Data & 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