- From: Stuart Naylor <indtec@eircom.net>
- Date: Tue, 17 Apr 2001 15:30:37 +0100
- To: <jos.deroo.jd@belgium.agfa.com>
- Cc: <www-rdf-interest@w3.org>
- Message-ID: <DFEDIAMBMMNMHKCCJJBLIEHOCFAA.indtec@eircom.net>
Obviously I nicked this from the ebXML standard http://www.ebxml.org/ to get a full overview. Business Process and Business Document Analysis Overview 12 Copyright C ebXML 2001. All Rights Reserved. 7 Business Process Modeling 284 7.1 Overview 285 Business process models define how business processes are described. Business processes 286 represent the "verbs" of electronic business and can be represented using modeling tools. The 287 specification for business process definition enables an enterprise to express its business 288 processes so that they are understandable by other enterprises. This enables the integration of 289 business processes within an enterprise or between enterprises. 290 Business process models specify interoperable business processes that allow business partners to 291 collaborate. While business practices vary from one organization to another, most activities can be 292 decomposed into business processes that are more generic to a specific type of business. This 293 analysis, utilizing business modeling, will identify business processes and business information 294 metamodels that can likely be standardized. The ebXML approach looks for standard reusable 295 components from which to construct interoperable processes and components. 296 7.2 Business Process and Information Metamodel 297 The Metamodel is a description of business semantics that allows Trading Partners to capture the 298 details for a specific business scenario using a consistent modeling methodology. A Business 299 Process describes in detail how Trading Partners take on roles, relationships and responsibilities to 300 facilitate interaction with other Trading Partners in shared Business Process. The interaction 301 between roles takes place as a choreographed set of Business Transactions. Each Business 302 Transaction is expressed as an exchange of electronic Business Documents. The sequence of the 303 exchange is defined by the Business Process, messaging and security considerations. Business 304 Documents are composed from re-useable business information components. At a lower level, 305 Business Processes can be composed of re-useable Common Business Processes, and Business 306 Information Objects can be composed of re- useable Business Information Objects that may be 307 composed of core components and domain components. 308 The Metamodel supports requirements, analysis and design viewpoints that provide a set of 309 semantics (vocabulary) for each viewpoint and forms the basis of specification of the semantics 310 ebXML BP/CC Analysis Team March 2001 and artifacts that are required to facilitate business process and information integration and 311 interoperability. 312 An additional view of the Metamodel, The Specification Schema, is also provided to support the 313 direct specification of the nominal set of elements necessary to configure a runtime system in order 314 to execute a set of ebXML business transactions. By drawing out modeling elements from several 315 of the other views, the Specification Schema forms a semantic subset of the Metamodel. 316 The Specification Schema is available in two stand-alone representations, a UML profile, and a 317 DTD. Figure 7.2-1 shows the high-level elements of The Specification Schema. 318 I really liked the spec until schema started to raise it's ugly head. The ebXML standard is very good but it is still a explicit profiling mechanism. Then the Web god doth speak http://www.scientificamerican.com/2001/0501issue/0501berners-lee.html Ontologies Of course, this is not the end of the story, because two databases may use different identifiers for what is in fact the same concept, such as zip code. A program that wants to compare or combine information across the two databases has to know that these two terms are being used to mean the same thing. Ideally, the program must have a way to discover such common meanings for whatever databases it encounters. A solution to this problem is provided by the third basic component of the Semantic Web, collections of information called ontologies. In philosophy, an ontology is a theory about the nature of existence, of what types of things exist; ontology as a discipline studies such theories. Artificial-intelligence and Web researchers have co-opted the term for their own jargon, and for them an ontology is a document or file that formally defines the relations among terms. The most typical kind of ontology for the Web has a taxonomy and a set of inference rules. The taxonomy defines classes of objects and relations among them. For example, an address may be defined as a type of location, and city codes may be defined to apply only to locations, and so on. Classes, subclasses and relations among entities are a very powerful tool for Web use. We can express a large number of relations among entities by assigning properties to classes and allowing subclasses to inherit such properties. If city codes must be of type city and cities generally have Web sites, we can discuss the Web site associated with a city code even if no database links a city code directly to a Web site. Inference rules in ontologies supply further power. An ontology may express the rule "If a city code is associated with a state code, and an address uses that city code, then that address has the associated state code." A program could then readily deduce, for instance, that a Cornell University address, being in Ithaca, must be in New York State, which is in the U.S., and therefore should be formatted to U.S. standards. The computer doesn't truly "understand" any of this information, but it can now manipulate the terms much more effectively in ways that are useful and meaningful to the human user. With ontology pages on the Web, solutions to terminology (and other) problems begin to emerge. The meaning of terms or XML codes used on a Web page can be defined by pointers from the page to an ontology. Of course, the same problems as before now arise if I point to an ontology that defines addresses as containing a zip code and you point to one that uses postal code. This kind of confusion can be resolved if ontologies (or other Web services) provide equivalence relations: one or both of our ontologies may contain the information that my zip code is equivalent to your postal code. Our scheme for sending in the clowns to entertain my customers is partially solved when the two databases point to different definitions of address. The program, using distinct URIs for different concepts of address, will not confuse them and in fact will need to discover that the concepts are related at all. The program could then use a service that takes a list of postal addresses (defined in the first ontology) and converts it into a list of physical addresses (the second ontology) by recognizing and removing post office boxes and other unsuitable addresses. The structure and semantics provided by ontologies make it easier for an entrepreneur to provide such a service and can make its use completely transparent. It is very hard to explain relevance because it is totally dependent on the quality of ontology references. We have two applications each with a internal application ontology both reference external more generic ontologies which hopefully at some converge on a singular ontology reference hopefully at the first hop. Relevance is a reverse of TBLs Search agents where we know where the data is we just have to find the question. Like the command line parameter TRACERT [DNSNAME] a list of each hop from one router to the next across the net is displayed in order of occurrence. With two destinations and a common source I guess this is what I would call a expression of relevance. This is about as far as I have got with my 'Chess' engine as a lateral hop is exponential to a vertical and I am having much more fun learning the finer points of gambits. The AI is quite easy it's the construction of the business process and data ontology's that is causing me the headaches. -----Original Message----- From: www-rdf-interest-request@w3.org [mailto:www-rdf-interest-request@w3.org]On Behalf Of jos.deroo.jd@belgium.agfa.com Sent: 17 April 2001 10:00 To: indtec@eircom.net Cc: www-rdf-interest@w3.org Subject: Re: Semantic API > [...] fresh thoughts! > What I have seen so far from anyone out the is still explicit declaration as > opposed to inference and selection by relevance. what do you mean with *selection by relevance* ? -- Jos De Roo, AGFA http://www.agfa.com/w3c/jdroo/
Received on Tuesday, 17 April 2001 08:37:29 UTC