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This is version 64.
It is not the current version, and thus it cannot be edited. Intended audienceThis document is intended for SEEK and Kepler developers. It is a DRAFT DESIGN DOCUMENT and does not reflect functionality as it currently exists in Kepler or SEEK. Comments and feedback are appreciated.
OverviewThe following lists the semantic-mediation service interfaces:
interface ISemanticMediation { Set<ResourceID> search( ConceptExpression, Set<ResourceType>, RemoteFlag ) Set<QueryResult> query( QueryExpression, RemoteFlag ) Boolean match( ConceptExpression, ResourceID, RemoteFlag ) Boolean compatible( ResourceID, Connection, ResourceID, StructTypeFlag, RemoteFlag ) Set<ResourceID> searchCompatible( ResourceID, Port, StructTypeFlag, RemoteFlag ) Set<StructMapping> compose( ResourceID, Connection, ResourceID, RemoteFlag ) Set<StructMapping> merge( ResourceID, Connection, ResourceID, RemoteFlag ) ConceptExpression semanticTypeConcepts( ResourceID, String, RemoteFlag ) // for summarizing annotations } The rest of this page describes each of these services and their dependencies.
Search: Simple Concept-Based Searching
Set<ResourceID> search( ConceptExpression, Set<ResourceType>, RemoteFlag ) The arguments for this service are:
The service returns a set of resources (as LSIDs) that have semantic types "matching" the given search term. 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). We assume each concept is associated to the ontology it is defined in (e.g., where the ontology is implied by the concept identifier). The search service depends on the following kepler object manager services: ResourceType getResourceType( ResourceID ) Set<SemanticTypeID> getSemanticAnnotations( RemoteSearchFlag ) Set<Ontology> getOntology( OntologyID ) The first operation returns the resource type of a given resource identifier (an LSID). The second operation returns the set of semantic types known to the kepler object manager (including semantic types stored on remote repositories depending on the value of the remote flag). The last operation returns the ontology for a given ontology identifier (also a resource id). Note that this last operation could be used with an ontology service, e.g., the simple one described at the end of this page[simple ontology service].
Optimized Remote SearchingIn general, the search operation requires access to all semantic types 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 semantic types 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 a semantic type that states only A may be in one repository, while a semantic type that states only B may be in another. Thus, for remote searches, the search algorithm must obtain and consider all remote semantic types to find matching resources, making the search operation inherently centralized. 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:
Set<RepositoryID> getRepositories() Set<ResourceID> getResources( RepositoryID, Set<ResourceType> ) Set<ConceptExpression> partialSearch( RepositoryID, ConceptExpression, ResourceID ) Using these operations, the search algorithm would procede as follows, assuming that the remote 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
Set<QueryResult> query( QueryExpression, RemoteFlag )
Match: Checking Matching Resources
Boolean match( ConceptExpression, ResourceID, RemoteFlag )
Compatible: Checking Semantically Well-Formed Connections
Boolean compatible( ResourceID, Connection, ResourceID, StructTypeFlag, RemoteFlag )
SearchCompatible: Searching for Semantically Well-Formed Connections
Set<ResourceID> searchCompatible( ResourceID, Port, StructTypeFlag, RemoteFlag )
Compose: Suggesting Well-Structured Actor Connections
Set<StructMapping> compose( ResourceID, Connection, ResourceID, RemoteFlag )
Merge: Suggesting Simple Merging of Heterogeneous Datasets
Set<StructMapping> merge( ResourceID, Connection, ResourceID, RemoteFlag )
SemanticType: Summarizing Semantic Annotations
ConceptExpression semanticType( ResourceID, String, RemoteFlag )
A Simple Ontology Interface
interface ISimpleOntologyAccess { Set<ConceptID> getConcepts( OntologyID ) Set<RoleID> getRoles( OntologyID ) :: Set<RoleID> Set<ConceptID> getMatchingConcepts( OntologyID, String ) Set<ConceptID> getMatchingRoles( OntologyID, String ) Set<ConceptID> getSubConcepts( OntologyID, ConceptID, DirectFlag ) Set<ConceptID> getSuperConcepts( OntologyID, ConceptID, DirectFlag ) Set<RoleID> getSubRoles( OntologyID, RoleID, DirectFlag ) Set<RoleID> getSuperRoles( OntologyID, RoleID, DirectFlag ) Booolean satisfies( ConceptExpression, ConceptExpression ) }
Comments
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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 |