Content-Infused OGC Web Services Enabling Dynamic Quality Assessment in Observing Systems Janet J. Fredericks Applied Ocean Physics & Engineering Woods Hole Oceanographic Ins=tu=on Carlos Rueda Monterey Bay Aquarium Research Ins=tute Workshop on Sensor Web Enablement 2011 (SWE 2011) As part of The 2011 Cybera Summit on Data For All Opening up the Cloud October 67, 2011, Banff, AB, Canada 1
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Content-Infused OGC Web Services Enabling Dynamic Quality Assessment in Observing Systems
Presentation by Janet Fredericks during the Sensor Web Ontology and Semantics paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).
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Content-Infused OGC Web Services
Enabling Dynamic Quality Assessment in Observing Systems
Workshop on Sensor Web Enablement 2011 (SWE 2011) As part of The 2011 Cybera Summit on Data For All -‐ Opening up the Cloud October 6-‐7, 2011, Banff, AB, Canada
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Research and survey data served with
associated metadata in a few speci5ic formats with
associated software installations
Sensor Manufacturers <html/> and manuals
NOAA/NDBC provides 24/7 QC;
Feeds National IOOS backbone;
NOAA/NODC provides national archival for valued
data sets (they can determine the value)
NSF/OOI; NSF/R2R; NSF/BCODMO provides community-‐based integration with tools and QC, along with discovery
and mapping opportunities
Real-‐time Rapid Response integration can be accomplished quickly and reliably by communicating metadata
in standards-‐based systems
Modeling using translation tools from the cloud, modelers have access to a broader
source of information
ANYONE By fully describing data, sensors and
processing with associated provenance, data can be discovered and explored for
any program
Data Provider Nightmare!
User-‐based Output 2
Research and survey data served with
associated metadata in a few speci5ic formats with
associated software installations
Sensor Manufacturers <html/> and manuals
NOAA/NDBC provides 24/7 QC;
Feeds National IOOS backbone;
Data Provider (and Consumer)
Nightmare!
User-‐based Output
Research and survey data served with
associated metadata in a few speci5ic formats with
associated software installations
Research and survey data served with
associated metadata in a few speci5ic formats with
associated software installations
IOOS
GEOSS
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Research and survey data served with
associated metadata in a few speci5ic formats with
associated software installations
Sensor Manufacturers <html/> and manuals
NOAA/NDBC provides 24/7 QC;
Feeds National IOOS backbone;
NOAA/NODC provides national archival for valued
data sets (they can determine the value)
NSF/OOI; NSF/R2R; NSF/BCODMO provides community-‐based integration with tools and QC, along with discovery
and mapping opportunities
Real-‐time Rapid Response integration can be accomplished quickly and reliably by communicating metadata
in standards-‐based systems
Modeling using translation tools from the cloud, modelers have access to a broader
source of information
ANYONE By fully describing data, sensors and
processing with associated provenance, data can be discovered and explored for
Original Equipment Manufacturer (OEM) File Descrip=on of Sensor Model
Configura=on/Ownership/Deployment (CONDEP)File Descrip=on of Sensor Configura=on, Deployment and
Event History Details
Observable Proper=es
SML system
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How does this model enable dynamic quality assessment? 1) ROLES -‐ Provides a template for instrument manufacturers/data managers/
marine operators to describe details that describe quality related informa=on in a standards-‐based encoding
2) CONNECTIONS -‐ Through the connec=ons list in SensorML, the QC flags can be associated with the QC tests with associated parameters
3) ENABLING SEMANTIC MAPPINGS -‐ Through inclusion of associated URLs encoded with each term, ontologies and mappings can be built to define rela=onships across poli=cal and research domains promo=ng interoperability and interdisciplinary research for all geospa=al, sensor-‐based observa=ons.
4) Encoding thorough descrip=ons of processing and process lineage promotes beker understanding of the observa=ons, which enhances the value and reliability of the data.
The original provider has no knowledge of how the data may be used! We need to communicate enough informa=on to enable assessment for a par=cular use beyond the project design! Did they sample fast enough for the new applica=on? Or long enough? Is the repor=ng frequency adequate?
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Next Steps • Build beker SensorML editors and registries -‐-‐ making things easier and promo=ng fully-‐described sensor and processing lineage. This will promote adop<on of the use of standards and more fully-‐described systems!
• Encourage manufactures, data managers and domain experts to create meaningful vocabularies including authorita=ve references to processing algorithms, with figures, equa=ons, etc. and to register the vocabularies, providing resolvable links in a standards-‐based encoding (OWL)
• Provide tools and opportuni=es for domain experts to create and register ontologies, associa=ng terms in RDF (Is ThisQCtest the same as ThatQCtest? Does this QC flag have th same meaning as thatQCflag)
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Conclusions • Structured Q2O (hkp://q2o.whoi.edu) SensorML serves as a
model for any sensor-‐based, in situ observa=ons; each component can be implemented by the responsible party and adop=on of the model can happen in stages.
• By associa=ng QC flags with qc tests, processing methods with observa=ons, and fully-‐describing how observable proper=es become observa=ons knowledge about quality will be shared.
• By referencing (encoding) resolvable terms, ontologies can be built and registered to foster interoperability across-‐domains and poli=cal boundaries.
The ability to dynamically assess data quality will provide a