,rules engine, or simply areasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including Pei Wang's non-axiomatic reasoning system, Novamente's probabilistic logic network, and Pronto - probabilistic description logic reasoner.

Semantic reasoners, etc. Existing semantic reasoners and related software:

Non-free software  Bossam (software), an RETE-based rule engine with native supports for reasoning over OWL ontologies, SWRL rules, and RuleML rules. [1]  DLog, Resolution based Description Logic ABox reasoner that translates to Prolog (DLog ).  OWLIM, a high-performance semantic repository developed in Java and available in two versions: free SwiftOWLIM and commercial BigOWLIM. Supports a subset of OWL-Lite semantics, which can be configured [2] [3] through rule-set definition and selection. (OWLIM ) [4]  RacerPro, a semantic web reasoning system and information repository (RacerPro ) [5]  SHER, a scalable Pellet-backed OWL DL reasoner (SHER ). [6]  OntoBroker, highly scalable SemanticWeb middleware (OntoBroker ).

Free software  BaseVISor, a versatile forward chaining inference engine specialized to handle facts in the form of RDF triples [7] with support for OWL 2 RL and XML Schema Datatypes (BaseVISor ).  Cwm, a forward chaining reasoner which can be used for querying, checking, transforming and filtering information. Its core language is RDF, extended to include rules, and it uses RDF/XML or N3 serializations as [8] required. (CWM )  Drools, a forward chaining inference based rules engine that uses an enhanced implementation of the Rete algorithm. [9]  FaCT, a description logic (DL) classifier. (FaCT ) [10]  FaCT++, the new generation of FaCT OWL-DL reasoner. (FaCT++ )  Hoolet, reasons over OWL-DL ontologies by translating them to full first-order logic and then applying a [11] first-order theorem prover. (Hoolet )  Jena (framework), an open source semantic web framework for Java which includes a number of different semantic reasoning modules.  KAON2 is an infrastructure for managing OWL-DL, SWRL, and F-Logic ontologies.  Large_Knowledge_Collider or LarKC is a large scale distributed reasoner that focuses on performance by allowing incomplete reasoning [12]  Pellet, an open-source Java OWL DL reasoner. (Pellet )  Prova, an open-source Semantic Web rule engine which supports data integration via SPARQL queries and type [13] systems (RDFS, OWL ontologies as type system). (Prova ) [14]  SweetRules, an integrated set of tools for Semantic web rules and ontologies. (SweetRules )

3

Yes (SWRL—DL Safe Rules)

2.1

Free/ Free/ Free/ open-source open-source open-source & Non-Free/ closed-source

Yes

Yes (SWRL, RIF, F-logic, ObjectLogic)

Yes

Yes

Free/ open-source

Non-Free/ closed-source

Yes (SWRL & own rule format)

Yes

Rule Support

Yes (Own rule format)

No

Yes

Yes

Yes

Yes (SWRL)

Unknown

2008-06-29

No complete reasoner included with standard distribution

Yes

Yes

No

SHIQ

varies by reasoner (incomplete for nontrivial description logics)

Tableau

Tableau

Rule-based Rule-based

Yes

Rule-based

OWL: Resolution & Hypertableau Datalog;F-logic: Rule-based (BottomUp, MagicSet, DynamicFiltering, QSQ)

No

No

Yes (SWRL, RuleML, Jess)

Yes (Own format)

FaCT++

Unknown

SROIQ(D) UnknownOWL:SHIQ(D) R-entailment, (for OntoBroker OWL 2 RL 6.1: Subset of OWL-RL); F-logic:normal logic, wellfounded semantics

First-order prover

Tableau

No

OWL-DL Entailment

6.1

1.3.4

No

Yes

2.0 preview

Yes Yes Yes Yes (Own (SWRL—DL (SWRL—DL (SWRL — not rule Safe Rules) Safe Rules) fully format) supported) & own rule format

Yes

No

2.0.2

2.x/3.x

DIG Support

Consistency checking

Incomplete for OWL DL

Yes

Yes

Yes

Yes

No

Yes

No

Bossam

Unknown

2.5.4

1.1.8

BaseVISor

HermiT, the first publicly-available OWL reasoner based on a novel“hypertableau”calculus which provides [15] much more efficient reasoning than any previously-known algorithm. (HermiT )

Semantic reasoner

Jena

FaCT

Supported expressivityR-entailment, for OWL 2 RL reasoning

Rule-based, Rete

Reasoning algorithm

Rule-based

Yes

Unknown

No

Yes

Resolution & Datalog

SHIQ(D)

Tableau

SHIQ(D-)

No

Yes

Yes

Unknown

SROIQ(D)

Yes

Yes

SHOIQ+

Unknown

Yes

SweetRules

Hoolet

Reasoner comparison

Version

Licensing

2.0

0.9b45

No

Free/ Free/ Free/ Free/ Free/ Non-Free/ Free/ Free/ closed-source closed-source open-source open-source closed-source closed-source open-source open-source (academic & Non-Free/ and research closed-source use) & Non-Free / closed-source

OWLIM

OntoBroker

Yes

4

HermiT

Pellet

KAON2

RacerPro

Semantic reasoner

External links [16]  OWL 2 Reasoners listed on W3C OWL Working Group homepage [17]  SPARQL Query Language for RDF [18] Introduction to Description LogicsDL course by Enrico Franconi, Faculty of Computer Science, Free University of Bolzano, Italy [19]  Marko Luther, Thorsten Liebig, Sebastian Bahm, Olaf Noppens: Who the Heck Is the Father of Bob? . ESWC 2009: 66-80 [20]  Jurgen Bock, Peter Haase, Qiu Ji, Raphael Volz. Benchmarking OWL Reasoners . In ARea2008 - Workshop on Advancing Reasoning on the Web: Scalability and Commonsense (June 2008) [21]  Tom Gardiner, Ian Horrocks, Dmitry Tsarkov. Automated Benchmarking of Description Logic Reasoners . Description Logics Workshop 2006 [22]  OpenRuleBench Senlin Liang, Paul Fodor, Hui Wan, Michael Kifer. OpenRuleBench: An Analysis of the [23] Performance of Rule Engines. 2009. Latest benchmarks at OpenRuleBench website . [24]  Pronto , a probabilistic description logic reasoner.

References [1] http://sintagma.szit.bme.hu/dlog [2] OntoText.com (http://www.ontotext.com/inference/rdfs_rules_owl.html#owl_fragments) [3] http://www.ontotext.com/owlim/index.html [4] http://www.racer-systems.com [5] http://www.alphaworks.ibm.com/tech/sher [6] http://www.ontoprise.de/index.php?id=135 [7] http://vistology.com/basevisor/basevisor.html [8] http://www.w3.org/2000/10/swap/doc/cwm.html [9] http://www.cs.man.ac.uk/~horrocks/FaCT/ [10] http://owl.man.ac.uk/factplusplus/ [11] http://owl.man.ac.uk/hoolet/ [12] http://pellet.owldl.com/ [13] http://prova.ws [14] http://sweetrules.projects.semwebcentral.org/ [15] http://hermit-reasoner.com/ [16] http://www.w3.org/2007/OWL/wiki/Implementations [17] http://www.w3.org/TR/rdf-sparql-query/ [18] http://www.inf.unibz.it/~franconi/dl/course/ [19] http://dx.doi.org/10.1007/978-3-642-02121-3_9 [20] http://www.aifb.uni-karlsruhe.de/WBS/pha/publications/owlbenchmark_07_2007.pdf [21] http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-189/submission_23.pdf [22] http://www2009.org/proceedings/pdf/p601.pdf [23] http://rulebench.projects.semwebcentral.org/ [24] http://pellet.owldl.com/pronto

5

Bossam (software)

Bossam (software)

Bossamis an inference engine (a Semantic Reasoner) for the semantic web. It is basically a RETE-based rule engine with native supports for reasoning over OWL ontologies, SWRL ontologies, and RuleML rules. Additionally, Bossam includes several expressivity features including: 1) URI references as symbols, 2) 2nd-order logic syntax, 3) disjunctions in the antecedent and conjunctions in the consequent (both via Lloyd-Topor transformation), 4) URI-based java method attachment, 5) support for both negation-as-failure and classical negation. Bossam loads, performs reasoning over, and answers to the queries over a knowledge set, which can include any combination of the following document types. 1. RDF(S) documents (in RDF/XML or in N3) 2. OWL documents (in RDF/XML or in N3) 3. Bossam rule documents 4. SWRL(+OWL) documents (in OWLX or in RDF/XML) Bossam can call Java objects from the antecedent or consequent of rules through the URI-based java method attachment. It's possible to easily mix Java objects into the combination of rules and ontologies.

External links  Bossam Rule/OWL Reasoner Homepage (http://bossam.wordpress.com)

Business rules engine

Abusiness rules engineis a software system that executes one or more business rules in a runtime production environment. The rules might come from legal regulation ("An employee can be fired for any reason or no reason but not for an illegal reason"), company policy ("All customers that spend more than $100 at one time will receive a 10% discount"), or other sources. A business rule system enables these company policies and other operational decisions to be defined, tested, executed and maintained separately from application code. Rule engines typically support rules, facts, priority (score), mutual exclusion, preconditions, and other functions. Rule engine software is commonly provided as a component of a business rule management system which, among other functions, provides the ability to: register, define, classify, and manage all the rules, verify consistency of rules definitions (”Gold-level customers are eligible for free shipping when order quantity > 10”and“maximum order quantity for Silver-level customers = 15”), define the relationships between different rules, and relate some of these rules to IT applications that are affected or need to enforce one or more of the rules.

IT use In any IT application, business rules change more frequently than the rest of the application code. Rules engines or inference engines are the pluggable software components that execute business rules that have been externalized from application code as part of a business rules approach. This externalization of business rules allows the business users to modify the rules frequently without the need of IT intervention. The system as a whole becomes more adaptable with business rules that can be changed dynamically, although QA and other testing would still be required.

6