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Enhancing Marine Industry Risk
Management Through Semantic
Reconciliation of Underwater IoT Data
Streams
14th
September, 2...
Port of Leixões, Porto
© University of Southampton IT Innovation Centre 2016
Environmental impact Periodic maintenance
License compliance Accidents and extreme events
Risk management
Maintaining know...
Decision
Maker
Surveyor Analyst
Information
Service Provider
Marine
Information
Ecosystem
Risk Management
Environment Data...
Hazard map for marine navigation channel based
on sediment transport analysis
Hazard Maps
© University of Southampton IT I...
Underwater Internet of
Things
© University of Southampton IT Innovation Centre 2016
Periodic maintenance
Modem
Sensors
Son...
testbeds
Concept and Objectives
• Turn environmental and sensor data (including
Underwater IoT streams) into knowledge
– provide su...
01/16 01/17
time
Survey Data
Simulation Data
Hazard Maps
Fused Data
Today Planned
Survey
Planned
Survey
Maintaining situat...
• Portal to query, resample, aggregate and
process data
o Import/Export binary files (e.g. GTIFF)
o Metadata management an...
EXPOSURES Architecture
© University of Southampton IT Innovation Centre 2016
 
Semantic Reconciliation 1/2
• netCDF is a self describing data format for Earth
observations (physical quantities)
• provi...
NetCDF data model (EO data)
SST = f(time, latitude, longitude)
© University of Southampton IT Innovation Centre 2016
• NetCDF organises the data storage
– small but well defined vocabulary to define metadata
– function based interpretation...
Semantic Reconciliation 2/2
• We adopted the netCDF data model
• Metadata encoding into RDF and disseminated as
Linked Dat...
Linked Data Dissemination
• Rationale
– existing standards (OGC WCS) allow data
interoperability but do not promote discov...
Application Trial
• Trial at Porto harbour explored a new data value
chain for the marine industry
– routine evaluation of...
Trial Results
© University of Southampton IT Innovation Centre 2016
Simulation Risk Map – Open TelemacObservation Risk Map...
Summary
• EXPOSURES is a service platform supporting semantic alignment, geo-
spatial fusion and linked-data access to und...
Contacts & Questions
Michael Boniface, Gianluca Correndo,
Simon Crowle, Juri Papay
University of Southampton
IT Innovation...
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Gianluca Correndo, Simon Crowle, Juri Papay and Michael Boniface | Enhancing marine industry risk management through semantic reconciliation of underwater IoT data streams

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Gianluca Correndo, Simon Crowle, Juri Papay and Michael Boniface | Enhancing marine industry risk management through semantic reconciliation of underwater IoT data streams

  1. 1. Enhancing Marine Industry Risk Management Through Semantic Reconciliation of Underwater IoT Data Streams 14th September, 2016 Correndo G., Crowle S., Papay J., Boniface M. [gc,sgc,jp,mjb]@it-innovation.soton.ac.uk] 12th International Conference on Semantic Systems, Leipzig University Professor Michael Boniface © University of Southampton IT Innovation Centre 2016
  2. 2. Port of Leixões, Porto © University of Southampton IT Innovation Centre 2016
  3. 3. Environmental impact Periodic maintenance License compliance Accidents and extreme events Risk management Maintaining knowledge about the interplay between humans and ecological processes is an essential for risk management © University of Southampton IT Innovation Centre 2016
  4. 4. Decision Maker Surveyor Analyst Information Service Provider Marine Information Ecosystem Risk Management Environment Data Acquisition Risk Analysis Data Search, Aggregation, Fusion Information Ecosystem © University of Southampton IT Innovation Centre 2016
  5. 5. Hazard map for marine navigation channel based on sediment transport analysis Hazard Maps © University of Southampton IT Innovation Centre 2016
  6. 6. Underwater Internet of Things © University of Southampton IT Innovation Centre 2016 Periodic maintenance Modem Sensors Sonar Camera
  7. 7. testbeds
  8. 8. Concept and Objectives • Turn environmental and sensor data (including Underwater IoT streams) into knowledge – provide support for data discovery, integration, fusion, presentation to communities and commercial teams – use explicit semantics and discoverable linked data – align with OGC Standards, tools, and Array DBs supports data fusion and visualisation © University of Southampton IT Innovation Centre 2016
  9. 9. 01/16 01/17 time Survey Data Simulation Data Hazard Maps Fused Data Today Planned Survey Planned Survey Maintaining situational awareness © University of Southampton IT Innovation Centre 2016
  10. 10. • Portal to query, resample, aggregate and process data o Import/Export binary files (e.g. GTIFF) o Metadata management and semantic reconciliation (e.g. NASA SWEET) o Map layer dissemination (e.g. OGC WMS) o Fusion of experimental data from AUVs with third party data sets • Linked Data interface for access to data on the web o Discoverability and semantic querying of the metadata assets o Available in RDF/XML and Turtle • Integration with SUNRISE GATE for UAV data collection EXPOSURES Capabilities © University of Southampton IT Innovation Centre 2016
  11. 11. EXPOSURES Architecture © University of Southampton IT Innovation Centre 2016  
  12. 12. Semantic Reconciliation 1/2 • netCDF is a self describing data format for Earth observations (physical quantities) • provides a data model to describe what’s inside • sets of array data • File’s are only a small piece of information in a wider context • same for every OGC WCS compliant server • Need to reconstruct the link between the single dataset and the wider context • management of metadata is key in exploiting data assets (retrieval, sharing, reconiliation) © University of Southampton IT Innovation Centre 2016
  13. 13. NetCDF data model (EO data) SST = f(time, latitude, longitude) © University of Southampton IT Innovation Centre 2016
  14. 14. • NetCDF organises the data storage – small but well defined vocabulary to define metadata – function based interpretation of datasets • Attributes, dimensions, and variables are strings – makes it difficult to reconcile such representation with external data sets – limited support for federation of data providers – limited support for semantic interoperability NetCDF data model © University of Southampton IT Innovation Centre 2016
  15. 15. Semantic Reconciliation 2/2 • We adopted the netCDF data model • Metadata encoding into RDF and disseminated as Linked Data • Alignment towards a comprehensive domain ontology • NASA SWEET (earth and environmental terminology) • Exploitation of ontology alignments to support data discovery and retrieval © University of Southampton IT Innovation Centre 2016
  16. 16. Linked Data Dissemination • Rationale – existing standards (OGC WCS) allow data interoperability but do not promote discoverability or semantic interoperability • Once semantically aligned the meta data can be made part of a bigger data ecosystem • i.e. Linked Data cloud • Necessary for a broad range of marine and environment applications © University of Southampton IT Innovation Centre 2016
  17. 17. Application Trial • Trial at Porto harbour explored a new data value chain for the marine industry – routine evaluation of the current state of the seabed – surveyors with UAVs collect seabed bathymetry, water current velocities, and spectral data for water turbidity • Data ingested into EXPOSURES – create coherent, rasterized plane of environmental values (such as seabed height or water temperature) – highly clustered data points sparsely distributed over AOI – interpolation and clipping functions applied to deal with missing and extraneous data points • Multiple surveys in areas of interest ingested and fused to produce for a more complete view • Discovery and visualisation of aggregated data accessible via Linked Data – visualizations of accretion/deletion of the seabed sediment profile – Geospatial temporal data queries • Fusion functions prepare data sets for simulation – predict ecological processes, impacts and what if analysis – reduce data preparation time © University of Southampton IT Innovation Centre 2016
  18. 18. Trial Results © University of Southampton IT Innovation Centre 2016 Simulation Risk Map – Open TelemacObservation Risk Map – QGIS)
  19. 19. Summary • EXPOSURES is a service platform supporting semantic alignment, geo- spatial fusion and linked-data access to underwater IoT data • Cost and complexity of developing marine applications is reduced – harmonization of temporal and spatial resolution (resampling and interpolation), array based data composition – data reconciliation of environmental properties – map layer visualization • OGC and W3C linked data interfaces allow knowledge of marine environments to be curated, published and shared by communities and commercial teams • Future work aims to extend the services to support a wider range of geo- spatial fusion capabilities – automating semantic annotations of simulation input data within analytical workflows – exploring commercial business models for marine information services © University of Southampton IT Innovation Centre 2016
  20. 20. Contacts & Questions Michael Boniface, Gianluca Correndo, Simon Crowle, Juri Papay University of Southampton IT Innovation Centre [mjb, gc, sgc, jp]@it-innovation.soton.ac.uk This research has been supported by the SUNRISE project under the FP7 framework, agreement number 611449. © University of Southampton IT Innovation Centre 2016

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