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Data and knowledge engineering

Our research in the field of data and knowledge engineering specialises primarily in knowledge representation and reasoning, machine learning and data mining, and mobile and spatial informatics.

This research is embedded in a variety of application domains, where we work closely with end-users. We develop novel techniques for capturing, modelling and processing information, to support knowledgeable decision-making.

Our expertise spans several core areas of artificial intelligence and informatics, including:

  • knowledge representation and reasoning
  • machine learning and data mining
  • distributed intelligent systems.

The group’s research in knowledge representation and reasoning addresses a variety of formalisms, including:

  • logics of argumentation and non-monotonic reasoning
  • lexically-informed logics
  • controlled natural language.

Our strengths in machine learning include:

  • text analytics
  • natural language processing
  • privacy-protection in data mining.

Group members’ interests in distributed intelligent systems include:

  • context-aware decision support
  • sensor informatics
  • heterogeneous information management using ontological approaches.


Research Expertise

Particular areas of strength and expertise in the School include:

  • Ambient information systems
  • Bioinformatics and biodiversity
  • Context-aware systems
  • Data/text/knowledge mining
  • Geoinformatics and spatial information systems
  • Grid-based distributed information management
  • Healthcare and medical informatics
  • Information quality
  • Information security and privacy
  • Linked data and the Semantic Web
  • Resilient information systems
  • Sensor information processing systems
  • Social computing
  • Spatial and temporal reasoning


  • The Catalogue of Life: keeping track of species in managing biodiversity
  • Improved management of cancer patients: the CANISC information system
  • Automated captioning of photo images: the TRIPOD geoinformatics system

Student Contributions

Recent successful PhD students have submitted the following theses:

  • M. Ali - Identifying and Comparing Opportunistic and Social Networks
  • S. Al Yahya - A Computer-Based Holistic Approach to Managing Progress of Distributed Agile Teams
  • E. Elgindy - Extracting Place Semantics from Geo-Folksonomies
  • R. Wright - Multiple systems thinking methods for resilience research
  • D. Pizzocaro - Instantaneous Multi-Sensor Task Allocation in Static and Dynamic Environments
  • G. Shercliff - Quality assessment of service providers in a conformance-centric service oriented architecture

Current Grants & Research Projects

Project information
HolderProject TitleSourceValue (£Ks)
Dr S. SchockaertApproximating markov logic theories in possibilistic logicThe Leverhulme Trust118.26
Dr D Knight, Prof T Fitzpatrick, Dr J Evas and Dr I SpasicCorpws Cenedlaethol Cymraeg Cyfoes (The National Corpus of Contemporary Welsh): A community driven approach to linguistic corpus constructionESRC1829.88
Mr A Hardisty and Professor A PreeceEnvironmental research infrastructures providing shared solutions for science and society - ENVRI PLUSEuropean Commission (Horizon 2020)79.6
Dr S SchockaertFormal lexically informed logics for searching the web - FLEXILOGEuropean Commission (Horizon 2020)1117.63
Professor R. Whitaker and Dr S. AllenGigamobile: Gigabit mobile networking using incentivised operator controlled device-to-device communicationsEPSRC (via Queens University Belfast)316.6
Mr A HardistyGLOBal infrastructure for supporting biodiversity researchEuropean Commission (Horizon 2020)95.8
Professor M Innes and Professor A PreeceOpen source communications, analytics and research (OSCAR) development centreHEFCE508.56
Dr J ShaoTo investigate how a computer based collaborative filtering system can be developed to offer self-serve investment options for retail investorsKTP & Equiniti & Welsh Government299.68
Dr K Button, Dr I Spasic and Professor A SmithUsing qualitative analysis of patient blogs to inform development of automated measurement of self-care with text mining and sentiment analysisWellcome Trust22.33
Professor A Preece together with colleagues from the Schools of Medicine, Dentistry, Healthcare Sciences and OptometryWales Centre for Primary and Emergency CareWelsh Government (NISCHR)2700

Recently Funded Research

The following projects have successfully completed:

  • Implementation of TRAK to develop eRehab for knee conditions: A web based application suite to support self-management in rehabilitation
  • Privacy protection in event-based data sharing and analysis
  • Using the smartphone to monitor mood states