ontology classifications acknowledgement abstract content from simulation systems is useful in...
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Ontology Classifications
Acknowledgement
AbstractContent from simulation systems is useful in defining domain ontologies. We describe a digital library process to generate and leverage domain ontologies to support simulation systems tasks. Workflow ontologies may be used to define compositions of simulation-related services. Simulation model ontologies may be used in customizing collection management systems for tasks such as organization, interface construction, and metadata record generation.
Improving Simulation Management Systems through Ontology Generation and Utilization
Targeted Simulation Systems
Jonathan P. Leidig, Edward A. Fox, Kevin Hall, Madhav Marathe, Henning Mortveit Contact: [email protected]
Simulation Workflows
Ontology Generation and Technologies
Model Ontology-Utilizing Digital Library Services
This work has been partially supported by NSF SDCI Grant OCI-1032677, NSF Nets Grant CNS-062694, CNS-0831633, HSD Grant SES-0729441, CDC Center of Excellence in Public Health Informatics Grant 2506055-01, NIH-NIGMS MIDAS GM070694-05/06, and DTRA CNIMS Grant HDTRA1-07-C-0113.
Related Article:Jonathan Leidig, Edward Fox, Kevin Hall, Madhav Marathe, Henning Mortveit. SimDL: A Model Ontology Driven Digital
Library for Simulation Systems. ACM/IEEE Joint Conference on Digital Libraries, Ottawa, Canada, June 13-17, 2011.
Prototype Implementation & Applications SupportedSwiss Tropical InstituteMalaria modelsDataset analysis
Cyberinfrastructure Network ScienceNetwork simulationsNetwork analysis
Content staging Interface presentation of model parametersInput parameter gatheringInput configuration generationInput configuration validation
Input, result, and analysis storing and retrievingGathering provenance from workflow stagesModel-specific indexingFaceted browsingRanked searching
Ontology FormatsXML schemaRDF
Ontology GenerationHuman-intensive model ontology
generationMetadata description set generation
softwareHarmonization yields context-specific
ontologies
HarmonizationRDF descriptionsSoftware guided human mapping
Ontology TermsDublin Core termsInfrastructure and collection-level terms5S framework termsModel and context-specific terms
SchemaInput
ConfigurationOutput Result
Dataset
SimulationProcess
Analysis
AnalysisProcess
Documentation Annotation
Experiment
Epidemiology ApplicationsMalaria modelsInfluenza modelsODE and agent-based modelsModels from NIH MIDAS communityModels from Gates Foundation
community
Analysis applicationsNetwork analysisModel-specific analysis
Digital Library IntegrationInstitutional infrastructureNetwork science cyberinfrastructure
Virginia Bioinformatics InstituteBiological domainsInfectious diseases (e.g., H1N1, H5N1)Biological organsInfrastructure domainsTransportation systemsComputer and wireless networks
Simulation model ontology
Input schema
Result schema
Validation
Compatibleanalyses
Languagesupport
Model ontology
relationships(e.g., malaria,
influenza)
Modelontology
Modelontology
Modelontology
Context-specific ontologyContext ontology
relationships(e.g., epidemiology,
network science)Context ontology
Context ontology
Context ontology
Domain-specific meta-ontology
Recommending and Selecting
Model-SpecificOntologies
Model OntologyHarmonization
Context-SpecificOntologies
Context OntologyHarmonization
Domain MetaOntologies
Sample ContentInput Files
Result Summaries
Analyses
Result FilesProducts
Model-SpecificDescription Sets
HarmonizedDescription Sets
Example Records(XML, RDF)
DB MetadataSchemas (DDL)