1. Subgroup 1 Collect interoperability requirements Define common, unified data model Engage tool & data providers, data consumers Subgroup 2 Identify and catalog common observation types Engage data providers and information managers Subgroup 3 Define extension ontologies of scientific terms Build on outputs of group 2 Engage range of domain scientists Subgroup 4 Demonstrate interoperability across multiple systems Define and prototype demonstration projects Provide infrastructure to support other groups Objectives of SONet Broad Objectives Address semantic interoperability in environmental & earth sciences data [sharing, discovery, integration] by building a network of practitioners (SONet), including domain & computer scientists, & information mgrs to create generic, cross-disciplinary data interoperability solutions Immediate Goals to Develop An extensible & open observations data model (“core model”) to unify existing domain-specific approaches A semantic (ontology) framework for scientific terminology and corresponding domain extensions Demonstration prototypes using these to address critical data interoperability issues Define and host Data Interoperability Challenge to test and refine above approaches Community workshops … to bring together project members, data managers, domain scientists, computer scientists, and members of the larger environmental informatics community Workshop 1: Collect detailed requirements and use cases to frame a “Scientific Observations Interoperability Challenge”; begin defining core model (held Oct, 2009) Workshop 2: Discuss various data models in terms of addressing “Scientific Observations Interoperability Challenge”; refine core model (expected Summer, 2010) Workshop 3: Roll-out of operational prototype; early evaluation and feedback Workshop 4: Training; further evaluative discussion, and plan SONet sustainability Similarities among Observational Data Models Prototype Architecture for Applying Semantic Annotation Subgroup 1: Core Data Model for Observations Subgroup 2: Catalog of Common Field Observations Subgroup 3: Scientist-Oriented Term Organization Subgroup 4: Demonstration Projects Core SONet Team ID# IN51B-1046 SONet: Towards a Shared Scientific Observation Model M. Schildhauer* 1, H. Cao 1, S. Bowers 2, M. Jones 1, D.L. McGuinness 3, L.E. Bermudez 4 1. NCEAS, Santa Barbara, CA, USA2. Gonzaga University, Spokane, WA, USA 3. McGuinness Associates, Latham, NY, USA 4. Southeastern Universities Research Association, Washington DC, USA * Contact: schild@nceas.ucsb.edu Entity Context CharacteristicMeasurement Observation Standard hasCharacteristichasMeasurement ofEntity hasContext usesStandard Protocol usesProtocol FeatureOfInterest ObservationContext ObservedProperty OM_Observation Result carrierOfCharacteristic forProperty ofFeature relatedContext Observatioin hasResult OM_Process usesProcedure PrecisionValue hasPrecision ofCharacteristic hasValue References: [1] Shawn Bowers and Joshua S. Madin and Mark P. Schildhauer, A Conceptual Modeling Framework for Expressing Observational Data Semantic. In ER 2008, 41-54. [2] OpenGIS observations and measurements encoding standard (O&M): http://www.opengeospatial.org/standards/om Extensible Observation Ontology (OBOE) [1] O&M [2] EntityFeatureOfInterest CharacteristicObservedProperty MeasurementOM_Observation Protocol OM_Process Result Standard Value Precision Context ObservatioinContext SiteSpeciesIndMass… GCE6Picea Rubens175.13… GCE6Picea Rubens2179.81… GCE7Picea Rubens1443.20… …………… observation “o1” entity “Plot” measurement “m1” key yes Characteristic “PoltCode” Standard “Nominal” observation “o2” entity “Tree” measurement “m2” key yes Characteristic “SpeciesName” Standard “TaxonomicName” measurement “m3” key yes Characteristic “SpeciesLocalNo” Standard “LocalNumber” measurement “m4” Characteristic “TreeMass” Standard “Numerical” context identifying yes “o1” map “Site” to “m1” map “Species” to “m2” map “Ind” to “m3” map “Mass” to “m4” observation “o1” entity “Plot” measurement “m1” key yes Characteristic “PoltCode” Standard “Nominal” observation “o2” entity “Tree” measurement “m2” key yes Characteristic “SpeciesName” Standard “TaxonomicName” measurement “m3” key yes Characteristic “SpeciesLocalNo” Standard “LocalNumber” measurement “m4” Characteristic “TreeMass” Standard “Numerical” context identifying yes “o1” map “Site” to “m1” map “Species” to “m2” map “Ind” to “m3” map “Mass” to “m4” (b) Semantic annotation to dataset (a) (a) Dataset http://sonet.ecoinformatics.orghttp://sonet.ecoinformatics.org Acknowledgements: NSF OCI INTEROP 0753144 Prototype Architecture ProductivityWeightMass Unit Kilogram Biomass usesStandard Gram is-a Bio.Entity Tree Leaf LitterTree LeafWet WeightDry Weight Observation Measurement SiteSpeciesIndMass GCE6Picea Rubens175.13 GCE6Picea Rubens2179.81 GCE7Picea Rubens1443.20 ………… PlaceTreatPlotLL sthC10.003 sthC10.002 sthN10.008 ………… Data Structural Meatadata Mass LL hasMeasurement 0.001 OBOE Semantic Annotation Domain-Specific Ontology is-a has-part hasChara cteristic is-a part-of is-ahas-mulitplier usesHase Standard ofEntity ofCharacteristic usesStandard ofCharacteristic