1. society
2. crime

Cover Sheet for Proposals
(All sections must be completed)
Name of Strand:
Geospatial
Name of Lead Institution:
Name of Proposed Project:
University of Leeds
Exploiting geo-spatial datasets to enhance crime analysis and
related research methods
University of Huddersfield
Name(s) of Project Partners(s)
(except commercial sector – see below)
This project involves one or more
Name(s) of any commercial partner company (ies)
commercial sector partners
YES / NO (delete as appropriate)
Full Contact Details for Primary Contact:
Name:
Nick Malleson
Position: Research Fellow
Email:
[email protected]
Tel:
0113 343 6757
Fax:
Address: School of Geography
University of Leeds
Leeds, LS2 9JT
Length of Project:
Project Start Date:
1st February 2011
Project End
Date:
30th Sept 2011
£62,763.82
Total Funding Requested from JISC:
Funding requested from JISC broken down across Financial Years (Aug-July)
Aug10 – July11
Aug11 – July12
£42,409.21
Total Institutional Contributions:
£20,354.61
£11,075.97
Outline Project Description
Crime analysts and researchers in related fields could benefit substantially by using existing
geospatial data (e.g. Open Street Map, LandMap and Ordnance Survey MasterMap) but rarely make
use of these datasets at present; defaulting instead to aggregate-level data in their analyses. This is due
largely to the technical expertise required to obtain the data and analyse them spatially using complex
geographical routines. Therefore, this research will make use of existing geospatial data sets and
perform analyses to create new, high-resolution national data with additional variables that will be
extremely useful for social scientists and crime analysts / environmental criminologists in particular.
I have looked at the example FOI form at Appendix K
and included an FOI form in this bid
I have read the Funding Call and associated Terms
and Conditions of Grant at Appendix L
YES (delete as appropriate)
YES (delete as appropriate)
1 Appropriateness and Fit to Programme Objectives and Overall Value to the JISC Community 1.1 Introduction 1. In recent years, a plethora of large data sets covering transport, demographics, land use and the environment
have been made available to UK researchers and this is due, in part, to past JISC investments. The
integration of such data provides powerful inputs to social science research in which location is a factor of
uniform underlying importance. However, the transformation of raw geospatial data into a form that is
suitable for research purposes is a demanding and complex process that requires a high degree of technical
ability and a thorough understanding of the data. This explains why researchers and domain experts are often
not using the data to its fullest potential.
2. Environmental Criminology (EC) and the related field of crime analysis are examples of research areas that
could substantially benefit from greater use of existing geospatial datasets. EC is a branch of criminology
that focuses on understanding the underlying social and spatial processes that generate crime patterns and
using the insights from this approach to reduce crime.
3. Not all geographic areas have equal crime risks. Crime opportunities are influenced by factors such as
housing design, street layout and natural surveillance; the accessibility of an area to the offender, the
juxtaposition of different land uses (i.e. what is next to what), the time of day and the willingness of local
residents to challenge strangers and report suspicious activity. Easy and concealed access to the rear of
properties can create opportunities for burglars and drug dealers. People living in highly accessible areas
(served by arterial roads, railways, bus routes) can be more susceptible to crime by travelling offenders than
those living in neighbourhoods with poor communications and fewer escape routes. EC explores the effects
of these types of environmental characteristics on crime and is, therefore, an important field both in terms of
academic research and government approaches to crime reduction. It is also a field in which there is
considerable potential for geospatial data and GIS to play a key role. GIS and spatial data can have enormous
value in the identification, interpretation and prediction of crime patterns; spatially, temporally and within
properties and populations.
4. Within the field of EC there has been a rapid growth in crime mapping and spatial crime analysis, focussed
predominantly in North America and the UK. However, it is evident that research in this field is often based
on analysis of local crime data in isolation, and it is difficult to capture underlying contextual data about the
environment within which a crime occurs, particularly at the disaggregate (i.e. house or street) level. Data
about the land use, physical infrastructure, and socio-economic and demographic characteristics, all of which
have an influence on the timing and location of crime opportunities, are often aggregated to census areas or
other zones based on administrative boundaries. This impairs researchers' attempts to gain a better
understanding of the relationship between contextual factors and crime opportunities at the micro scale.
However, the data required to realise these aims are currently available through services such as Digimap
and the Open Street Map Initiative, but are not commonly being used to advance the study of crime. One of
the factors preventing wide scale use of the data is the technical expertise required to analyse it and to derive
useful geospatial attributes that capture the environmental context of crime with which environmental
criminologists are familiar. A systematic approach to the harnessing and exploitation of existing geospatial
data will enable both the academic and end user communities to explore policy relevant research in EC and
crime analysis on a scale that hitherto has not been possible.
5. To further these aims, this research will make use of existing geospatial data sets and perform analyses to
create new, high-resolution data that will provide essential contextual information for crime analysts and
social science researchers in related fields. The exact data sets, analyses and associated tools are discussed in
detail below. This central objective is closely aligned with the objectives of the programme in general, and
the geospatial strand in particular, as the project will:
•
•
•
Increase the use of geospatial data in a research field not commonly associated with JISC initiatives
and one that is not primarily geospatial in focus nor widely uses geospatial tools;
Help EC researchers improve the quality of their research by providing new, nationally accessible
geospatial data resources;
Enhance the existing geospatial toolset through the development of new routines for analysing
spatial data specifically for crime analysis and, due to their similarities, other social science research
areas (for example, contextual influences on health variations). This will also benefit wider
geospatial and JISC communities.
1.2 Intentions and Scope of the Project 6. As the primary objective of the research is to produce new data that will be used by social scientists, it is
important that the scope is limited to fully satisfy the requirements of stakeholders and the end user
community. Therefore, this research will focus on one particular crime type; residential burglary. This is an
area with a well established theoretical underpinning, yet EC and crime analysis has often been restricted to
the analysis of burglary data from police sources, and has widely ignored geo-spatial datasets that provide
critical contextual information about the locations of burglary.
7. An advantage with focussing on burglary is that there is a well established evidence base of factors which
increase the risk of a property being burgled and existing geospatial data are ideal sources from which this
information can be extracted. These factors include the surveillability of a property (how visible the property
is to neighbours and passers-by), the building type (detached houses, for example, often have more potential
entry points that terraced), the accessibility of a property (how easy the property is to access), the
permeability of the adjacent road (the number of potential burglars who are likely to know about the
building) etc. Clearly these types of variables will be useful for crimes other than residential burglary (e.g.
motor vehicle theft or criminal damage) and also for disciplines other than EC (this will be discussed in more
detail along with sustainability considerations in Section 3.3).
8. The technique of geographically analysing existing building and road data to create additional variables for
crime analysis is an approach that has already been shown to hold merit. Recent research at the University of
Leeds has demonstrated that substantial improvements to crime analysis can be gained by deriving, from
existing digital data sources, the factors that are likely to influence an offender's choice of target for domestic
burglary. The resulting dataset was able to provide researchers with an estimate of the risk of becoming a
victim of crime at the household-level to demonstrate systematically that burglary risk is highly influenced
by natural surveillance, street layouts and the design of the housing stock. Making this type of analysis, and
the resulting data, available to the community would be extremely beneficial both in terms of analysing
current burglary trends as well as predicting future occurrences.
9. Along with new data derived from existing geospatial sources, the research will generate a new software tool
to supplement the data outputs which will be capable of repeating the geospatial analysis methods used to
derive the original data outputs. This will enhance the sustainability of the research by making the analysis
methods formally available as algorithms in computer code and also by providing a tool for non-technical
experts to use. The software will allow users to input a data set and re-calculate the derived variables. For
example, if crime analysts obtain new road network data, they will be able to use the software to re-calculate
the permeability of the individual road segments in the new data. In effect, the community will be able to
analyse and modify their own data in addition to downloading pre-prepared information from repositories.
10. There are a variety of existing tools already in the domain of the geospatial community and these will be
used where ever possible. For example, the Travelling Salesman project
(http://sourceforge.net/projects/travelingsales/), which is part of the OpenStreetMap Initiative, will be useful
in analysing road network data. The software itself could even be released as a plug-in to a communitysupported GIS such as QGIS; significantly reducing the amount of new computer code required for visual
and data I/O operations.
1.3 Project Objectives 11. The previous section has indicated how the proposal will meet the objectives of the call in general. The
specific objectives of the project are to:
•
•
•
•
•
•
•
•
Examine how existing geo-spatial data sets are currently used in crime analysis and related fields and to map
these against user needs;
Identify gaps in existing geo-spatial data sets for crime analysis and related fields;
Explore how current geo-spatial data sets can be exploited to better suit user needs;
Analyse the data and create new datasets with additional variables to support crime analysis;
Publish derived data in geospatial repositories;
Produce software that will enable users to repeat the analysis process on new data as they become available;
Derive a crime-based case study to demonstrate the power of the new data for crime analysis;
Disseminate the results of the project to the geospatial community as well as to crime analysts and
environmental criminologists through a research blog, conference presentations and academic papers.
1.4 Summary of Outputs 12. This section will discuss the outputs in general whilst more formal project deliverables will be identified in
Section 2.1, below. Outputs of the project can be organised into three categories: data, software and text.
Data outputs will include a street-level and a household-level data set with variables that will be useful to
crime analysts, as discussed in Section 1.2. The software output will be an open-source computer program
(or plug-in to an existing program), capable of re-analysing new data to create the chosen attributes. Textual
outputs include a research blog that describes the progress of the research with links to the data and software,
a case study that will utilise the generated data to demonstrate the potential for new types of crime analysis
and several research papers.
13. The proposal and its outputs are well aligned with current research directions in the geospatial community,
both methodologically and in terms of data storage/usage. All data will be deposited into community
repositories such as ShareGeo Open, ShareGeo Digimap and data.gov.uk to make them widely available.
Open data will be utilised wherever possible to minimise access restrictions using sources such as Digimap
OpenStream and OpenStreetMap. The data will also reflect current community trends in data description and
publication by linking descriptions in the project blog to the data themselves using a common strategy such
as UK Location Linked Data. The spatial data will also be linked to relevant meta-data in accordance with
common data infrastructures such as INSPIRE. The software produced will be similarly aligned. Software to
build tools will be released under a GNU General Public License and SourceForge will be used as a code
repository. Where appropriate, existing open source components will be used or adapted to support the
creation of new tools.
14. With regards to input data, there are a large number of sources of which the research could potentially make
use and a wide range of spatial factors that could prove useful to crime researchers. Early stages in the
project will comprise a survey of users to identify their precise requirements, but at this stage the following
are examples of the types of analysis that are possible and will be invaluable for crime research:
•
•
•
Using road network data (such as OpenStreetMap or the OS MasterMap Integrated Transport Network
layer) as an input, develop spatial routines to estimate the integration of each individual road segment
(integration is a measure of how well connected a road is to the rest of the network). This integration
value can be used to estimate the permeability of individual roads or neighbourhoods, i.e. the number of
people who are likely to use the road as part of a journey. This is a factor that has been closely linked to
burglary and one that crime researchers would find extremely useful in their analysis of crime patterns.
Using a building boundary dataset such as the Landmap Feature Collection or the Ordnance Survey
MasterMap Topographic Area, create an estimate of the visibility of buildings from the adjacent road and
from their neighbours. Target visibility is another factor that has been linked to burglary and is a
measure that will substantially improve crime analysis.
Combine a building dataset with a deprivation dataset (such as the Index of Multiple Deprivation) or a
demographic dataset (such as the Output Area Classification) to create measures of proximity to
deprivation which, when combined with other building-level variables such as visibility, can form the
basis of a household burglary risk index.
15. Importantly, these analyses will be extremely useful for researchers in fields other than crime and this is
discussed in Section 3.3, below.
2 Quality of Proposal and Robustness of Workplan 2.1 Project Deliverables 16. To meet the objectives outlined in Section 1.3, the following deliverables will be produced by the project:
•
•
•
•
•
•
A household-level data set with building attributes that are essential to crime analysts.
A street-level data set with similarly useful attributes.
A high-resolution burglary risk dataset, combining information from the derived house- and street-level data
with other data sources (such as deprivation data) to estimate the risk of burglary based on environmental
attributes as specified in the EC literature.
A documented crime case study exhibiting the new datasets and demonstrating their use in crime analysis.
An open source computer program (or plug-in) able to re-generate the household- and street- level datasets.
At least two refereed papers in either the British Journal of Criminology, the Journal of Quantitative
Criminology, the International Journal of Geographical Information Science or the International Journal of
Applied Geospatial Research.
•
An international conference presentation to either the International Seminar on Environmental Criminology
and Crime Analysis (ECCA) (attended by world leaders in environmental criminology) or a geospatial event
such as the OpenStreetMap annual international conference as well as presentations at several national
conferences and community events.
2.2 Project Work Plan / Methodology Stage 1: User geospatial awareness and Needs Assessment
17. The first exercise will be to engage with end users to explore their awareness of geospatial data, current
levels and types of use and future analytical needs. This will be carried out using an online questionnaire that
will be circulated to academic institutions and practitioners (police, community safety partners etc). This
“core” group of potential users will be involved throughout the project, as discussed in Section 3. In addition,
there will be a review of published literature (and unpublished projects) within the UK to:
• Establish current knowledge about and use of geo-spatial data sets in teaching, research and practice;
• Ascertain how these datasets are used by each user group, and the interoperability between the datasets;
• Assess any limitations on the availability of and access to geo-spatial datasets currently used or sought after;
• Identify which datasets and variables the user community require that may be generated by exploiting
existing datasets.
Stage 2: Data Access and the Creation of New High Resolution Data for EC and Crime Analysis
18. This stage will involve accessing the geospatial datasets identified in stage 1 and then analysing and
modifying them to match user requirements highlighted in the needs assessment. These tasks will require
new methods to be developed in order to spatially analyse the input data sets and derive new data. Section
1.4 concluded with an example of the type of analysis that will be conducted. In addition to data creation,
this stage will involve the development of software tools (or plug-ins to existing open source tools) that will
enable users to repeat the analysis process on new data sets as they become available.
Stage 3: Case Study Pilot
19. Having derived new data products, stage 3 will document a scientific case study using the data. The purpose
of the case study will be to exhibit the new data sources to the community and demonstrate how they can be
used to inform crime analysis. It will also form the basis of an academic paper and will be presented to the
community at a crime science conference.
Stage 4: Validation and Sustainability
20. To evaluate the usability of the new datasets, individuals will be selected as part of the stage 1 online
questionnaire. This will evaluate the usefulness and appropriateness of the new datasets to the users and will
also be used to evaluate the potential of the pilot case study for future research and teaching purposes.
21. Throughout the project there will be additional project management and dissemination, engagement with the
user community (through a research blog and dissemination at relevant events), continued project risk
assessment and liaison with the funding body as required.
2.3 Project Timetable Phase
One
Two
Three
Task
Initial Project Team Meeting
User Needs Assessment: Create, Pilot and Deliver Online
Questionnaire
Analyse Findings from Online Questionnaire
Lit Review of Geo-Spatial Datasets used in EC and Crime
Analysis
Interim Report Phase 1: Project Meeting 2
Establish Access to Relevant Datasets
Data Capture
Data Manipulation
Standards
Creation of New Data
Creation of software to supplement data
Interim Report Phase 2: Project Meeting 3
Establish Access to Data for Pilots
MB
1
Staff Days
NM AH
1
1
3
1
1
5
5
5
15
20
1
2
Date
Feb 2011
Feb to Mar 2011
1
10
8
Mar 2011
Feb-Mar 2011
1
3
1
March 2011
April 2011
April 2011
April to June 2011
April to June 2011
May to July 2011
May to July 2011
July 2011
July 2011
2
1
4
AN
1
3
5
5
1
1
5
Four
NA
Data Capture
Data Analysis for Case Study
Write up Case Study
Interim Report Phase 3: Project Meeting Four
Evaluation and Sustainability: Create, Pilot and Deliver
Online Questionnaire
Analyse Online Evaluation Survey
Interim Report Phase 4: Final Meeting
Produce Final Project Report
Project Management (General)
Project Dissemination and Writing Peer Review Papers
Attendance at JISC and other Community Events
Total Staff Days
2
1
1
1
10
20
5
10
10
1
2
1
1
4
1
2
1
1
1
2
-
5
75
5
75
10
July - August 2011
August 2011
August 2011
August 2011
August 2011
August to Sept 2011
September 2011
September 2011
Ongoing throughout
project
2.4 End User Requirements 22. It is essential to fully explore end-user requirements to ensure that the data products produced for this
research fulfils their needs. Therefore, establishing concrete end-user requirements is an early activity in the
project plan, but at this stage it is clear that analysts require:
•
•
•
•
Data to be released in formats that are compatible with the systems most commonly used by analysts
(e.g. ESRI Shapefiles or MapInfo Tab files) as well as open standard formats such as GML;
Data attributes that describe the spatial properties of individual objects that are of direct use in their
research field;
Data that is publically available or available under a HE license;
Tools that are easy to use, well documented and platform independent.
2.5 Measures of Success 23. As the project is relatively short, it is unrealistic to measure success through the amount of community use of
the generated data and applications. Therefore, the success of the project will be determined by:
a. The usefulness of the generated data for crime analysts in academia and outside professional
organisations. This will be established as part of the ongoing user engagement throughout the project;
b. The results of a specific case study conducted using the data as part of the project;
c. The extent to which the research can be published in high quality, peer-reviewed journals;
d. The reception of the research at relevant conferences.
2.6 Management Arrangements 24. The major part of the workload will be shared equally between the research staff at the Universities of Leeds
and Huddersfield. Nick Malleson (Leeds) will be responsible for software development, standards and data
analysis. Andrew Newton (Huddersfield) will be responsible for the user needs assessment and the
development of the case study. Shared activities include data capture and manipulation as well as writing
project reports. Research leadership will be shared between Mark Birkin and Alex Hirschfield, ensuring an
appropriate of geospatial knowledge (Birkin) and criminological domain experience (Hirschfield). An extra
10 days have been allocated to Leeds in recognition of the requirement for overall project management and
coordination. Birkin will have the overall responsibility for managing the strategic direction of the project,
including monitoring ongoing project activities, liaising with research teams at both Universities, ensuring
the research logs are up to date and undertaking any action required in response to the occurrence of planned
or unforeseen risks.
25. The project will be conducted closely with stakeholders who are the most likely users of the generated data,
including professionals at Safer Leeds as well as criminology experts in the University of Huddersfield. This
close working relationship will ensure that the outputs of the project fulfil the main objective; namely to
make existing geospatial data more useful for analysts whose research will benefit considerably from their
use.
2.7 Risk Assessment 26. The following risk assessment analyses risk probability (P) and severity (S) to determine an overall risk
evaluation (E = P*S).
Risk
P
S E
Technical and
data availability
2
1
2
Organisational
2
2
4
Legal / copyright
2
3
6
Security and data
protection
Staffing
1
5
5
2
3
6
Meeting the
needs of users
2
2
4
Description and controls
These risks are limited as the data required for the project are already available and the
analysis methods (such as road integration techniques and spatial building analysis) have
been used successfully in other settings. In the event that technical difficulties do arise, help
can be sought in the geospatial community which is extremely active and supportive.
Although the research team is divided across two institutions, both parties have
considerable collaboration experience and are geographically close. The project team also
have a wide variety of experience in developing geospatial software as well as highly
relevant domain-specific expertise in environmental criminology. Staff hours have been
delegated specifically to project management and organisation.
Some data will have strict copyright and access restrictions. Care will be taken before
releasing derived data to repositories or generating outputs using the data (e.g. maps).
Parts of the project could potentially utilise sensitive crime data. Best practice guidelines
will be followed when handling sensitive data and producing visual outputs.
All staff are in place. If replacement staff are required, full documenting of the project using
code repositories and research logs will simplify the recruitment process.
Both project partners have longstanding experience working with domain experts. To limit
the risk of not meeting user needs, requirement analysis will begin early in the project and
stakeholders will be kept up to date with developments throughout the project. A core group
of interested users will also be established early on.
2.8 IPR Position 27. In accordance with the JISC IPR statement, all data outputs from the project will be released publically (or to
UK HE, FE and Research communities depending on underlying data licences). The source code of the
software application(s) will be the copyright of the University of Leeds and will released under an open
source license to be publically available in perpetuity.
3 Engagement with the Community 3.1 Stakeholder Engagement and Needs Analysis 28. Section 2.4 outlined explicitly the needs of the target users. As the main output of the research will be used
by others, engaging users throughout the lifetime of the project is essential for its success. The partner
institutions are ideally suited for this task as they have access to a wide variety of potential users. The
Applied Criminology Centre in the University of Huddersfield, led by Professor Hirschfield, is at the
forefront of environmental criminology research in the UK and has close working relationships with eminent
criminology researchers. Early project objectives are to engage with this community and establish their
precise needs in terms of the geospatial data that will substantially improve their research potential. A core
group of interested researchers will be established early on and through a series of meetings and
presentations will be able to contribute to the ongoing development of the research.
29. The partners also have close links to professional organisations outside of academia. For example, Safer
Leeds (the public body tasked with coordinating efforts to reduce crime in the Leeds area) have worked
closely with the University of Leeds on a number or research projects and are supporting the bid.
30. Engagement of the wider geospatial community is also important because the community can guide the
development of the project and the outputs will be useful to researchers outside the field of crime analysis.
The School of Geography in the University of Leeds is ideally suited to engage this community as it
currently hosts a number of geospatial bids (many funded by JISC), publishes an applied geospatial journal
(entitled “Applied Spatial Analysis and Policy”) and has been involved in geospatial initiatives such as
CIDER (the Centre for Interaction Data Estimation and Research).
3.2 Dissemination and Evaluation 31. As discussed in Section 1.4, dissemination of the results will take on a number of forms. The most relevant
of these with respect to community engagement are the research blog and presentations at community events.
Additional dissemination will also take place with the core group of users in the form of presentations and
meetings in order to garner specific feedback for ongoing project evaluation. Along with the measures of
success outlined in Section 2.5, evaluation in this manner will help to ensure that the user community will
benefit from the outputs.
3.3 Continued Community Engagement and Sustainability 32. All data outputs will be publically available (as far as licensing restrictions allow) and will be deposited in
public repositories (e.g. ShareGeo). Similarly the accompanying software outputs will be open source and
available in a public code repository (e.g. SourceForge). This, along with proper documentation of the work
and links to the data (e.g. through the UK Location Linked Data strategy) will support the sustainability of
the research beyond the life of the project.
33. To engage with the JISC and geospatial communities, specific days have been allocated in the project plan in
order to attend a community synthesis event and funding has also been allocated to attend additional events
such as the OpenStreetMap international conference. These events will provide an opportunity to
disseminate the ongoing progress of the project as well as gathering opinion on fruitful methods of further
research. Also, by engaging with groups such as the Open Source Geospatial Foundation and DevCSI, the
researchers will be able to make the best use of existing tools, data and methods and seek support as
technical obstacles arise.
34. As discussed, there are a number of important stakeholders in the wider community who could benefit from
this work including the police, community safety partnerships, local authorities etc. Building and
maintaining relationships with these bodies will benefit the wider links between research and practitioners
and could lead to better data sharing and collaboration in the future. This has implications for the long term
sustainability of projects similar to this one and could indirectly benefit the JISC and geospatial communities
in the future. There are also other research fields which could benefit from the new data sources. For
example, the following areas have been highlighted in the UK Location Strategy as potentially benefiting
from greater access to reliable geographical data:
•
•
•
Transport – understanding road or neighbourhood permeability (see Section 1.2) will be useful in
designing efficient transport systems or improving the existing road network;
Security – estimating the visibility of a building to its surroundings is an essential factor in understanding
the risk of numerous types of crime and has obvious relevance for security;
Insurance –the burglary risk profile which will be derived as part of the crime case study will be
extremely relevant in terms of insurance against burglary risk.
Also, it is worth noting that the Strategy itself highlights “crime reduction” specifically as an area that could
benefit from greater geographic data and this further emphasises the importance of the proposal and its
potential for continued research beyond the life of the project.
35. In order to strengthen and sustain the relationship between the lead and partner institutions it is anticipated
that two future research proposals will be developed. The first is a joint bid to the EPSRC (or other relevant
funding body) to enhance the crime analysis tools developed in this proposal, to extend the analysis to
examine other categories of crime (not just burglary) and to extend this research into other related
disciplines. The second will be a bid to the University of Huddersfield University Research Fund (URF)
2011 to create a Centre for Advanced Spatial Analysis which will promote the use of geo-spatial data,
analysis, teaching and training throughout the institution.
4 Budget 36. The following budget identifies how the requested funds have been allocated. A breakdown of costs for the
partner institution, the University of Huddersfield, follows the main budget. The non-staff budget includes
sufficient funds for travel between the partner institutions and covers attendance at several national
conferences and community events. It also covers attendance at an international conference in order to
disseminate the project outputs internationally. We have also acquired letters of support from Safer Leeds
and senior academics at the host institutions which will allow the project to benefit from the advice and
expertise of these third party organisations at no extra cost to the project.
37. As all project outputs are to be released publicly (or as far as possible given data restrictions) the partner
institutions will share the benefits of the project freely with other institutions and the community as a whole.
However, the institutions recognise the positive benefits in terms of publicity and academic/professional
synergy and therefore a contribution of 15% has been offered by each institution.
Feb - Jul 11
BUDGET
Aug - Oct 11
TOTAL £
Directly Incurred Staff
Total Directly Incurred Staff (A)
£0.00
Non-Staff
Feb - Jul 11
£0.00
Aug - Oct 11
Hardware/software
£0.00
TOTAL £
£0
£0
£0
£1,600
£400
£2,000
Evaluation
£0
£0
£0
Other
£0
£0
£0
£2,000
£500
£2,500
Project Partner Costs Total (P)
£23,755.97
£11,377.99
£35,133.96
Directly Incurred Total (C) (A+B+P=C)
£25,755.97
£11,877.99
£37,633.96
Dissemination
Total Directly Incurred Non-Staff (B)
Directly Allocated
Staff
Feb - Jul 11
Aug - Oct 11
TOTAL £
£0
£0
£0
Mark Birkin, Grade 10, 0.11 FTE
£4,101.34
£2,050.67
£6,152
Nick Malleson, Grade 7, 0.40 FTE
£7,654.05
£3,827.03
£11,481
Estates
£2,169.37
£1,084.68
£3,254
£0
£0
£0
£13,924.76
£6,962.38
£20,887.14
£10,212
£5,106
£15,319
Total Project Cost (C+D+E)
£49,893.19
£23,946.60
£73,839.79
Amount Requested from JISC
£42,409.21
£20,354.61
£62,763.82
£7,483.98
£3,591.99
£11,075.97
Other
Directly Allocated Total (D)
Indirect Costs (E)
Institutional Contributions
Percentage Contributions over the life of the project
JISC
Partners
85%
No. FTEs used to calculate indirect and estates charges, and
staff included
No FTEs 0.51
Total
15%
100%
Which Staff Mark Birkin & Nick
Malleson
Breakdown of University of Huddersfield costs
Budget Heading
Staff Name
fte
Directly Allocated
Directly Allocated
Alex Hirschfield
Andrew Newton
Directly Incurred
Directly Allocated
Indirect costs
Dissemination / transport
Estates costs
Full economic cost
Feb-Jul 2011
Aug-Oct 2011
Total fEC
85%
0.05
0.40
2,376.99
10,511.54
1,188.49
5,255.77
3,565.48
15,767.31
3,030.66
13,402.21
0.45
0.45
2,000.00
902.66
7,964.79
500.00
451.33
3,982.39
2,500.00
1,353.99
11,947.18
2,125.00
1,150.89
10,155.11
35,133.96
29,863.86
Contribution from Huddersfield University
5,270.09
5 Previous Experience of the Project Team 38. The Centre for Spatial Analysis and Policy (CSAP) is hosted at the School of Geography, University of
Leeds, and is at the forefront of modern geospatial research. It specialises in analysing, synthesising and
modelling the dynamics of spatial phenomena in a wide range of fields including migration, crime, travel,
demographics, socioeconomic classification and retail behaviour. The School has a strong history of
contributing to the wider geospatial community through projects such as the Centre for Interaction Data
Estimation and Research (CIDER), the publication of the Applied Spatial Analysis and Policy journal and
the creation of the ONS Output Area Classification (OAC).
39. Mark Birkin is Professor of Spatial Analysis and Policy in the School of Geography at the University of
Leeds. He has wide-ranging leadership experience ranging from managing individual projects to
institutional responsibilities. From 2001 until 2005 Mark was Director of the Institute for Interdisciplinary
Informatics, and has also spent four years as leader of the Centre for Spatial Analysis and Policy. He is
currently Director of External Relations in the School of Geography. Mark is the joint PI with Professor
Mike Batty (UCL) of the GENeSIS node of ESRC’s National Centre for Digital Social Research, and is also
director of the JISC project ‘e-infrastructure for social simulation’. He is editor of the journal Applied
Spatial Analysis and Policy, a member of the editorial board of Transactions in GIS, and a member of the
JISC Geospatial Working Group.
40. Dr Nick Malleson (BSc Computer Science, MSc Geo-Informatics, PhD Geography) is a research fellow in
the School of Geography at the University of Leeds and a member of the Centre for Spatial Analysis and
Policy (CSAP). Dr Malleson’s research is interdisciplinary and centres around the development and
application of spatio-temporal computational models in the social sciences. His recently completed doctoral
research implemented a complex micro-level model which used geospatial data and artificial intelligence to
predict and explore occurrences of residential burglary in real cities.
41. The Applied Criminology Centre (ACC) at the University Huddersfield specialises in the evaluation of
situational crime prevention and cross-cutting analyses that explore inter-relationships between crime and the
social, physical and land use environment. It has expertise in the processing and analysis of spatiallyreferenced crime data, geo-demographics and the capture and analysis of data on 'crime generators' (e.g.
bars, night clubs, transport hubs) and on the location, timing and dosage of crime-reduction interventions.
Relevant projects include: Crime & Spatial Concentration of Disadvantage (ESRC); Surveillance & Crime
Reduction (EPSRC); Alcohol Supply Points & Crime (AERC) and major national evaluations for the Home
Office (Reducing Burglary Initiative, Impact of '24 hour drinking' on crime), Neighbourhood Renewal Unit
(New Deal for Communities Crime Theme) and Department for Transport (crime on bus networks). The
ACC has made important contributions to the crime reduction evidence base and has developed new
techniques for measuring crime displacement, diffusion of benefit and cost effectiveness.
42. Professor Alex Hirschfield (BA,PhD,FFPH) Directs the ACC and is an inter-disciplinary environmental
criminologist with an earlier background in human geography (he coordinated the ESRC-funded
Manchester/Liverpool Regional Research Laboratory). He has over 30 years' experience in research and
consultancy and has led large scale national evaluations for the Home Office (burglary reduction),
Neighbourhood Renewal Unit (crime and regeneration) and Youth Justice Board (Preventing Violent
Extremism). He has secured funding from ESRC (Crime and Social Order Programme, Regional Research
Laboratory Initiative, the Social Context of Pathways in Crime - SCoPic), Department of Health (crime and
health impacts), Department for Transport (crime on public transport), EPSRC (surveillance technologies)
and the EU (health and security in EU night clubs); freight crime in the northern European corridor (ERDF
INTERGEG). He is a committee member of the Association for Geographic Information's Crime and
Disorder Special Interest Group and served as Home Office Senior Academic Advisor to Government Office
NW.
43. Dr Andrew Newton (BSc Geography, Msc GIS. PhD Environmental Criminology) has 11 years research
experience in environmental criminology and expertise in working with geospatial data for research and policy
evaluation projects using Geographical Information Systems. His research interests include the geography of
crime, crime and disorder on public transport and along transport routes ('corridors of crime'); crime and youth
disorder, alcohol, violence and the night-time economy and the deployment and evaluation of crime reduction
technologies (e.g. communications and surveillance). He has secured funding from the Home Office, Alcohol
Education Research Council, Department for Transport Merseyside PTE, EPSRC, ERDF (EU), Government
Office North West and the Alberta Gaming and Liquor Commission (AGCL, Canada). He has published
widely in the field and has presented at over fifty national & twenty-five international conferences.