Ontologies: Weather and Ontologies: Weather and Flight Information - PowerPoint PPT Presentation

Ontologies: Weather and Ontologies: Weather and Flight Information Kajal Claypool Kelly Moran y MIT Lincoln Laboratory 1 This work was sponsored by the Federal Aviation Administration under Air Force Contract No. FA8721-05-C-0002. Opinions, interpretations, KC conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.

Interactions between FAA Facilities and Airlines for Newark Congestion Problems Evans, J. Ducot, E., “Corridor Integrated Weather System, Lincoln Laboratory Journal, Volume 16, Number 1, 2006 2 KC

Next Generation Air Transportation System Operational Concept 3 KC

Semantic Interoperability Framework Mediation Transition Semantic Interoperability Eurocontrol Semantic Interoperability Framework must be able to support Semantic Interoperability Framework must be able to support F Framework k Native access Semantic Interoperability Framework • Mediation for systems that will never switch over for Weather Dissemination • Transition of legacy systems to net-centric systems T iti f l t t t t i t • New systems Web-based Cockpit Weather Decision Displays Support Tools Tools 4 KC

Outline Background • Ontology Engineering (Kajal) • NNEW Weather Ontology – Flight Object Ontology – Ontology Alignment (Kelly) • Ontology Alignment – Semantic Discovery in NextGen Network Enabled Semantic Discovery in NextGen Network Enabled – Weather (NNEW) Summary • 5 KC

NNEW Ontology Development Methodology – “Green” Engineering Ontology-level method: Cost • Q Quadrant 4 d t 4 Quadrant 1 Q d t 1 – Spiral development Specification Focus Area Evaluation methodology Specification: Define the Specification: Define the – – Start of Start of round 1 domain and scope of the ontology Review Integration & test End of plan round 1 validate e Plan Next Phase Prototype Implementation Quadrant 3 Quadrant 2 6 KC

NNEW Ontology Development Methodology Ontology-level method: Cost • Q Quadrant 4 d t 4 Quadrant 1 Q d t 1 Focus Area Evaluation: – Specification Focus Area Evaluation Segment the overall domain and scope of ontology into smaller focus gy Start of Start of areas. Prioritize the focus round 1 area. Review Integration & test End of plan round 1 validate e Plan Next Phase Prototype Implementation Quadrant 3 Quadrant 2 7 KC

NNEW Ontology Development Methodology Prototype implementation: Cost • Q Quadrant 4 d t 4 Quadrant 1 Q d t 1 Conceptualize : Enumerate – Specification Focus Area Evaluation important concepts Reuse: Identify reuse Reuse: Identify reuse – – Start of Start of round 1 opportunities at upper/mid/low ontologies for Review straight reuse or as starting point point Integration & test End of Implement: Define the plan – round 1 validate classes, class hierarchy, and properties for the and properties for the e concept Plan Next Phase Prototype Implementation Quadrant 3 Quadrant 2 Validate: Validate the – ontology focus area ontology focus area 8 KC

Design Principles Design principles: • Expressive representation Expressive representation – Model concepts with hierarchies and relationships, not with flat term concatenation Internal concept reuse p – Reusing concepts within an ontology ensures consistency and reduces ambiguity Consistent scoping – C Converge on a common granularity for each sub-domain l it f h b d i 9 KC

NNEW Weather Ontology 1. General weather concepts OWL Wordnet (in OWL form) / SUMO 2. Aviation specific weather JPL SWEET concepts derived from general weather ontology Weather/Oceanography Ontology Aviation specific Ontology Aviation-specific Ontology Eurocontrol FAA Extensions AFWA Extensions Extensions 3. FAA specific weather concepts derived from aviation Layered Approach to Ontology Design y gy g concepts concepts Legend: Legend: subClassOf Constrained Concepts 10 KC

Example: Wind Ontology Legend SWEET 2.0 JMBL derived WordNet derived Weather Ontology 11 KC

Flight Information Ontology: Flight Information Ontology: Data Dictionary to Ontology 12 KC

Flight Information & Modeling Process Data Dictionary Data Dictionary Data Model Data Model XML Schema XML Schema Automated Manual FullMoon + extensions FullMoon + extensions Time consuming Time consuming Key Issue: • DD - human readable not machine readable 13 KC

Ontology: Capturing Knowledge Data Dictionary Ontology (Web App) (OWL) FO Data Dictionary FO Data Dictionary XML Schema XML Schema D t Data Model M d l (MS Word format) Human in the loop Machine readable: Semi-automate generation of data model • Machine process-able: • Can be reasoned over – Can support mediation for transition systems Can support mediation for transition systems – – Searchable/indexable • Basis of capturing agreement, and of applying knowledge • 14 KC

An Ontology Embedded in Word Template ! Datatype property: hasKeyword Concept [range: string] Concept label Axiom: Inverse properties Axiom: Equivalent class Object property: hasSource Object property: Object property: A Annotation: dc:description t ti d d i ti hasAlteringEvent Object property: hasPart [range: string] Object property: createdBy Datatype property: hasDataUsage Object property: hasContributor [range: string] [range: string] Object property: hasAudience Object property: measurement.owl#hasUnit Datatype property: hasFormat [range: string] Instance data Datatype property: Datatype property: hasMaturity [range: string] h M t it [ t i ] hasAccrualMethod [range: string] Object property: hasAccess Datatype property: hasAccuralPeriodicity [range: Datatype property: string] hasDisposition [range: string] Datatype property: isMandatory Datatype property: isMandatory Obj Object property: requires t t i [range: boolean] Annotation: references (custom) Axiom: Inverse properties Datatype property: Annotation: rdf:comment hasDataTransaction [range: string] g] Annotation: dc:creator Annotation: dc:creator Annotation: dc:date [type:date] Annotation: dc:versionInfo 15 KC Concept Object property Datatype property Axiom Annotation Instance Data

Ontology Example Text Ontology 16 KC

Outline Background • Semantic Interoperability Framework • NNEW Weather Ontology – Ontology/Vocabulary Alignment – Semantic Discovery in NextGen Network Enabled – W Weather (NNEW) th (NNEW) Summary • 17 KC

Interoperability Challenges Department of Defense Vocabulary National Weather Service Vocabulary (Joint METOC Broker Language – JMBL) (Climate and Forecast) aerosol_angstrom_exponent temperatureAdiabaticLapseRate temperatureAir age_of_stratospheric_air temperatureAirDifferenceStandard air density air_density temperatureAirError temperatureAirErrorEstimate temperatureAirError temperatureAirErrorEstimate air_potential_temperature temperatureAirIncrement temperatureAirMean air_temperature air_temperature temperatureAir temperatureAir air_pressure temperatureAnomaly temperatureAntenna air_pressure_anomaly temperatureBoundary temperatureBrightness air_pressure_at_cloud_base temperatureBrightnessCorrected air_pressure_at_cloud_top temperatureBrightnessCount air pressure at convective cloud base air_pressure_at_convective_cloud_base temperatureBrightnessOccurrence temperatureBrightnessOccurrence air_pressure_at_convective_cloud_top temperatureBrightnessStandardDeviation air_pressure_at_freezing_level temperatureDewpoint air_pressure_at_sea_level temperatureDewpointDepression air_temperature temperatureDewpointDepressionCoefficient air_temperature_anomaly temperatureDewpointDepressionErrorEstimate air temperature at cloud top air_temperature_at_cloud_top temperatureDewpointDepressionIncrement temperatureDewpointDepressionIncrement atmosphere_ atmosphere_ atmosphere atmosphere air_temperature_lapse_rate temperatureDewpointDepressionMinimum air_temperature_threshold temperatureDewpointMaximum altimeter_range temperatureDewpointMaximumMean absolute_ absolute_ altimeter_range_correction_due_to_dry_troposphere temperatureDewpointMaximumStandardDeviation altimeter_range_correction_due_to_ionosphere temperatureDewpointMean vorticity vorticity ti it ti it vorticityAbsolute vorticityAbsolute ti it Ab ti it Ab l t l t altimeter_range_correction_due_to_wet_troposphere lti t ti d t t t h temperatureDewpointMinimum t t D i tMi i altitude temperatureDewpointMinimumMean altitude_at_top_of_dry_convection temperatureDewpointMinimumStandardDeviation angle_of_emergence temperatureDewpointStandardDeviation angle_of_incidence 1046 temperatureDifference temperatureEarthSkin 1270 angle_of_rotation_from_east_to_x temperatureFrequency temperatureGradient angle_of_rotation_from_east_to_y temperatureHeatIndex angstrom_exponent_of_ambient_aerosol_in_air temperatureInfraredStandardDeviation 18 KC