SlideShare a Scribd company logo
Geospatial Data Curation & interoperability
in the COBWEB project –
citizen science & crowdsourcing for
environmental policy
Didier G. Leibovici & Mike Jackson
University of Nottingham (COBWEB partner)
didier.leibovici@nottingham.ac.uk
Chris Higgins
COBWEB Project Coordinator
chris.higgins@ed.ac.uk
European projects: Citizen Observatories
Community-based & crowdsourcing
www.citizen-obs.eu/
These 'citizens' observatories' will include community-based environmental monitoring,
data collection, interpretation and information delivery systems. This will require the
development of highly innovative monitoring technologies, like low-cost micro sensors
that can be embedded in smartphones. Citizens shall then be able to collect
environmental data on a range of parameters, automatically transmit this data to suitable
data repositories and exchange their knowledge and experience within a Citizens'
Observatory framework which enables citizenship co-participation in community
decision making and cooperative planning
environmental exposure
air quality, noise
health
water management
floods and drought
species distribution, flooding and
land cover and use
environmental governance
seawater colour, transparency and fluorescence
management of the coastal zone
water quality
odour perception, discomfort and nuisance
ambient odour exposures
Essential context – WNBR
• UNESCO Man and Biosphere Programmes
World Network of Biosphere Reserves (WNBR)
– Sites of excellence to foster harmonious integration
of people and nature for sustainable development
through participation, knowledge sharing, poverty
reduction and human well-being improvements,
cultural values and society's ability to cope with
change, thus contributing to the Millennium
Development Goals
• 610 reserves in 117 countries
COBWEB Biosphere Reserves
• Germany: Wadden See and Hallig Islands
• Greece: Mount Olympus & Gorge of Samaria
• Left open possibility of expansion to further
European and non-European BR’s
UK (Wales): Biosffer Dyfi
– Development work
concentrated here
FP7 COBWEB project: pilot case studies
6
EO enhancement:
content (linked data), accuracy
(bidirectional)
Contribute to: land cover,
habitat, biodiversity
Data existing:
optical, radar ,LiDAR, … plant
ontologies?
Citizen Observations:
vegetation (species,
communities, etc.) biophysical
(moisture, greenness,
phenological state)
Biological monitoring:
content (linked data), accuracy
(bidirectional), timely and
updated information
Contribute to: environmental
policy, habitat
Data existing:
RSPB, linked to EO derived
data,
Citizen Observations:
Species and habitat related
information (fauna, flora)
Flooding:
timely information, finer scale,
Calibrating flood models
(hydraulic and erosion),
Validation of flood extents and
water pathways
Contribute to: environmental
policy, warning systems
(hazards and risks)
Data existing:
Historical data, floodplains,
flood risk maps, weather data,
Network of sensors
Citizen Observations:
Time tagged photo (flood limits,
colour [sediment transport])
mobile data capture & Quality Assurance / Conflation
Key components of the COBWEB architecture
• Portal software & Survey Authoring tool
survey management & for mobile app building
• Quality Assurance & Conflation
QA workflow authoring tool, WPS
• Multi-source Retrieval
Middleware Service for Sensors (SIXTH /SWE and GeoPkg)
• Access control and privacy
single sign on, federation
• Co-design projects
– Biological monitoring
– Flooding
– Validation of Earth Observation products
Data life cycle
Generic SDI-QA-Fusion-Decision
QAQC service:
-enriches the data collected
with quality metrics, update
them as new data comes in
-feedbacks on existing data
with quality metrics
-qualifies users with quality
metrics by direct assessments
or profiling
conflation service:
-retrieves relevant
information
-compares and re-use
informed quality of data
-combines the information to
achieve better quality
meta-quality decision service:
-compares policy
requirement and achieved
data quality
-elaborates new data
collection requirements
-estimates the potential
impact of current data quality
in the policy decision-making
.Workflow authoring tool
BPMN encoding
.ontology support
SKOS encoding
.running WPS or app
The QA workflow
is composed of more than
one QC
into a workflow
that may loop back /feedback
to the user or to other users
etc.
to get additional information.
(confirmatory / ensemble /
linked data )
Interoperability example
QAQC with authoring tool and WPS calls
QAwAT
QAwOnt
QAwWPS
A flooding data
capture QA
workflow
Qualifying the observations, the
users and the authoritative data
Quality elements
Obs /Auth - ISO19157 standard
Auth - GeoViQUA-feedback
model
User -COBWEB-Stakeholder
Quality Model
QAQC: the COBWEB QAQC / 7 pillars
Meek, S Jackson, M Leibovici, DG (2014) )
A flexible framework for assessing the quality of crowdsourced data
.AGILE conference, 3-6 June 2014, Castellón, Spain
COBWEB RDA Plenery 5  - Joint meeting of IG Geospatial & IG Big Data - Didier Leibovici & Mike Jackson
Quality elements created concerning the
Observation the User and the Authoritative
data
Interactivity with the user (messages)
Similar QC in different pillars for different quality elements
Modifications and accumulations of quality
elements throughout the QA workflow

More Related Content

COBWEB RDA Plenery 5 - Joint meeting of IG Geospatial & IG Big Data - Didier Leibovici & Mike Jackson

  • 1. Geospatial Data Curation & interoperability in the COBWEB project – citizen science & crowdsourcing for environmental policy Didier G. Leibovici & Mike Jackson University of Nottingham (COBWEB partner) didier.leibovici@nottingham.ac.uk Chris Higgins COBWEB Project Coordinator chris.higgins@ed.ac.uk European projects: Citizen Observatories
  • 3. www.citizen-obs.eu/ These 'citizens' observatories' will include community-based environmental monitoring, data collection, interpretation and information delivery systems. This will require the development of highly innovative monitoring technologies, like low-cost micro sensors that can be embedded in smartphones. Citizens shall then be able to collect environmental data on a range of parameters, automatically transmit this data to suitable data repositories and exchange their knowledge and experience within a Citizens' Observatory framework which enables citizenship co-participation in community decision making and cooperative planning environmental exposure air quality, noise health water management floods and drought species distribution, flooding and land cover and use environmental governance seawater colour, transparency and fluorescence management of the coastal zone water quality odour perception, discomfort and nuisance ambient odour exposures
  • 4. Essential context – WNBR • UNESCO Man and Biosphere Programmes World Network of Biosphere Reserves (WNBR) – Sites of excellence to foster harmonious integration of people and nature for sustainable development through participation, knowledge sharing, poverty reduction and human well-being improvements, cultural values and society's ability to cope with change, thus contributing to the Millennium Development Goals • 610 reserves in 117 countries
  • 5. COBWEB Biosphere Reserves • Germany: Wadden See and Hallig Islands • Greece: Mount Olympus & Gorge of Samaria • Left open possibility of expansion to further European and non-European BR’s UK (Wales): Biosffer Dyfi – Development work concentrated here
  • 6. FP7 COBWEB project: pilot case studies 6 EO enhancement: content (linked data), accuracy (bidirectional) Contribute to: land cover, habitat, biodiversity Data existing: optical, radar ,LiDAR, … plant ontologies? Citizen Observations: vegetation (species, communities, etc.) biophysical (moisture, greenness, phenological state) Biological monitoring: content (linked data), accuracy (bidirectional), timely and updated information Contribute to: environmental policy, habitat Data existing: RSPB, linked to EO derived data, Citizen Observations: Species and habitat related information (fauna, flora) Flooding: timely information, finer scale, Calibrating flood models (hydraulic and erosion), Validation of flood extents and water pathways Contribute to: environmental policy, warning systems (hazards and risks) Data existing: Historical data, floodplains, flood risk maps, weather data, Network of sensors Citizen Observations: Time tagged photo (flood limits, colour [sediment transport])
  • 7. mobile data capture & Quality Assurance / Conflation
  • 8. Key components of the COBWEB architecture • Portal software & Survey Authoring tool survey management & for mobile app building • Quality Assurance & Conflation QA workflow authoring tool, WPS • Multi-source Retrieval Middleware Service for Sensors (SIXTH /SWE and GeoPkg) • Access control and privacy single sign on, federation • Co-design projects – Biological monitoring – Flooding – Validation of Earth Observation products
  • 9. Data life cycle Generic SDI-QA-Fusion-Decision QAQC service: -enriches the data collected with quality metrics, update them as new data comes in -feedbacks on existing data with quality metrics -qualifies users with quality metrics by direct assessments or profiling conflation service: -retrieves relevant information -compares and re-use informed quality of data -combines the information to achieve better quality meta-quality decision service: -compares policy requirement and achieved data quality -elaborates new data collection requirements -estimates the potential impact of current data quality in the policy decision-making
  • 10. .Workflow authoring tool BPMN encoding .ontology support SKOS encoding .running WPS or app The QA workflow is composed of more than one QC into a workflow that may loop back /feedback to the user or to other users etc. to get additional information. (confirmatory / ensemble / linked data ) Interoperability example QAQC with authoring tool and WPS calls QAwAT QAwOnt QAwWPS
  • 11. A flooding data capture QA workflow Qualifying the observations, the users and the authoritative data Quality elements Obs /Auth - ISO19157 standard Auth - GeoViQUA-feedback model User -COBWEB-Stakeholder Quality Model
  • 12. QAQC: the COBWEB QAQC / 7 pillars Meek, S Jackson, M Leibovici, DG (2014) ) A flexible framework for assessing the quality of crowdsourced data .AGILE conference, 3-6 June 2014, Castellón, Spain
  • 14. Quality elements created concerning the Observation the User and the Authoritative data Interactivity with the user (messages)
  • 15. Similar QC in different pillars for different quality elements
  • 16. Modifications and accumulations of quality elements throughout the QA workflow