Andy Turner | A.G.D.Turner@leeds.ac.uk | Twitter | LinkedIn | ORCID | GitHub

Research officer and scholar specialising in computational geography.

Based in the Centre for Computational Geography (CCG), in the School of Geography (SoG) at the University of Leeds (UoL), Andy began working on a series of research projects from October 1997. Much of this has involved developing and using enhanced research infrastructure and geographical data assimilation, data processing, and data visualisation technology.

Andy tutors students, mentors and supervises student led research projects, runs computer practical sessions, convenes learning modules and moderates assessment on the Geographical Information Systems MSc and Geography BA programmes. Andy also delivers training for the Centre for Doctoral Training on Data Analytics & Society and for Leeds Institute for Data Analytics partners.

Research Ethics Lead for the SoG, Andy is a member of the Business, Environment and Social Sciences Research Ethics Committee otherwise known at UoL as the AREA FREC.

Working with the SoG GeoInclusive Task Force, Andy is aiming to: support functional diversity, promote cultural diversity, encourage inclusive practise, decolonize knowledge, and support people with less privilege and with exploited heritage more.

Andy has wide ranging geographical research interests and is:

• deputy director of the CCG - an interdisciplinary University centre founded in 1992 and originally led by Stan Openshaw; and,
• a member of the four SoG research clusters:
  • Ecology and Global Change
  • River Basin Processes and Management
  • Social Justice, Cities, Citizenship
  • The Centre for Spatial Analysis and Policy

The rest of this Web page is divided into 5 Sections about Andy's work:

1. Aims and Objectives
2. Primary Research Interests
3. Expertise
4. Software Development
5. Research Projects

1. Aims and Objectives

General

• Help develop impartial advice, guidance and good practice documentation for research.
• Review and critique policy and promote evidence-based policy.
• Be inclusive, collaborative and scientific.
• Develop understanding, knowledge, skills and expertise for all to use.
• Ensure that research data is findable, accessible, interoperable and reusable (FAIR) and promote the FAIR Guiding Principles for scientific data management and stewardship.
• Advance a geographical information science based approach to mapping and understanding our world (particularly the immediate generational threats people and wildlife face, but also considering longer term resilience and sustainablility, and thriving not just surviving).
• Advocate the use and development of open source software and code for scientific research and research infrastrucutre.
• Encourage and support work aiming to ease the reproducibility of research results.
• Encourage the use and development of open standards.
• Develop and rekindle interdisciplinary research collaborations and contribute to a wide range of scientific endeavor.

Specific

• Help with the recommissioning of the NERC Environmental Data Service initially by leading a research fellowship aiming to advise on this process.
• Develop a partnership between the SoG and Meanwood Valley Urban Farm.
• Develop a Digital Twin Earth and Solar System and put it to good use.
• Revisit past research work and try to reproduce research results and make it easier for others to do so, and create updated outputs along the same lines and engage in new research that may or may not lead on from these.

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2. Primary Research Interests

• Geographical
  • Methods of data
    • Analysis
    • Mining
    • Visualization
  • Distribution patterns of geographical variables (including types of: people, biota, rock and soil; resource, waste, and phenomena)
  • Modelling
  • Systems science
• Aggregate data and (geographically weighted) statistics
• Environmental change, environmental protection, environmental degradation and pollution
• Land use, land use policy, land use patterns, land use change impacts, land use capability, and land use suitability analysis
• Geomorphology
• Demography
• Epidemiology
• Changes and inequalities in: health, wealth, income and access (to places, information, services and welfare)
• Safety, risk and mitigation
• Sustainable development
• Resource management
• Social justice

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3. Expertise

• Geographical Information Systems
• Linked Data
• Web Services
• Web based information systems
• Research integrity (in particular, data management and research ethics)
• Software engineering
• Reproducibility
• Software sustainability and open source software development
• Java programming
• Grid computing
• Sensitive data classification and management
• I am familiar with:
  • Linux and Windows operating systems
  • A variety of scripting and other programming languages including:
    • Fortran
    • Python
    • JavaScript
    • R
  • A variety of data processing and visualisation methods and software
  • Integrated Development Environments, build, deployment and software engineering tools and services
  • Continuous integration
  • Cloud computing
  • Virtualisation and containerisation
  • Open standards development
  • Numerous technical standards for data access and integration including:
    • OGC Standards
    • ISO TC211 Standards
    • ISO/IEC_27001
    • Data Documentation Initiative
    • Some W3C Standards
    • Some OASIS Standards
    • Some OGF Standards

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4. Software Development

I am developing well tested and documented Java libraries using Maven, JUnit and NetBeans:

• ccg-io: input/output utilities (including an effective way to cache data).
• ccg-math: a range of mathematical functionality including fixed point and arbitrary precision arithmetic and computing with matrices.
• ccg-grids: for storing and processing raster data.
• ccg-v2d: for storing and processing 2D vector geometry.
• ccg-v3d: for storing and processing 3D vector geometry.
• ccg-gws: for Geographically Weighted Statistics.
• ccg-chart: for generating charts from data.
• ccg-text: for text data processing.
• ccg-ukpc: for checking if a sequence of characters might be viable UK unit, sector, district or area postcode and for returning the type (unit/sector/district)
• Processing specific data sets:
  • ccg-data-ukpc: for UK Office for National Statistics Postcode Directory and UK National Statistics Postcode Lookup data processing.
  • ccg-data-stats19: for STATS19 data processing.
  • ccg-data-shbe: for UK Single Housing Benefit Extract data processing.
  • ccg-data-census: for UK Human population Census data processing.
  • ccg-data-waas: for UK Office for National Statistics Wealth and Assets Survey data processing.
  • ccg-data-lr: for UK Land Registry corporate land and property ownership data processing.
  • ccg-data-us: for Understanding Society data processing.
  • ccg-data-elsa: for English Longitudinal Study of Ageing data processing.

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5. Research Projects

I could be interested in any type of academic research project.

A Web page linking to details of my past and present research projects.

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