SONet: Scientific Observations Network Semtools: Semantic Enhancements for Ecological Data Management Mark Schildhauer, Matt Jones, Shawn Bowers, Huiping Cao

Outline Project overview Observational data models (SONet) OBOE re-factored O&M EQ SONet core - domain ontologies Semantic tools for observational data (Semtools) Semantic annotation OM Query language Querying annotated observational metadata and data

Challenges Mark and Matt fill in …

Our Approach The SONet Project -Define a core observational model (based on OBOE, O&M, and others) … progress made on OBOE/O&M alignment -Identify and develop domain-specific vocabularies for describing observational data semantics -Define a set of scientific use cases for data interoperability -Develop a set of interoperability “demonstration prototypes” The Semtools Project -Incorporate OBOE and semantic annotations into existing Metacat and Morpho metadata tools -Focus on ecology data and use cases

WeightMass Unit Biomass usesStandard Gram is-a Bio.EntityTree Leaf LitterTree LeafWet WeightDry Weight Observation Measurement SiteSpeciesIndMass GCE6Picea Rubens GCE6Picea Rubens GCE7Picea Rubens ………… Data Structural Meatadata Mass hasMeasurement OBOE Semantic Annotation Domain-Specific Ontology is-a has-part hasCharac teristic is-a part-of is-a ofEntity usesStandard ofCharacteristic

Observational data models OBOE 1.0 O&M (ISO) EQ SONet Domain Ontologies Plant Traits SBC Ongoing

OBOE Core 1.0 Extensible Observation Ontology (OBOE) [1] 7 Entity Characteristic Observation Measurement Protocol Standard hasMeasurement ofCharacteristic usesProtocol usesStandard ofEntity hasContext 1..1 * * * * * * hasValue 1..1 * *

OBOE re-factored (cont.) Shawn adds more (2-3 slides) on OBOE …

O&M ([2]) 9 Feature – Abstraction of real world phenomena (Def. 4.5) – E.g., Tree Feature type – Class of features having common characteristics (Def. 4.6) Property – Facet or attribute of an object referenced by name (Def. 4.14) – E.g., Height Property-type – Characteristic of a feature type (Def. 4.15) Feature Property carrierOfCharacteristic

Feature Property OM_Observation observedProperty featureOfInterest carrierOfCharacteristic O O&M (Cont.) Observation –Act of observing a property (Def. 4.10) Measurement –Set of operations having the object of determining the value of a quantity (Def. 4.9) OM_Observation –An instance of feature type

Feature Property OM_Observation Result hasResult Procedure usesProcedure carrierOfCharacteristic observedPro perty featureOfInterest O&M (cont.) Observation procedure – Method, algorithm or instrument, or system of these which may be used in making an observation (Def. 4.11) – The base class OM_Process Observation result – Estimate of the value of a property determined through a known procedure. Any type

Feature ObservationContext Property OM_Observation Result relatedObservation hasResult Procedure usesProcedure ObservationContext Some observations depend on other observations to provide context in understanding the result. (Sec ) Link a OM_Observation to another OM_Observation, with the role name relatedObservation for the target carrierOfCharacteristic observedPro perty featureOfInterest O&M (cont.)

Entity Feature CharacteristicProperty Observation Measurement OM_Observation Protocol Procedure Result Standard Entity hasContextObservationContext Entity CharacteristicMeasurement Observation Standard hasMeasurement ofEntity Protocol Feature ObservationContex Property OM_Observation Result carrierOfCharacteristic observedProper ty featureOfInterest relatedObservation hasResult Procedure usesProcedure 13 hasValue usesProtocolusesStandard ofCharacteristic hasContext

EQ ([4]) Entity – Describes some object in the real world. E.g., eye Quality – Describes an entity's attribute and its attribute value. E.g., color = red, means eye’s color is red. Character – Composed of Entity and Quality attributes to represent the meaning of which entity's which attribute. E.g., eye's color. Character state – Quality value. E.g., “red” to represent eye’s color is red).

Comparison OBOE re-facoredO&MEQ EntityFeatureEntity CharacteristicPropertyQuality attribute Observation OM_Observation MeasurementQuality value or Character state ProtocolProcedure Standard + ResultResult hasContextObservationContext

SONet core - domain ontology: trait Trait group: Centre d'Écologie Fonctionnelle et Évolutive (CÉFÉ) [5]

SONet core -domain ontology: SBC Group: Santa Barbara Coastal (SBC) Lont Term Ecological Research (LTER) [6]

Plant – iPlant group ([7]) PATO ([8]) – Phenotypic Quality Ontology – Automatic tool to convert PATO to be compatible with SONet core model SONet core -domain ontology: ongoing

How to use SONet core model? SONet-core Morpho data annotation tool to generate data instances for you automatically OM query language OM query framework for data discovery O&M Write your own xml file to contain the observation and measurement data Write Schematron [3] file to validate whether the data xml file No tool report! 19

Tools Morpho data annotation tool to generate data instances for you automatically Observation and Measurement (OM) query language Framework for querying annotated observational data 20

Semantic Annotation

OM Query example Tree[Height > 5 Meter] -Return datasets that have at least one Tree observation containing a Height measurement with a value greater than 5 Meters Tree[Height > 5 Meter], Soil[Acidity >= 7 pH] -Return datasets that contain at least one Tree observation (having a measurement where the Height was greater than 5) and at least one Soil observation (having an Acidity measurement of 7 or greater) 22

OM Query Example (cont.) Tree[Height > 5 Meter] -> Soil[Acidity >= 7pH] -Incorporates context via the "->” (arrow) symbol, which can be read as "contextualized by" or "has context" -Returns datasets that contain at least one Tree observation (with the corresponding height value) where the observation was taken within the context of a Soil observation (with the corresponding acidity value) 23

Query framework Annotation 1Annotation 2 Annotation 3 Annotation 4 File 1 File 2File 3File 4 Offline data processing Result Q1Result Q2 … …. OBOE-aware DB … 24 OBOE domain model Annotation interface Query 1Query 2 … …. Online query engine

Offline data processing Annotation as a bridge … Annotation 1Annotation 2 Annotation 3 Annotation 4 File 1 File 2File 3File 4 Measurement type table Observation Type table Entity type table Context type table Map 25 OBOE-aware DB

Annotation as a bridge … Annotation 1Annotation 2 Annotation 3 Annotation 4 File 1 File 2File 3File 4 Measurement type table (for ann1, 2, …) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) 26 OBOE-aware DB

Offline data processing (raw data loading) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) Measurement type table (for ann1, 2, …) Raw data loading … Annotation 1Annotation 2 Annotation 3 Annotation 4 File 1 File 2File 3File 4 Table 4 Table 3 Table 2 Table 1 … 27 OBOE-aware DB

Offline data processing (data materialization) Measurement table Observation table Entity table Context table Measurement type table (for ann1, 2, …) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) Table 4 Table 3 Table 2 Table 1 … Data materialization … Annotation 1Annotation 2 Annotation 3 Annotation 4 File 1 File 2File 3File 4 28 OBOE-aware DB

Measurement Table (for file 1, 2, …) Observation table (for file 1, 2, …) Entity table (for file 1, 2, …) Context table (for file 1, 2, …) Measurement type table (for ann1, 2, …) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) Table 4 Table 3 Table 2 Table 1 … Data materialization … Annotation 1Annotation 2 Annotation 3 Annotation 4 File 1 File 2File 3File 4 29 OBOE-aware DB

Measurement type table (for ann1, 2, …) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) Table 4 Table 3 Table 2 Table 1 … Query strategy 1 Online query engine (query re-writing over raw data) 30 Measurement Table (for file 1, 2, …) Observation table (for file 1, 2, …) Entity table (for file 1, 2, …) Context table (for file 1, 2, …) OBOE-aware DB

Measurement type table (for ann1, 2, …) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) Table 4 Table 3 Table 2 Table 1 … Query strategy 2 Online query engine (query re-writing over materialized data) 31 Measurement Table (for file 1, 2, …) Observation table (for file 1, 2, …) Entity table (for file 1, 2, …) Context table (for file 1, 2, …) OBOE-aware DB

Measurement type table (for ann1, 2, …) Observation type table (for ann1, 2, …) Entity type table (for ann1, 2, …) Context type table (for ann1, 2, …) Map (for ann1, 2, …) Table 4 Table 3 Table 2 Table 1 … Query strategy n?? Online query engine 32 Measurement Table (for file 1, 2, …) Observation table (for file 1, 2, …) Entity table (for file 1, 2, …) Context table (for file 1, 2, …) Other materialization/de- normalization?? RDF triple store? OBOE-aware DB

Ontology Editing Tools Protégé plug-in -For creating and editing OBOE-compatible ontologies -Form-based UI -Generates “low-level” OWL constraints/axioms

References [1] Shawn Bowers and Joshua S. Madin and Mark P. Schildhauer, A Conceptual Modeling Framework for Expressing Observational Data Semantic. In ER 2008, [2] OpenGIS observations and measurements encoding standard (O&M): [3] Schematron ISO standard: [4] EQ: [5] CECF: [6] SBC LTER: [7] iPlant: [8] PATO: 34