Lifecycle of Semantic Web Processes

semantic Web process  An abstract Web process specifies the controlflow and data-flow of an application  Does not define which Web services will be executed at runtime  Abstracting away the resource descriptions allows:  Web processes modeling dynamic packages to be portable  Reuse processes to generate different process instance at runtime Abstract semantic Web processsemantic Web process AWS Shopping AWS Golf AWS Dinner AWS Movie AWS Fishing Abstract semantic Web process AWS Abstract Web service Designer AWS Check Weather Not sunny Sunny E-Tourism Ontology A dynamic package that includes a fishing experience in the morning, takes the tourist for shopping, schedules a golf game or a movie in the afternoon, and a dinner at night. Dynamic Packaging Web Process Generator  Concrete dynamic package Web processes are automatically created using a suitable generator.  The generator may optimize the concrete process based on the availability of Web services.  Each service is turned into an executable service by specifying the locations of the Web service implementation Concrete Dynamic Packaging Web Process  An abstract Web process typically originates several concrete processes.  Each Web process invokes different Web services  The processes are valid from a functional pointof-view, but they may not generate valid dynamic package  Need to follow time or cost constraints Conditional Planning  Select a schedule that is consistent with the overall dynamic package  Conditional planning  The main objective of the planning is to schedule an appropriate timeframe during which the tourist will realize a particular activity referenced by a dynamic package Dynamic Packages and QoS  At this stage  All the dynamic packages are valid  Some packages may take more time to execute than others or be more expensive for the tourist  They have a distinct QoS (Quality of Service)  Compute the QoS  Use the SWR algorithm  Ranking and selecting  Rank and select the packages which have a set of characteristics that is more similar with the tourist QoS requirements Examples of Ontologies Examples of Real Ontologies MGED Ontology  The MGED Ontology  Provide standard terms for the annotation of microarray experiments.  Terms will enable unambiguous descriptions of how the experiment was performed.  212 classes, 101 properties.  The MGED Ontology is being developed within the microarray community to provide consistent terminology for experiments.  This community effort has resulted in a list of multiple resources for many species.  Approximately 50 other ontologies for different species  The concepts are structured in DAML+OIL and available in other formats (rdfs) The MGED Ontology is Structured in DAML+OIL using OILed 3.4 Source: "The MGED Ontology is an Experimental Ontology,“ 5th Annual Bio-Ontologies meeting (Edmonton, Canada Aug. 2002) MGED Ontology consists of classes, properties, and individuals (instances) Source: "OntologyEntry in MAGE," MGED 6 (Aix-en-Provence, France Sept., 2003) MGED Ontology: BiomaterialDescription: BiosourceProperty: Age Source: "The MGED Ontology is an Experimental Ontology,“ 5th Annual Bio-Ontologies meeting (Edmonton, Canada Aug. 2002) Examples of Real Ontologies OBO  OBO (Open Biological Ontologies)  Is an umbrella organization for structured shared controlled vocabularies and ontologies for use within the genomics and proteomics domains. Examples of Real Ontologies GO Ontology  Gene Ontology (GO)  Describes gene products in terms of their  Associated biological processes,  cellular components and  Molecular functions in a species-independent manner. Component ontology 1379 terms 212 KB Process ontology 8151 terms 4.82 MB Function ontology 7278 terms 1.16 MB GO format flat files, XML, MySQL