How Earth Science can contribute to and benefit from the Spatial Information Infrastructure

1
How Earth Science can contribute to and benefit
from the Spatial Information Infrastructure

• Andrew Woolf1 (a.woolf_at_rl.ac.uk) and Stefano
  Nativi2 (nativi_at_imaa.cnr.it)
• 1STFC Rutherford Appleton Laboratory
• 2Univ. Florence and CNR-IMAA

2
Outline

• The Earth Science SII synergy
• SII requirements for Earth Science
• Earth Science benefits from SII

3
Earth Science SII synergy
4
Environmental informatics
an emerging field centering around the
development of standards and protocols, both
technical and institutional, for sharing and
integrating environmental data and
information Biosphere Data Project, UC Berkeley
Research and system development focusing on the
environmental sciences relating to the creation,
collection, storage, processing, modelling,
interpretation, display and dissemination of data
and information UK Natural Environment Research
Council

• American Geophysical Union
• Earth and Space Sciences Informatics (ESSI) Focus
  Group (http//essi.agu.org)
• European Geosciences Union
• ESSI Division proposal (http//wikihost.org/wikis/
  eguessi)

5
Advanced earth sciences computing e.g. EU Grid
projects
CYberinfrastructure for CiviL protection
Operative ProcedureS (http//www.cyclops-project.e
u)
Dissemination and Exploitation of GRids in Earth
sciencE (http//www.eu-degree.eu)
C3-Grid Collaborative Climate Community Data and
Processing Grid (http//www.c3grid.de)
Natural Environment Research Council DataGrid
(http//ndg.nerc.ac.uk)
6
Grid-SII architectures

• Many of these grid projects adopt a similar
  information architecture to SII
• Irreversible trend from data-centric to
  service-oriented

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Earth Science SII synergy
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Earth Science SII synergy

• Environmental policymaking is key driver for
  Spatial Information Infrastructures
• air quality
• climate change
• water
• energy
• risk zones
• ...

(earth-sciences)
9
GEOSS an earth science SII

• Global Earth Observation System of Systems
• GEO membership 58 countries EC
• purpose is to achieve comprehensive, coordinated
  and sustained observations of the Earth system
• e.g. for decision support in nine societal
  benefit areas

The success of GEOSS will depend on data and
information providers accepting and implementing
a set of interoperability arrangements, including
technical specifications for collecting,
processing, storing, and disseminating shared
data, metadata, and products. GEOSS 10-Year
Implementation Plan
10
SII requirements for Earth Sciences
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Information modelling

• ISO TC211 model-driven approach
• But traditional approach is file-centric

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e.g. Geosciences GeoSciML
slides courtesy Simon Cox
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e.g. Climate Sciences CSML
ltProfileFeature gmlid"WOCE_SO3_AR9404_4
9.temperature"gt ltlocationgt-64.622
160.738 lt/locationgt
lttimegt1995-01-15T111300lt/timegt
ltvaluegt ltProfileCoverage
gmlid"WOCE_SO3_AR9404_49.temperature.data"gt
ltprofileDomaingt
ltCSMLMultiPoint srsName"urnndgcrspressure"gt
ltpositiongt2.0 4.0 6.0 8.0
...lt/positiongt
lt/CSMLMultiPointgt
lt/profileDomaingt
ltgmlrangeSetgt
ltgmlValueArraygt
ltgmlvalueComponentgt
ltgmlQuantityList uom"ndguomdegC"gt-1.7210
-1.7260 -1.7320 -1.7350 ...lt/gmlQuantityListgt
lt/gmlvalueComponentgt
lt/gmlValueArraygt
lt/gmlrangeSetgt lt/ProfileCoveragegt
lt/valuegt ltparameter
xlinkhref"ndgphenomenatemperature"/gt
lt/ProfileFeaturegt
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Observations

• Within earth sciences, the processes of
  observation and measurement are paramount
• measurement of temperature in ocean with an
  eXpendable BathyThermograph (XBT)
• observation of radiance of Earths surface by
  satellite radiometer
• simulation of pressure in atmosphere by a
  computational numerical weather prediction model

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An emerging Observations and Measurements model

• OGC document 05-087r4, on ISO track

An Observation is an Event whose result is an
estimate of the value of some Property of the
Feature-of-interest, obtained using a specified
Procedure
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The temporal dimension

• Most Earth Science data is dynamic in nature, on
  a wide spectrum of timescales
• rapid gravity-waves
• geological timescales
• Discovery Use Cases (see INSPIRE Draft Metadata
  IR)
• find winter rainfall
• find weather forecast valid 3 days from now
• find data on Tertiary minerals

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Coverage data

• ISO 19123 coverage
• feature that acts as a function to return values
  from its range for any direct position within its
  spatial, temporal or spatiotemporal domain
• Most Earth Science information regarded as a
  field over some region of space and/or time
  (rather than discrete spatial object with
  attributes)
• cf. Observations and Measurements model
• result of Observation is coverage-valued
  property of the feature-of-interest

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SII benefits for Earth Sciences
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Use Case On-demand risk monitoring
SII
Daily analysed rainfall data
Hydrological flood-risk model
DEM data
soil moisture etc...
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Use Case Scientific validation of model against
in-situ data
SII
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Role of repositories

• Inheritance enhances re-use

Organisation A
Organisation B
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Role of repositories

• Operations
• enable advanced workflows

implements
uses
instanceOf
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Advanced geo-processing workflow

• Possible now
• semantics repositories (ISO 19110)
• semantic service annotation (OWL-S)
• Future
• data?service matchmaking
• automated service composition
• Information modelling and semantics
• Ontology Definition Metamodel (ODM)
• UML (e.g. ISO 19109 General Feature Model)
• OWL

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Integrating effect of SII standards

• Various Earth Science domains are developing
  SII-like infrastructure
• earth observation (e.g. ESA SSE)
• climate science (e.g. LAS, OPeNDAP)
• biodiversity (e.g. OBIS)
• These all will benefit from re-engineering
  around SII standards
• service/dataset catalogues with standard metadata
• standards-based data modelling
• standard service interfaces

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Conclusions
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Conclusions

• There is a significant synergy between the Earth
  Sciences and SII
• integrated, global, multi-disciplinary
• Earth Sciences offer several particular benefits
  to hardening SII
• observations, coverages, time
• The Earth Sciences have a lot to gain from the
  SII
• service/data discovery, advanced scientific
  workflows