MODELLING WATER SECURITY FROM A RISK AND POLLUTION PERPECTIVE:
BUSINESS CASE AND STATEMENT OF END-USER NEEDS
Document compiled by Defra, Environment Agency, Water Industry and NERC following a
meeting held in March 2012
1. BACKGROUND
The need for integration of models has never been stronger with moves in Government to
integrate policies on different pollutants (see Natural Environment White Paper), and a
Government agenda to increase transparency in decision making. In parallel, the water industry is
increasingly adopting catchment approaches as part of integrated water cycle management to
simultaneously optimise water resources, enhance water quality, manage wastewater and increase
water security and resilience. The White House seeks similar advances in modelling, public
communication and transparency1 and this is being advanced in the US water/environment arena
by the EarthCube2 initiative and KESS (food security/soils). Such modelling is being
internationalised at an early stage through the activities of the Belmont Forum and less formal
UK, US and Australia links. The pilot Environmental Virtual Observatory is strongly engaged
with this international activity.
Many government and industry organisations use models and quantitative tools to inform
operational decisions, and the development and implementation of policy at local, regional and
national scales. Models provide a synthesis of scientific knowledge and the increasing volumes of
data provided by advanced monitoring technologies. NERC programmes produce excellent
research but are often focused on generating high quality science delivery, to meet essential
NERC research priorities rather than translating this into tools that can be directly used by
stakeholders to address policy and management issues. In order to address this issue, the
Macronutrients Directorate in Oxford organised a one day meeting with representatives from
DEFRA, Environment Agency, National River Trust, British Water, Thames Water, Welsh
Government, Scottish Government, Natural England, UKWIR, Water Consultancy Community,
SEPA, the Environmental Sustainability KTN, NERC Water KE Programme and NERC Science
Management (Appendix 1). The meeting was organised to discuss the actions necessary to
develop a more robust and less fragmented modelling resource to provide a ‘user interface’ for
knowledge emerging from research. This would aim to provide a vehicle to accelerate knowledge
transfer from researchers working on fundamental environmental processes to the users of that
knowledge.
This document is a follow up from that meeting and proposes priorities for the development of
tools, models and meta-models that stakeholders can use directly for policy and environmental
management.
2. SCOPE
This document covers models representing macronutrient losses to the environment and their
subsequent impacts on ecology, people and ecosystem services, including:
 Water quality and impacts of surface and groundwater pollution:
o Nutrients and sediment in water and impacts on ecology
o Faecal indicator organisms/ pathogens and their fate
1
http://www.whitehouse.gov/sites/default/files/omb/egov/digital-government/digitalgovernment.html?goback=.gde_3427896_member_120023144
2
http://www.nsf.gov/pubs/2011/nsf11065/nsf11065.jsp?org=NSF

Air quality and its impacts:
o Ammonia emissions from agriculture
 Greenhouse gas emissions from agriculture and land use:
o Nitrous Oxide
o Methane
(See appendix 3 for further details)
It aims to collate the collective requirements of stakeholders, including:
 Policy makers (Defra, Scottish Government, Welsh Government),
 Regulators (e.g. Environment Agency, OFWAT)
 Operational staff involved in land management or catchment management including:
o government agencies (e.g. Environment Agency, Natural England)
o NGOs involved in delivering advice to land managers (e.g. Rivers Trusts)
o Commercial consultants
o Water industry (eg UKWIR, Water UK, British Water and individual WSCs)
o Agricultural industry
It aims to set out an approach to better integrate the UK modelling resource and provide a forum
to promote exchange between the developers and users of environmental models. This will create
a vehicle to turn research outputs into tools, models and meta-models that stakeholders can use
directly for policy formulation and delivery, and environmental management.
Demonstrating tangible economic or societal benefits from its research investments is of
considerable importance to NERC. Realising this by operationalizing outcomes of research
programmes such as Macronutrient Cycles3, Environmental Virtual Observatory4, Biodiversity &
Ecosystem Service Sustainability5, serves not only to inform public policy and regulation but
enhances business performance and practice, with consequent benefits for both UK plc and the
environment.
3. STAKEHOLDER MODEL NEEDS
Stakeholders have many needs for models at local, regional, national and global scales, as follows:
1. Modelling to 'scale-up' research from small scale (e.g. sub-catchment) research:
Model and meta-model approaches and process based tools (incorporating appropriate
uncertainty frameworks), to improve capacity to understand the likely effectiveness of
policy over:
a. Spatial scales: To interpolate observations at the field/ sub-catchment scale to (1)
catchment and (2) national scales. This would use data gathered in research and
monitoring programmes to provide evidence on the probable effectiveness of
measures in delivering reductions in multiple pollutants at different scales local,
regional and National)
b. Temporal scales: (1) To improve the resolution of our predictive capability and
understanding of short-term, event-driven fluxes in emissions to water and air and
their contribution to annual and longer term total flux. (2) To provide an
3
http://www.nerc.ac.uk/research/programmes/macronutrient/
http://www.evo-uk.org/
5
http://www.nerc-bess.net/
6
http://macronutrient-cycles.ouce.ox.ac.uk/
4
indication on the likely timescales that improvements in water and air quality and
could reasonably be expected to be delivered.
c. Climate variability: To provide capability to understand the performance of
catchments under a range of climate conditions: eg periods of drought or excess
rainfall. This is key to ensuring catchment management decisions are robust to
future climate change.
d. Interactions and trade-offs: between multiple pollutants, and between
environmental impacts and agricultural production.
e. Mitigation/ Adaptation measures: Disaggregate the cost-effectiveness of
individual measures from measurements at the outlets of catchments where
multiple measures have been applied, building on conceptual modelling underway
through DTC.
f. Source apportionment: Modelling to diagnose the probable contributions of
different sources or nutrient pollution over the spatial and temporal scales and to
predict the effectiveness of source controls across catchments.
g. Ecosystem Services: models are required that can quantify ecosystem services so
that sustaining ecosystem services can be incorporated into policy on a sound
basis.
Approaches should build on our existing modelling capacity e.g. using ensemble
approaches to combine multiple models.
2. Communicating modelling capabilities and outputs:
a. Better cataloguing of model metadata (including details of the primary purpose of
the model, known limitations and caveats for use) to help decision makers select
the right tool for the job.
b. Development of decision support/synthesis tools to translate complex multi-model
output into information which is targeted to key stakeholder groups (operational
staff, policy makers, farmers etc.)
c. Investigate ways of developing modelling approaches that integrate numerical data
with alternative ‘soft’ information sources including local knowledge etc. This
includes investigating ways to improve the way in which users interact with
models.
3. Improve our confidence in predictions through testing and parameterisation of
models: using data-sets collected in the DERA, EA and NERC programmes to:
a. Parameterise and run models,
b. Improve process understanding and feedback mechanisms in models, (see
appendix 3 for the EA requirements for process based models)
c. Ground-truth and test the modelling resource at our disposal, setting realistic
confidence intervals on our estimates.
d. Utilise new techniques in uncertainty analysis, making use of cloud computing to
enhance this area of knowledge.
e. Make use of ensemble based approaches to identify which process representations
work best at specified scales, and/or for certain catchment, soil or climatic
typologies, and from this
f. To construct simple meta-models suitable for locations with limited data
availability.
Analysis of the discrepancy between models and outputs should challenge our conceptual
models of catchment function, and improve both our understanding and model
representations over time. A risk based evidence approach should be encouraged, using the
distribution of multiple model outputs as a basis of decision making.
Appendix 2 -4 give an overall summary of the user needs from DEFRA, the EA and
the Water Industry
Figure 1: A Proposed Modelling Strategy to meet the needs of Stakeholders. A proposed
modelling framework would address the central layer in the diagram above: allowing
combinations of existing models to be run on common datasets to underpin decision support tools
which would be developed separately.
4. PROPOSED ACTIONS
From an end-user’s perspective, there is an acute need to facilitate the application of existing
models and improve the coherency of the UK capability in macronutrient environmental
modelling. Activities are proposed to develop an integrated framework in five areas: (1) to
engender closer collaboration between modellers, (2) to improve collaboration and knowledge
exchange between modellers and users of models, (3) to develop technical solutions to link
models together to address complex questions involving interactions between multiple pollutants
over multiple spatial scales (4) identify the key policy issues facing government in the area of
nutrient pollutants over the next 5 years, and (5) to provide improved water industry tools to
understand both operational and strategic risk in water resource management.
1. Develop a forum to improve collaboration between modellers and to bring together endusers and developers of models. This could follow the model established by the Water
Industry Forum Ltd which brings together for discussions, in an informal business setting,
several contiguous located major water companies with their tier 1 and 2 framework
contractors and regulators. The contractors learn the vision of regulators which drive the
specification of the work required for the companies. It encourages (up to a point) shared
good practice, cooperative contracting, increased opportunity and improved delivery (see:
http://www.waterindustryforum.com/ ). Currently, intellectual property provides a barrier
to model use and model integration. We propose developing a culture where models are no
longer seen as commodities, rather the skills to use them are. This is in line with the new
markets for data approach taken by Defra’s open data initiative. Activities will focus on:
a. Agreeing ways of working amongst modellers:
i. Develop common mechanisms to link models together
ii. Agree ways of overcoming IPR barriers that currently hamper model
application
iii. Encourage open source model code where possible or encourage model
sharing, so code development and model linkage can be enhanced by a
wider community
iv. Developing common approaches for quality assuring emerging models
b. Improve communication between the users and developers of models:
i. Identify ways to make existing models and their outputs more useful and
responsive to the needs users (DEFRA, EA, Water and Farming industry)–
removing barriers to their operational use.
ii. Provide opportunities for EA staff to contribute model developments for
integrated catchment management and for policy analysis on behalf of
DEFRA. These staff need to have the time to get to use the models and
make sure that they deliver models suitable outputs and that these are used
appropriately. This could include training for core staff in the EA to use and
apply key models and the development of formal training programmes for
operational staff.
iii. Agree protocols for the evaluations of model performance and acceptability
criteria
iv. Agreeing which combinations of models should be applied for particular
uses
v. Identify key priorities for new work
c. Improve coordination between end-users to
i. Share models and other resources
ii. Coordinate investment in new models
2. Establish a technical solution to integrate models through a modelling framework (see
figure 1 and appendix 2). This needs to be co-owned and co-developed by the community
of modellers and model users established in 1, above. The priority is to explore options
for linking models and modellers to address a broader range of questions using metamodel techniques.
3. Identify the key policy issues that government will face over the next 5 years in the area of
water [and air?] pollution, for example based on the recommendations of the European
Nitrogen Assessment6. These can then provide a focus for integrated modelling activities
so that the correct and appropriate tools are in place to answer the questions. These will
also provide the necessary data and scenario analysis for evidence based policy decisions.
4. Identify the key issues that relate to the water industry that need addressing (see Appendix
4)
5. NEXT STEPS
1. Explore options to incorporate the above recommendations in the scope of potential future
NERC investments such as the Environmental Virtual Observatory (EVO) and emerging
soil health research programme and the Open Data Initiative (see appendix 5).
2. The NERC Water Security Knowledge Exchange Programme (http://www.wskep.net/)
should be approached with the request to host a working forum that will:
6
http://www.nine-esf.org/ENA
Constitute a Special Interest Group of Government policy leads, regulators,
water industry, NERC Research Programme leads, and NERC Knowledge
Exchange Fellows
ii. Develop a narrative between stakeholders leading to an agreed set of key
priorities, stakeholder interoperability, terms of reference, and pathway to
product delivery
iii. Establish working groups between the research community and end-users,
and manage these partnerships to sustain the engagement and ensure
completion of each group’s assigned task
iv.
The WSKEP to develop a communications programme to update the core
stakeholders on progress, articulate and highlight the aims and activities of
the SIG to a broader audience, and solicit input or expertise as required
3. Explore opportunities to link to other on-going NERC activities (Macronutrient Cycles
(MC), Changing Water Cycles (CWC), Environmental Virtual Observatory (EVO),
Biodiversity and Ecosystem Service Sustainability (BESS))
4. Explore co-funding opportunities for the above activities from the end-users identified.
i.
6 GANTT CHART
Here are a set of tasks that the modelling gaps initiative may address over a 4 year period.
Tasks of USER/MODELLERS Project
Create Users/Modellers Forum
Regular Meetings of the Forum
Identify 6 key policy issues
Identify key modelling tools required
Source these tools from existing models
Deveop new models if required
Create linkages between the key models
Address each policy issue using model tool kit
Deveop scenarios and uncertainty analysis
Outline a strategy for each policy
Produce a summary report for each policy
Write key papers on models, uncertainty
Train Key Staff
year 1
year 2
year 3
Year 4
APPENDIX 1: List of contributors:
Document compiled by:
NERC:
Paul Whitehead (Director, NERC Macronutrient Cycles programme)
Adrian Macdonald (Environmental Virtual Observatory)
Murray Gardner
Environment Agency:
Robert Willows
Defra:
Dan McGonigle
Luke Spadavecchia
UKWIR:
Hans Jensen
Workshop attendees:
Environment Agency
SEPA
Defra
Welsh Government
Natural England
The Rivers Trusts
Water industry
LWEC
NERC
Knowledge Transfer Networks
Jim Wharfe
Louise Webb
Robert Willows
Mark Hallard
Dan McGonigle
Luke Spadavecchia
James Skates
Russ Money
Alistair Maltby
Michelle Walker
Peter Daldorph (Atkins, representing UKWIR/Industry)
Jonathan Westlake (Thames Water)
Ian Bernard (British Water)
Dan Osborn
Chris Franklin
Murray Gardner
Paul Whitehead (Macronutrient Cycles programme Director)
Jill Crossman (Macronutrient Cycles programme secretariat)
Neil Runnalls (Water Security KE Programme)
Kerry Thomas (Environmental Sustainability KTN)
APPENDIX 2: DEFRA Priorities for developing a water quality modelling framework
1. Rationale
Existing water quality and air quality models (numerical representations of processes) tend to
focus on individual pollutants at specific spatial scales. They have often suffered from a lack
of testing against data, due to a scarcity of observational data. Furthermore our current
modelling resource is somewhat atomised, with access limited by institutional boundaries.
Where models are shared, version control may be an issue, but also the lack of common
datasets to parameterise and run them means that results are often difficult to evaluate.
Government, agencies and industry would benefit from better access to the existing UK
numerical modelling resource (models and capability) for macronutrients. This would entail
the following:
1. Testing models against data to assess which models should be used and where.
2. Bringing together existing and emerging models and running them on common datasets through a coherent, open source framework. This would allow ensemble
approaches in assessing interactions between pollutants, effects over increasing spatial
and temporal scales and predicting nutrient losses to water and air in different
scenarios.
3. Developing tailored decision-support software for end-users (e.g. Environment
Agency, water companies etc).
Several large scale research initiatives have emerged or are currently emerging which are
developing high resolution datasets that could be used to support the first two of these
activities. These include the NERC Macronutrient Cycles programme, the Greenhouse Gas
Research Platform, the Demonstration Test Catchments, CEH catchment studies, National
Ecosystem assessment and others.
Developing such an integrated modelling resource would provide a user interface for
knowledge emerging from basic research funded by research councils. If an open-source
framework could be developed, it would provide a vehicle to accelerate knowledge transfer
from researchers working on fundamental environmental processes to the users of that
knowledge.
2. Key principles:
A modelling framework should:



Embrace open-source development and code-sharing to increase transparency and
scrutiny of underlying assumptions
o To allow researchers to use models and add to them as appropriate through
iterative developments, and
o To allow wider scrutiny by the research community.
o To allow end user organisations to add to them and develop bespoke decision
support front-ends
Build on existing models and systems of integration where available (e.g. NERC pilot
Environmental Virtual Observatory, developments in cloud computing, ‘models as
web services’ approaches, etc)
Take account of the wider data-sharing agenda (e.g.

Have a web-enabled user interface/interfaces to allow free access. This would
increase access and understanding of existing models and how they work
3. Previous work to inform model integration
Several pieces of work have made recommendations that support this proposed approach:




Defra
Scientific
Advisory
Council
Modelling
Sub
Group
report
(http://sac.defra.gov.uk/sub-groups/modelling-sub-group/)
Defra project IF0111: Setting the priorities for future work on nutrient decision
support
systems
(http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=Non
e&Completed=0&ProjectID=14515)
Defra project ES0204: Agricultural decision support tools for prediction and
management
of
nutrient
input
and
loss:
NIL
IMPACT
http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=Non
e&ProjectID=13492&FromSearch=Y&Publisher=1&SearchText=es0204&SortString
=ProjectCode&SortOrder=Asc&Paging=10#Description
Defra Demonstration Test Catchments Modelling Strategy
APPENDIX 3 Priorities for Environment Agency--Catchment Modelling Requirements
Broad objectives
The main aim is to develop a modelling system that



will allow the impact of farming and other land uses on a range of environmental and
policy relevant endpoints to be assessed (eg chemical and ecological quality measures,
ecosystem service benefits.
enjoys academic, DEFRA support
will have the confidence of key stakeholders.
It will need to

quantify the multiple impacts of farming at a range of scales
o eg this particular farm or local area contributes this amount of harm or benefit to
this local river or this area of catchment.

quantify the benefits of policies and land management practices to reduce those impacts
o eg this type of farm or practice contributes this amount of harm or benefit to
our rivers when integrated across whole one or more RBD or England.

harm to be assessed in a variety of ways eg exposure represented as a distribution of
concentrations (eg seasonally), in terms of load exported by a particular pathway (instream, bed load, groundwater flow) integrated over periods (days, seasons, years)

quantify the contribution farming makes to these impacts in comparison to other sources
eg point sources

make use of the best available science and data, including National datasets (incl remote
sensing, farm census, distributed monitoring), data from research case studies.

exploit or develop existing model formulations where possible

incorporate local observations where this can improve model prediction

allow extrapolation of knowledge to data poor catchments, and allow upscaliing and
integration

allow risks to a range statutory duties (eg WFD) and developing policy objectives

provide a basis for evidence based policy analysis, evaluation to achieve multiple
objectives

provide a basis for spatially explicit targeting of measures on the basis of the evidence.
Measures to include advice, incentives, regulation, etc
In order to do this the model will need to be able to simulate the movement of 3-4 principal
sediment fractions, and associated substances though a spatially distributed, dynamic,
process-based, hydrological model.
Substances to include principal chemical forms of N, P, org C, FIO’s.
Model to allow other substances (eg pharmaceuticals, metals) to be represented through
generic properties and processes (e.g. conservative, first/second order decay, volatalisation,
daughter substances, partitioning, to/from bed and suspended sediment, org fraction, etc.)
To allow the contribution from principal sectors to
 the mass of substances in defined compartments (soil water, river reach or reaches
(water, sediment fraction x, or in combination), groundwater aquifer, fine sediment)
 the mass flux between compartments over time,
 the time-variation (distribution, time series) in concentration at a point or averaged
over a spatial unit.
Source inventory
To include a spatially and temporally explicit representation of the present-day loading of
each substance, or methods to do so.
Using data that is or can be made available to the DEFRA family.
Principal sectors and subsectors to be defined in such away as to allow management actions
and policy options to be explored
Eg Water company discharges : size, type,
Eg Farming : Arable: Crop rotation x, y, z)
(Note the above applies to source inputs that can in principle be controlled spatially. Other
sources to be considered will include natural and non-natural land uses, incl. types of urban,
density of households or population, forestry, atmospheric deposition).
Where there is evidence of significant within year (eg seasonal) variation in source loadings,
then this variation in input should be adequately described.
To explicitly document the evidence and main sources underpinning each process description
and parameterisations, including uncertainties on parameter estimates
Processes
Incorporates important processes affecting transport, exchange, transformation through a
catchment.
1) Model(s) to be partially or fully spatially distributed
2) To run on a continuous (daily or sub-daily) temporal resolution
3) Suitable for the simulation of catchment hydrological response to variations in rainfall
and temperature (stationary and non-stationary time series generated from appropriate
meteorological data).
4) To explicitly (but simply) represent spatial variation in surface and groundwater
hydrological pathways
5) Surface water pathway should consider including the influence of surface vegetation,
surface storage, infiltration, overland flow, through flow, percolation to groundwater
6) Hence the model should demonstrate acceptable level of skill representing both high
and low flow components of hydrographs
7) Integrated simulation of hydrological and geochemical processes affecting, in
particular, nutrients (N, P), FIO’s, org C)
8) Software should be modular and open source and/or use commercially available
software (eg GIS, database)
9) For ecological impacts, should provide flexibility such that a broad variety of
empirical relationships (models) between exposure and probable impact on receptors
can be incorporated.
Hydrological features
To be considered
Weather generation
Rainfall
Solar radiation
Temperature
Interception
Surface depression storage
Infiltration
Evapotranspiration
Aquifer Recharge
Lateral flowthrough
Channel flow
Sediment erosion, re-suspension and deposition (or at least prediction of in channel sediment
characteristics and volumes)
Solute travel time (reach residence time) (eg aggregated dead zone (flow dependent) or
empirical canonical)
Geochemical features
Nitrogen cycle
Ammonification
Nitrification
De-nitrification
Plant uptake and release (decay)
Terrstrial - Wetlands, grasslands (various) broad leaf/coniferous, moorlands,
agricultural crops?)
Aquatic – suspended algae
Epiphytic algae
Submerged macrophytes
Marginal vegetation
Oxygen
In channel (in stream) DO balance and BOD
Surface O2 exchange (eg Oxygen entrainment and aeration due to channel features
(weirs, etc)
Phosphorus
Partitioning between dissolved and suspended particle, soil and particle/sediment bound
phases, Chemical trasformations in dissolved and particulate phases, influence of sediment
type and redox?), Plant uptake and release (decay) (see above)
General pollutants
Conservative or first order decay, Coefficient based partitioning based on general properties
APPENDIX 4 Priorities for Water Industry--Catchment Modelling Requirements
The water industry, as represented by UKWIR, jointly with the Environment Agency, has just
developed and delivered a fully functional integrated framework of models to apportion loads
and concentrations of chemicals to WFD water bodies at different spatial and temporal scales.
See UKWIR report Chemical Source Apportionment under the WFD, ref.12/WW/02/3, and is
a contribution to "Previous Work to Inform Model Integration". However, the draft
statement of needs includes functionality which is not present or not well developed in the
UKWIR-EA model. In particular, in-river fate and storage processes which could be
important (especially for BOD, ammonia, DO and steroids). In addition, the statement notes,
correctly, that a different model is needed if event-based water quality impacts are the key
concern, e.g. intermittent discharges from sewer overflows and storm tanks or the release of
pathogens, principally FIOs. In these cases, shorter time step modelling than the monthly
intervals set in the UKWIR-EA model would be required.
UKWIR supports the (WFD) principles of control of pollution at source, the use of
catchment-type solutions and application of the polluter pays principle. We believe it is
necessary, therefore, to quantify pollution loads from point and diffuse inputs to a river
catchment and to assess the water quality benefits (in terms of chemistry and ecology) that
would arise from a range of individual and in-combination pollution control measures on
both point and diffuse sources.
A common and agreed integrated catchment modelling approach offers a number of benefits
to the industry, including: direct support to the development of River Basin Management
Plans, achieving the greatest benefit from point source control solutions, defending against
abortive investment and unnecessary increases in carbon footprint, chemical usage and waste
production. The full benefits of a catchment modelling approach will only be achieved by
linking water industry asset management strategies, natural catchment characteristics and the
potential benefits of controls on other sources of pollution across a catchment. The approach
should evaluate the environmental and water industry co-benefits of alternative, staged
solutions based on multi stakeholder measures. Specifically, who should invest and, for the
water industry, where, when and how sewage treatment should be improved and potable
water sources protected.
Generic asset management strategies and local, catchment-specific asset management options
to be tested would include: temporal changes in the operation of wastewater processes
matched to river capacity (i.e. real time control); changes in the allocation of treatment effort
spatially between different treatment works in a catchment (catchment based control);
consolidation of assets (centralisation); dispersion of assets (transfer of flows between STW,
relocating discharge points, multiple discharge points for larger STW) and reducing
abstractions/increasing reservoir compensation flows.
APPENDIX 5 OPEN DATA INSTITUTE
The business plan for the government’s Open Data Institute has revealed ambitions to support
and commission research, collaborative R&D, and knowledge transfer. The institute, which
will open its doors in East London in September, was announced by Chancellor George
Osborne last November. Initially, the centre, to be co-directed by world wide web creator Tim
Berners-Lee and his University of Southampton colleague Nigel Shadbolt, will support and
mentor start-ups designed to make the most of open data. But plans for the institute published
on 22 May show that while business incubation and innovation will be the core activities,
research and development will also be on the agenda. The institute will commission
university researchers to take part in four 24-month projects to “address any urgent
requirements to further develop techniques, methods and understanding in a critical area of
Open Data delivery”. The plan says programmes would have a value of £759,500. The centre
would also support externally commissioned collaborative R&D worth £696,563. There are
plans for four such projects in the centre’s first five years. “These projects would be carried
out in collaboration with private or public sector organisations; they would contribute funding
from their side to approximately double the effort. These projects would tend to focus on key
Open Data capabilities that companies themselves wanted to extend or further develop for
deployment,” reads the document. Another goal cited in the plans is to support knowledgetransfer projects in which research associates would be placed in organisations to “effect
knowledge transfer around the tools, techniques and methods of Open Data”. Each of these
placements says the plan, would be around 12 months and have a value of £845,950.