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The MMI Device Ontology: Enabling Sensor Integration
1. The MMI Device Ontology:
Enabling Sensor Integration
Carlos Rueda1, Nancy Galbraith2, Robert A. Morris3,
Luis E. Bermudez4, Robert A. Arko5, John Graybeal6,
1 Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA
2 Woods Hole Oceanographic Institution, Woods Hole, MA, USA
3 Department of Computer Science, University of Massachusetts at Boston, Boston, MA, USA
4 Open Geospatial Consortium, Herndon, VA, USA
5 Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA
6 California Institute for Telecommunications and Information Technology, University of
California San Diego, La Jolla, CA, USA
MMI Device Ontology Working Group
Marine Metadata Interoperability Project
American Geophysical Union Fall Meeting 2010
1
Dec 16, 2010 – Session: IN44B-08
2. • Mission
–To promote the exchange, integration and use of
marine data through enhanced data publishing,
discovery, documentation and accessibility
The MMI Device Ontology: Enabling Sensor Integration - AGU Fall Meeting 2010 Session: IN44B-08 2
3. • Main Projects
– Website: Resources
& References
– Metadata Guides
– Ontology Registry and Repository (ORR)
– Ontology Development
– OOSTethys Demo
The MMI Device Ontology: Enabling Sensor Integration - AGU Fall Meeting 2010 Session: IN44B-08 3
5. Motivation
• Lack of a proper device characterization
• Lack of common/extensible vocabulary
• Difficulty to find device related information
–Functionality
–Measured variables
–Instrument composability
–Deployments
• Uncoordinated sensor data management
approaches
The MMI Device Ontology: Enabling Sensor Integration - AGU Fall Meeting 2010 Session: IN44B-08 5
6. Main Goals
• Develop an extensible ontology of marine
devices
• Integrate with models for sensor descriptions
• Provide provenance metadata for
oceanographic observations
• Help users and software agents discover
sensors and sensor data of interest
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8. Logistics
• Organic Group at the MMI Drupal site
– http://marinemetadata.org/devont
– Agendas/minutes/reports/guidance/comments/references
• Regular telecons
• Mailing list
• Task tracker
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9. Technologies and Tools
• W3C Web Ontology Language (OWL)
• Ontology Editors and Visualizers
• MMI Ontology Registry and Repository (ORR):
–publication
–versioning
–resolvability
–mappings
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10. Methodology
• Use case driven
• Facets-to-ontology process
• Validation / Enrichment
–Instantiations
–Reasoner tools
–Coordination with similar efforts
(eg., W3C Sensor Network Incubator Group)
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11. Use cases / Competency Questions
1. Get data information from sensor identification
2. Compare two data sets to get information about
observed variables over time
3. Find multibeam devices that can sense measurand
in earthRealm
4. Find devices with environmental tolerance
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12. Device Facets
The MMI Device Ontology: Enabling Sensor Integration - AGU Fall Meeting 2010 Session: IN44B-08 12
13. Facets-to-Ontology Process
• Pick entry from list of facets and identify:
–key entities (look at nouns)
–key relationships (look at verbs)
• For an identified entity:
–Definition; examples; atomic value or class?
–significant relationships
• For an identified relationship:
–kind (data type; object type; cardinality)
Propose change -> Task tracker -> Review -> Update -> Repeat
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15. Core class hierarchy Component
• Component: Base class (physical unit) System
hasComponent
• System: A Component that can be a
composite of multiple (sub)components Process Platform
• Process: A System that has inputs
and outputs Device
• Platform: A System of Processes
and/or Platforms Sensor Sampler
• Device: a physical Process
• Sensor: a device that measures a physical phenomenon, converting it
into a digital representation that can be output to other components
• Sampler: Device that obtains a physical piece or subset of an observed
feature
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16. The MMI Device Ontology: Enabling Sensor Integration - AGU Fall Meeting 2010 Session: IN44B-08 16
17. Measurement Capability
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20. Composition and Deployments
• CTD: Composition of
–Conductivity sensor
–Temperature sensor
–Depth sensor
• Deployment aspects
–Device canBeDeployedOn Platform [0..*]
–Device hasDeployment Deployment
–Deployment hasDeployedSystem System [0..*]
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21. A Particular CTD model
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22. Multibeam Ontology
• Describe multibeam mapping sonars for U.S.
academic research vessels
• Small number of complex systems (10 vessels)
• Joint development with NSF-funded Rolling Deck
to Repository (R2R) program
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27. Lessons Learned
• Process is important
• “The best is the enemy of the good”
– comprehensiveness is difficult
• A single authoritative device type vocabulary?
More feasible/practical:
–Base conceptual model
–Community coordination
–Mappings
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28. Recommendations
for similar ontology efforts
• A process with appropriate level of formality
• Visual representation highly useful
• Have semantic experts and actual users
• Continuous testing is important
• Less is more:
do not pretend to be overly comprehensive
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29. Next Steps
• Better separation of concerns
–Intrinsic aspects
–Data management aspects
• Further harmonization and integration with
–MMI Platform Ontology
–SWEET
–SensorML and related profiles (eg., SID), OGC
• User-friendly editors for device descriptions
• End-to-end demonstrations
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30. The MMI Device Ontology:
Enabling Sensor Integration
More contributors are welcome; help us move the work forward!
Thank you!
http://marinemetadata.org/devont
Carlos Rueda – carueda@mbari.org
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