Peter McBrien

ORCID: 0000-0002-2153-9625
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About
Contact & Profiles
Research Areas
  • Advanced Database Systems and Queries
  • Semantic Web and Ontologies
  • Service-Oriented Architecture and Web Services
  • Data Management and Algorithms
  • Business Process Modeling and Analysis
  • Peer-to-Peer Network Technologies
  • Data Quality and Management
  • Distributed systems and fault tolerance
  • Graph Theory and Algorithms
  • Constraint Satisfaction and Optimization
  • Advanced Data Storage Technologies
  • Advanced Software Engineering Methodologies
  • Cognitive Computing and Networks
  • Data Visualization and Analytics
  • Logic, Reasoning, and Knowledge
  • Logic, programming, and type systems
  • Network Security and Intrusion Detection
  • Access Control and Trust
  • Natural Language Processing Techniques
  • Web Data Mining and Analysis
  • Scientific Computing and Data Management
  • semigroups and automata theory
  • Advanced Computational Techniques and Applications

Imperial College London
2008-2019

King's College London
1995-2002

King's College School
2002

Imperial Valley College
1991-2002

We describe a new approach to data integration which subsumes the previous approaches of local as view (LAV) and global (GAV). Our method, we term both (BAV), is based on use reversible schema transformation sequences. show how LAV GAV definitions can be fully derived from BAV sequences, sequences may partially or definitions. also supports evolution schemas, discuss ongoing implementation within AutoMed project.

10.1109/icde.2003.1260795 article EN 2004-05-13

10.1016/s0169-023x(98)00013-5 article EN Data & Knowledge Engineering 1998-10-01

10.1016/s0306-4379(98)00014-3 article EN Information Systems 1998-07-01

Abstract. Recent years have witnessed a growing realization that the development of large data‐intensive, transaction‐oriented information systems is becoming increasingly more difficult as user requirements become broader and sophisticated. Contemporary approaches been criticized for producing which are to maintain provide little assistance in organizational developments. This paper introduces TEMPORA paradigm, currently under advocates closer alignment between policy system functionality....

10.1111/j.1365-2575.1991.tb00032.x article EN Information Systems Journal 1991-04-01

This paper presents SPOWL, which uses Spark to perform OWL reasoning over large ontologies. SPOWL acts as a compiler, maps axioms in the T-Box of an ontology programmes, will be executed iteratively compute and materialise closure results entailed by ontology. Such is then available queries retrieve information from Compared MapReduce, adopting enables cache data distributed memory, reduce amount I/O used, also parallelise jobs more flexible manner. We further analyse dependencies among...

10.1145/3070607.3070609 article EN 2017-05-08

10.5555/1929757.1929792 article EN International Conference on Conceptual Modeling 2010-11-01

In this paper we survey and measure the performance of methods for reasoning using OWL-DL rules over data stored in an RDBMS. Reasoning may be broken down into two processes classification type inference. context databases, is process deriving additional schema constructs from existing a database, while inference inferring values tables/columns other tables/columns. Thus it that focus paper, since as are inserted there need to use derive new facts.

10.1145/2237867.2237873 article EN 2012-05-20
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