|
|||
|
This is version 40.
It is not the current version, and thus it cannot be edited. OverviewThe following lists the semantic mediation service interfaces:
interface ISemanticMediation { search( ConceptExpression, Set<ResourceType>, RemoteSearchFlag ) :: Set<ResourceID> query( QueryExpression, RemoteSearchFlag ) :: Set<QueryResult> } The rest of this page describes each of these services and their dependencies.
Search: Simple Concept-Based Searching
search( ConceptExpression, Set<ResourceType>, RemoteSearchFlag ) :: Set<ResourceID> The arguments for this service are:
We assume that (via a GUI) an initial search string has been converted to a description-logic concept expression. A concept expression can be single concept (like "Biomass") or a complex formula (including nested disjunctive and conjunctive formulas, and so on). The search service depends on the following kepler object manager services: getResourceType( ResourceID ) :: ResourceType getSemanticAnnotations( RemoteSearchFlag ) :: Set<SemanticAnnotationID> getOntology( OntologyID ) :: Set<Ontology> The first operation returns the resource type of a given resource identifier (an LSID). The second operation returns the set of semantic annotations known to the kepler object manager (including annotations stored on remote repositories depending on the value of the search flag). The last operation returns the ontology for a given ontology identifier (also a resource id).
Optimized Remote SearchingIn general, the search operation requires access to all semantic annotations to find matching resources. For example, consider a search expression A and B, i.e., a resource must contribute to both concept A and concept B. To find appropriate matches for this search term, the algorithm must look for annotations that explicitly state A and B as well as those that state only A and only B (which taken together make A and B). Note that an annotation that states only A may be in one repository, while an annotation that states B may be in another. Thus, for remote searches, the search algorithm must gather and consider all remote annotations to find matching resources. The search operation is inherently centralized because of this situation. We may reduce the cost of search by adding additional services that can be executed locally at each repository and by altering the search algorithm, making it slightly less centralized. The additional services are:
getRepositories() :: Set<RepositoryID> getResources( RepositoryID, Set<ResourceType> ) :: Set<ResourceID> partialSearch( RepositoryID, ConceptExpression, ResourceID ) :: Set<ConceptExpression> Using these operations, the search algorithm would procede as follows, assuming that the remote search flag has been selected. With the getRepositories service, the algorithm first obtains the available repositories from the local kepler object manager. The algorithm selects the first returned repository and with the getRepositories service, obtains the relevant resources in the respository. For each resource in the repository, the partialSearch service is used, which returns the parts of the concept expression that the resource matches (e.g., just the concept A). The algorithm then moves to the next repository, performing the same steps. However, for those resources already having partial matches (from the previous step), the algorithm reformulates the search term given to partialSearch to include only the additional required parts of the concept expression (e.g., just the concept B). Once a complete match is found, the resource is considered a match and is not further checked. Finally, the algorithm repeats the process until all repositories have been examined.
Query: Complex Concept-Based Searching
query( QueryExpression, RemoteSearchFlag ) :: Set<QueryResult>
|
This material is based upon work supported by the National Science Foundation under award 0225676. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF). Copyright 2004 Partnership for Biodiversity Informatics, University of New Mexico, The Regents of the University of California, and University of Kansas |