Encyclopedia of Computer Science and Technology

ontologies and data models 351online service continued to struggle in the 2000s, essentiallyabandoning the ISP part of its business. MeanwhileCompuServe, after peaking in the 1990s, gradually shrankto a shadow of its former self. Even mighty Microsoft hashad trouble growing its Microsoft Network (MSN), reinventingit in 1999 as a Web portal and then trying to integrateit more closely with its operating system and softwareproducts as “Windows Live” as well as providing servicessuch as instant messaging, blogging, and picture sharing.The long-term prospects for AOL and other commercialonline services are uncertain. Many of the advantagesthese services had until the late 1990s have diminished.For example, the once mutually incompatible e-mail systemsof online services have been replaced by standardInternet e-mail protocols, so there is little advantage tousing a particular service for e-mail. Users can obtaine-mail accounts from a variety of ISPs or through freeWeb-based services such as hotmail.com. Content such asnews, video, and music (see streaming) is available frommany Web sites, and most companies now offer extensiveonline technical support for their products. At thesame time, attempts to support content-rich sites througheither advertising or a subscription model have largelyfoundered. For services such as AOL, the ultimate questionis whether the parts of the service still form a sufficientlycompelling whole.Further ReadingAmerica Online. Available online. URL: http://www.aol.com.Accessed August 16, 2007.Bourne, Charles P. A History of Online Information Services, 1963–1976. Cambridge, Mass.: MIT Press, 2003.Kaufeld, John. AOL for Dummies. Hoboken, N.J.: Wiley, 2004.Microsoft Network. Available online. URL: http://www.msn.com.Accessed August 14, 2007.Swisher, Kara. There Must Be a Pony in Here Somewhere: The AOLTime Warner Debacle. New York: Three Rivers Press, 2004.ontologies and data modelsA persistent problem in artificial intelligence (see artificialintelligence) is how to provide a software systemwith a model that it can use to reason about a particularsubject or domain. A data model or ontology basically consistsof classes to which the relevant objects might belong,relationships between classes, and attributes that objects inthat class can possess. (For implementation of these ideaswithin programming languages, see classes and objectorientedprogramming.)For example, a business ontology might include classessuch as:• Entity—a business or person• Supplier—an Entity that provides wholesale goods orservices• Customer—an Entity that buys the company’s goodsor services• Contractor—an Entity that performs work for thecompany on contractIn the above list it can be seen that the last three classesall include as their parent or “superclass” the class Entity.Another way to put this is to say that the Entity class “subsumes”the last three classes. These relationships can beeasily shown in tree diagrams, with the most general or“universal” class at the top and the more specialized classesextending downward and outward. The process of definingrelated classes and specifying criteria for the inclusion ofan object in a class is called “partitioning.” (Readers familiarwith set theory will also note that the language of sets,subsets, and inclusion also works well with this scheme.)Classes can have other types of relationships. For example,a class can be defined as being “part of” a structurebuilt from several classes. For example, a Customer mightbe part of a Transaction class.Attributes are assigned to classes as appropriate. Notein the example above that when attributes such as contactinformation are defined for the Entity class, they will alsoapply to the descendant classes Supplier, Customer, andContractor.ImplementationOntologies can be used to provide guidance to a variety oftypes of programs (for example, see expert system, naturallanguage processing, and software agent). Thusif an automatic news summarizer program encounters astory that includes references to opposing lawyers and legalissues, it could apply an ontology that defines the likelyrelationship of the participants in the case.Creating useful ontologies is quite labor intensive interms of the human thinking and coding involved. However,there have been substantial efforts in recent years tocreate anthologies for many fields, particularly in biologyand genetics. The Web Ontology Language (OWL) is apopular tool for creating ontologies that can be used tomake Web content more understandable to programs (seesemantic web).Meanwhile, an ambitious and long-running projectcalled Cyc (for Encyclopedia) under the direction of DouglasLenat has been engaged in creating what amounts tovast ontologies for many of the domains included in everydayhuman life as well as specialized fields of knowledge. Alarge portion of this work has been made available as opensource.Further ReadingCYCorp. Available online. URL: http://www.cyc.com/. AccessedOctober 21, 2007.Gasevic, Dragan, Dragan Djuric, and Vladan Devedzic. ModelDriven Architecture and Ontology Development. New York:Springer, 2006.Macy, Lee W. OWL: Representing Information Using the Web OntologyLanguage. Victoria, B.C., Canada: Trafford Publishing,2005.Nigro, Hector Oscar, Sandra Gonzalez Cisaro, and Daniel Xodo,eds. Data Mining with Ontologies: Implementations, Findings,and Frameworks. Hershey, Penn.: Idea Group, 2007.Web Ontology Language (OWL), World Wide Web Consortium.Available online. URL: http://www.w3.org/2004/OWL/.Accessed October 21, 2007.