HarmoniRiB – a database design for
uncertain multi-disciplinary data in
support of the WFD
Roger V. Moore
Centre for Ecology and Hydrology
U.K.
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Points to address
 Achievements
 Major current challenges
 Achievements in the near future
 Outstanding issues requiring research
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Achievements
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Background
 HarmoniRiB is about uncertainty
 Why is uncertainty important?
– Water Framework Directive
– Major spending decisions
– Knowledge of uncertainty can influence decisions
• Iraq
• Sewage works construction
• ‘Good ecological status’
– Important to future users of data
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Problem

Problems in the operational use of uncertainty information in decision making:
–
Field programmes don’t record uncertainty
–
Few operational tools for assessing uncertainty
–
Most database systems have no mechanism for storing uncertainty
–
Models:
–
•
Do not take in uncertainty information
•
Rarely output uncertainty information
Operational decision making has no means of taking account of uncertainty
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Project objectives
 To establish a methodology and tools for:
– assessing and describing uncertainty in data and model output
– developing river basin management plans using uncertain data
 To test the methodologies with case studies and illustrate how
uncertainty in data and models may affect the river basin
management planning
establish data sets (including uncertainty
estimates) for eight river basins with representative examples of
 To
the problems faced by water managers
develop and populate a database system that can
handle uncertain data
 To
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Topics
 Data
 Database design
– Overview
– Recording uncertainty in data
 Issues
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Data requirement
 Driven by WFD:
– Equitable & sustainable
allocation of water
resources
– ‘Good ecological status’
 Catchments, rivers, lakes,
groundwater, coastal and
transitional waters
– Meteorology
– Quantity
– Quality
– Ecology
– Land use
 WFD requires:
– Programmes of measures
– River basin management
plans
– Pressures
• Point and diffuse
discharges
• Abstractions
– Socio-economic
– System characteristics
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Meteorological data
 Precipitation




Temperature
Solar radiation
Relative humidity
Wind speed
Minimum for
estimating
evaporation
 Wind direction
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Rivers and lakes - water level
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Rivers and lakes – water quality &
ecology
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Groundwater
Hydra evaporation sensor
Tower
Automatic weather station
Solar radiation
Wind direction
Wind speed
Net radiation
Rain gauge
Temperature
and humidity
Bore Hole
Plastic sheet
Net rainfall gauges
Soil water suction samples
Tipping bucket recorder
Neutron probe
Puncture tensiometers at
10cm intervals to 1m
4m access tubes
9 m access tube
Equitensiometer to
10m at 1m intervals
Deep tensiometer
30 - 50 m access tube
(experimental)
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Pressures – discharges and
abstractions
Coastal and transitional waters
- water quality
Time series of images
Flight paths
Time
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Coastal and transitional waters
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Database design
– Objective
• Facilitate integrated water management
– Facilitate understanding of process interactions
• Remove walls between data from different
disciplines
– Record uncertainty
Climate
€
Reservoir
Flow
Ecology
Fishing
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Tourism
A generic approach to storage
 All data stored as the values
of attributes describing or
associated with objects
Object
 All data are assumed to
change over time
 No distinction made between
spatial and non-spatial
attributes
Attribute
 Uncertainty can be recorded
for every value
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Data Model
What?
Flow
24/2/05 14:50
5.05
When?
Where?
Site 01
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Storage of time series data
28.7
36.5
31.2
25.3
12.4
20.3
19.4
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
where?
Site
01
BOD
What is in a cell?
14.50
GMT
what?
when
?
•Value
• Qualifier
• Method
• Validation status
• Uncertainty
• Owner/dataset
Object
ID
Attribute
ID
Date Time
Site
01
Flow
24/02/05
Replicate
ID
Value
5.05
Qualifier
Validation
Status
Uncertainty
Method
ID
Data
resource
ID
Uncertainty model
Uncertainty model
Identity
Applicability
Describes the sources of
uncertainty in a given
measurement scenario,
how they should be
recorded and the
effectivness of the model.
Sources of uncertainty
(1 … n)
Method of recording
(1 of … )
Quantitative
Quantitative
PDF
Goodness of model
Scenario
ACF
1
.
0
0
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Quantitative model
Uncertainty recorded as a PDF
PDF = Normal
Mean = 
SD = σ
?
1
.
0
0
?
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Data Uncertainty Engine


Characterisation and assessment of uncertainty in data
Propagation of data uncertainty through models

Free download from
www.harmonirib.com
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
24
Major current challenges
 Most people do not think generically
– Find it difficult to map their data onto objects and attributes
 Merging similar data sets from across Europe
– Views of the world are different
– Terminologies are different
 Populating and achieving agreement on standard
terminologies
 Making ontologies comprehensible
 Setting up uncertainty models
 Determining uncertainty at the individual value level
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Achievements in the near
future
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Populating the
HarmoniRiB database
River basin network
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Merging databases
 Bring together the databases for the following FP5 & 6
projects:
– HarmoniRiB
– TempQSim
– AquaStress
– …….
 And possibly:
– Scenes
– ……
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Further work on database
design
 AquaStress
 OpenMI-LIFE – linking to models to databases
 Scenes
 Environmental Observatories
– CUAHSI
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Outstanding issues requiring
research
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Outstanding issues
requiring research




Practical ways of capturing uncertainty at the moment of observation
Practical ways of deducing uncertainty in historic data
Improved methods of describing uncertainty
Efficient methods of storing uncertainty
 Building standard European terminologies where agreement can be
achieved
 Effective tools for building cross reference systems where agreement
not possible
 Automating metadata capture
 Time and time based queries
 Efficient storage and indexing of temporal data
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Questions?
HarmoniRiB Web site address:
www.HarmoniRiB.com
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
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RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
River Kennet
 Kennet is largest tributary of the Thames
 Groundwater used for public supply
– Local area
– Blending with water from other sources (high nitrate)
– Supplying Swindon: major town outside catchment
 Kennet is also
– A Trout fishery
– A Site of Special Scientific Interest (parts are also cSAC)
– Extensively modified
• Canal
• Weirs / sluices
• Land drainage
 Ongoing debate as to the impacts of various
pressures on the ecosystem
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Objective
 To understand the effects of uncertainty on:
– the assessment of pressures on river ecology
due to the demand for water resources
– the subsequent selection of management
strategies.
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Risk based approach to
screening
Results of screening assessment using low
resolution data
Achieves
good status -
“At risk” of failing to
achieve good status
Not “At Risk” of failing to
achieve good status
Type I error.
OK, no action required other
than monitoring
(Good or High)
Reality Does not
OK, action required:
achieve good monitoring, develop
status programme of
(Moderate,
measures
Type II error.
Poor or Bad)
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Deliverables
User interface
Tools – eg graphs
Input data
The OpenMI
interface standard
Database
User interface
Output data
Input data
Rainfall Runoff
Guidelines
User interface
Output data
Input data
Configuration tools –
eg model linking
River
User interface
Output data
Input data
Economy
Output data
Utilities - eg Smart wrapper
Tourism
Flow
Ecology
Fish
Reservoir
Groundwater
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
€
Uncertainty in spatial data
?
?
PDF = Normal
Mean = 
SD = σ
Variogram
Nugget=
Sill=
Range=
System characteristics – terrain
model and river network
Outlet
HarmonIT
•To build a model linking mechanism for:
• run time data exchange between models, databases & tools
•In order to:
• improve ability to model complex scenarios
Climate change
Evaporation
Precipitation
Reservoir yield
Ecology
Ecolo
gy
Flow
Planning
Floods
Ecology
Evaporation
Surface runoff
Coast
Estuary
Groundwater
Droughts
?
Aquifer yield
•HarmoniRiB will test linking to databases
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
•Water quality
Prerequisites for linking
Evaporation
 To be linkable a model must:
Precipitation
Rainfall
runoff model
─ expose modelled quantities
Surface runoff
─ have time-step controlled computation
How ?
─ be structured in the way its initialization
is separated from obtaining boundary conditions
Evaporation
River
─ submit to run-time control
Coast
Estuary
Hydraulic model
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Typical model architecture
Application
User interface + engine
Engine
Simulates a process – flow in a channel
Accepts input
Provides output
Model
An engine set up to represent a particular location e.g.
a reach of the Thames
Model application
User interface
Write
Input data
Run
Read
Engine
Write
Output data
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
OpenMI
Engine converted to an engine component
User interface
Engine component provides and accepts data through an
interface
Input data
OpenMI defines a standard interface
If an engine component has the standard interface, it becomes
Engine
OpenMI compliant and is called a Linkable Component
Output data
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
The OpenMI interface
Interface
functions:
1. Descriptive

To provide an Exchange Model to allow other Linkable
Components to find out what items this model can
exchange :
Engine

•
Quantities
(What)
•
Element sets
(Where)
To define what will be exchanged
2. Run time

To enable the model to request and receive data at run
time
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Exposing modelled quantities
Database
Accepts
Provides
Rainfall
(mm)
Water level
(m)
Flow
(m3/s)
…
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Linking modelled quantities
Database
Rainfall runoff
model
Accepts
Provides
Accepts
Provides
Rainfall
(mm)
Temperature
(Deg C)
Runoff
(m3/s)
Water level
(m)
Rainfall
(mm)
Flow
(m3/s)
…
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Linking elements
Rainfall data
Rainfall runoff
Model
Elements are the
locations where
quantities are
calculated or
stored
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006
Linking at run time
User interface
User interface
Input data
Input data
Database
GetValues(..)
Rainfall runoff
Output data
Quantity
Output data
Link
Date/time
RDF, Ontologies and Metadata Workshop - Edinburgh – 9th June, 2006