IDEON: An ExtensibleOntology for Designing,Integrating, and ManagingCollaborative DistributedEnterprisesAzad M. Madni,* Weiwen Lin, and Carla C. Madni
Intelligent Systems Technology, Inc., 2800 28th Street, Suite 306, Santa Monica, CA 90405
IDEON : AN EXTENSIBLE ONTOLOGY FOR COLLABORATIVE DISTRIBUTED ENTERPRISES
Received July 22, 2000; Accepted September 28, 2000
An organizations ability to achieve and sustain competitive advantage in the face of continualchange depends, to a large extent, on the adaptability, interoperability, and maintainabilityof its enterprise management approach and supporting software implementation. In thisregard, the major challenges facing organizations are: (a) achieving seamless integration ofenterprise design, management and control processes and supporting applications; (b)ensuring interoperability between new and legacy business applications; and (c) adaptingbusiness strategies and ongoing operations to changes in the external and internal environ-ments. The latter requires integrated planning and execution of enterprise processes. This paperpresents IDEON, a unified, extensible enterprise ontology that has been designed in responseto these needs. Two specific applications of IDEON are presented along with the specificextensions for each application. 2001 John Wiley & Sons, Inc. Syst Eng 4, 3548, 2001
Today, there are several information technology (IT)trends and market dynamics that are driving enterprisemanagement and control requirements. Among these isthe fact that IT is expanding from a back-office resource
(e.g., manufacturing resource planning/enterprise re-source planning) to a front-office (e.g., sales force auto-mation, customer relationship management) enabler ofcompetitive advantage. Change, once viewed as a shortperiod of relative instability, is now a continuous proc-ess. At the same time, monolithic enterprises that totallyown all of the products, services, and channels requiredto serve a customer are rapidly being replaced by stra-tegic partnerships, virtual enterprises, and integratedvalue chains. The need to operate in a rapidly changing
*Author to whom all correspondence should be addressed.
Systems Engineering, Vol. 4, No. 1, 2001 2001 John Wiley & Sons, Inc.
business and technical environment is driving the needfor technology infrastructures and application architec-tures that are increasingly more flexible, interoperable,extensible, and maintainable. In the light of these dy-namics, an organizations ability to achieve and sustaina competitive advantage depends, to a large extent, onthe flexibility, interoperability, and maintainability ofits enterprise management and control capability. It isin this area that enterprise ontologies have the highestpayoff.
Interest in ontologies has surged as researchers andsystem developers have become increasingly more in-terested in reusing and sharing knowledge across sys-tems (i.e., software applications). However, today thereis a major impediment to knowledge sharing given thatthe different systems use different concepts and termsfor describing domains [Schlenoff et al., 2000]. As aresult, it is difficult to take knowledge out of one system(e.g., a planner or process modeler) and use it in anothersystem (e.g., a workflow system).
The foregoing problem can be alleviated by devel-oping ontologies that could be used as a foundation formultiple systems (e.g., planning system, workflow sys-tem). Such ontologies would ensure that the differentapplications shared a common terminology, which isthe essence of knowledge sharing and reuse. It is notsurprising, therefore, that the two major thrusts in on-tology research are the development of (a) reusableontologies that span multiple systems and (b) tools thatenable the merging of ontologies and/or translating oneto another. The former assures correct interpretation ofthe knowledge and facilitates the information creationand retrieval process. The latter assures knowledgesharing in a heterogeneous systems environment.
But there is more to ontologies than successfulknowledge sharing and reuse. Ontologies fundamen-tally change the way in which systems are constructed.Today knowledge bases are created from scratch with-out focusing on sharing or reuse. As a result, it generallytakes much too long to create and verify the complete-ness and traceability of the knowledge contents. How-ever, with an ontology focus this can all change. Onecan envision a tomorrow in which ontologies in persist-ent, reusable form are used to effectively and compactlyorganize the knowledge content of databases. The bene-fits of this strategy are dramatic reduction in knowledgebase development time as well as the creation of robustand reliable knowledge bases from pre-existing, veri-fied components.
It is this thinking that drove the creation of IDEON,a unified enterprise ontology specifically designed tosupport integrated planning and execution of enterpriseprocesses. While other enterprise ontologies have fo-cused on enterprise analysis and re-engineering,
IDEON is focused on integrating and managing plan-ning and execution within collaborative distributed en-terprisesa key requirement for supply chainmanagement, command and control, collaborative sys-tems engineering, emergency management, and crisisaction planning and execution. IDEON has been suc-cessfully employed on two key applications which arepresented in this paper. The first application is crisisaction planning and execution. The key challenge onthis application was to create an ontology that supportedplan execution with replanning capabilities in the faceof change events. The second application is IntegratedProduct-Process Development (IPPD). The key chal-lenge on this application was to create an ontology thatwould support (a) the design and tailoring of systemsengineering processes from an IPPD and standardsperspective and (b) the execution and management ofcollaborative systems engineering processes in a dis-tributed environment. What is common to these appli-cations is the integration of model building activitiesand model-based execution capabilities. IDEON wascreated to support this class of problems with appropri-ate domain-specific extensions when needed.
The outline of this paper is as follows. Section 2defines the term ontology and briefly presents thegoals and current themes in ontology research. Section3 reviews the major organizational ontologies in termsof their goals, scope, organizational components, andstatus. Section 4 presents the origins, objectives, andpayoffs of IDEON. Section 5 presents the key designconcepts underlying the development of IDEON. Sec-tion 6 presents and discusses the four complementaryIDEON perspectivesenterprise context view, the or-ganizational view, the process view, and the re-source/product view. Section 7 presents two specificapplications of IDEON: crisis action planning and exe-cution; and IPPD-enabled complex systems engineer-ing. For each application, specific IDEON extensionsare discussed. Section 8 summarizes the IDEON valueproposition for designing, integrating, and managingcollaborative distributed enterprises.
2. ONTOLOGY RESEARCH
The Webster dictionary [Woolf, 1981] defines an ontol-ogy as a particular theory about the nature of being orthe kinds of existents. Intelligent systems from thefield of computer science are responsible for formallyrepresenting these existents, whereas conceptualizationprovides the basis for formally representing a body ofknowledge. Conceptualization consists of a set of con-cepts (e.g., objects), their inter-relationships, as well asother relevant entities about which knowledge is being
36 MADNI, LIN, AND MADNI
expressed. Every knowledge model employs someform of conceptualization, implicit or explicit. An ex-plicit specification (or representation) of this conceptu-alization is called an ontology [Gruber, 1993].Formally, an ontology consists of a set of terms, theirdefinitions, and axioms that inter-relate them [Grunin-ger and Fox, 1995]. The set of terms is normally organ-ized as a taxonomy.
From a domain perspective, an ontology is a formaldescription of the entities within a given domain: theproperties they possess, the relationships they partici-pate in, the constraints they are subject to, and thepatterns of behavior they exhibit. It provides a commonterminology that helps to capture key distinctionsamong concepts in different domains, which aid in thetranslation process. An ontology consists of a core andextensions to express information involving conceptsthat are not part of the core. The main idea behind a coreand extensions is not to clutter the core with everyconceivable concept that might be useful in specificapplications. Rather, the idea is to provide modularextensions to the core thereby allowing a user to tailorthe ontology to suit his/her application needs.
Current goals of ontology research are to: (1) makeontologies sharable through common formalisms andtools; (2) develop ontology content (also called ontol-ogy design); (3) compare and translate ontologies; and(4) compose new ontologies from existing ones. Recentwork in ontology design spans ontologies that representgeneral world knowledge, domain-specific ontologies,and knowledge representation systems that embodyontological frameworks. The ontology engineeringcommunity agrees on the key benefits of integratingontologiessharing and reuse of knowledge. Makingontologies interoperable is highly useful but also chal-lenging. The key to achieving a reasonably high degreeof interoperability is to: (a) compare and contrast exist-ing ontologies to see how they represent the basic typesand aspects of knowledge; and (b) use the results of thisanalysis to identify and resolve the critical issues inintegrating the different ontologies.
3. ORGANIZATIONAL ONTOLOGIES
A number of ontologies for modeling organizationsexist in the ontology literature. While the design goalsof these various ontologies are quite different, each ofthem provides valuable insights for identifying andvalidating key enterprise concepts. The relevant organ-izational ontologies include: TOVE [Fox, Chionglo,and Fadel, 1992; Gruninger and Fox, 1995], KIF [Gene-sereth and Fikes, 1992], Enterprise Ontology [Uscholdet al., 1998], Open Information Model [Meta Data
Coalition, 1999], and CIMOSA [Kosanke, 1995]. In thefollowing paragraphs, each of these ontologies is re-viewed with respect to the goals, scope, accomplish-ments/status, and organizational componentsaddressed.
The Toronto Virtual Enterprise (TOVE) project is aproject at the Enterprise Integration Laboratory, Uni-versity of Toronto. The goal of TOVE is to construct adata model that is expressive enough to represent allaspects of enterprise knowledge at both the genericlevel and the application level. Specifically, the datamodel is intended to: (1) provide a shared terminologyfor the enterprise that each agent can jointly understandand use; (2) define the meaning of each term as pre-cisely and unambiguously as possible; (3) implementthe semantics in a set of axioms that enable TOVE toautomatically deduce the answer to many commonsense questions about the enterprise; and (4) define asymbology for depicting terms and concepts graphi-cally. Table I presents the concepts and their subclassrelations (subclasses) included in the TOVE ontology.
The TOVE project was unique in that it employed aformal approach to ontology design and evaluation.First, ontology specialists collaborated closely withadministrative and engineering personnel from varioustypes of industrial firms (e.g., IBM, Canada; BHP Steel,Australia; Toyo Engineering, Japan) to identify specificproblems that arise in actual enterprises. Because theontology was expressed in KIF, it allowed automateddeduction. So analysis was done in terms of deducingfacts from the ontology represented in KIF. Specifically,the problems identified were used as a guide to create acomprehensive set of competency questions that anenterprise ontology should be able to answer. The com-petency questions identified were then used to guide theselection of concepts and relations that were includedin TOVE. Next, the competency questions and all con-cepts and axioms were formalized in first-order logic tocreate an initial version of the ontology. Finally, theformalized competency questions were used to validateand finalize TOVE.
It should be noted that TOVE is not a single ontol-ogy, but a set of several individual ontologies that linksthe various logical parts of an enterprise model throughappropriate relations. These ontologies represent activi-ties, states (including time), products, organization, andactivity-based cost management. Within each of theseontologies, a number of hierarchical structures (two orthree levels deep) are used to represent clusters of
IDEON: AN EXTENSIBLE ONTOLOGY FOR COLLABORATIVE DISTRIBUTED ENTERPRISES 37
knowledge. Finally, axioms and relations are used tolink knowledge between the various clusters.
The TOVE project employed a more formal ap-proach to ontology design than was used by the otherontologies described in this paper. Therefore, it is morerelevant than the others to this paper. There are, how-ever, some important gaps in the TOVE ontology,which may well be a result of the ambitious scope ofthe TOVE project.
3.2. Knowledge Interchange Format[http://logic.stanford.edu/kif/Hypertext/kif-manual.html]
The Knowledge Interchange Format (KIF) is an exam-ple of an ontology definition language. KIF providesfacilities for defining objects, functions, and relations.KIF, which has declarative semantics, is based on first-order predicate calculus. It provides for the repre-sentation of meta-knowledge and nonmonotonicreasoning rules. KIF could be legitimately consideredan ontology in that it does contain a certain view of theworld. While its representation is far from being at thelevel of detail of the other ontologies, KIF does axioma-tize microtheories of numbers, sets, and lists.
3.3. Enterprise Ontology[http://www.aiai.ed.ac.uk/~entprise/]
The Enterprise Ontology is an outcome of a project atthe University of Edinburgh, AIAI Institute. It has asimilar motivation as TOVE. Its goal is to obtain anenterprise-wide view of an organization which can thenbe used to provide a method and computer tools thathelp capture aspects of a business and analyze these toidentify and compare options for meeting the businessrequirements. The main motivation behind the Enter-prise Ontology is to facilitate enterprise design andanalysis by supporting communications among humansas opposed to machines. Table II presents the majorconcepts used in the Enterprise Ontology.
Because the primary objective of this project was tofacilitate communications between humans, there wasless of an attempt to precisely formalize the concepts.In contrast to the TOVE, the semantics...