Birkbeck University of London Knowledge Lab | Research | How can innovative computational methods and technologies be leveraged to support individuals and communities in information searching and understanding, and in knowledge creation?

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How can innovative computational methods and technologies be leveraged to support individuals and communities in information searching and understanding, and in knowledge creation?

The ubiquity of digital technologies is making available increasing volumes and varieties of data and information, presenting new opportunities for creating, assimilating, critiquing and sharing knowledge. Applying advanced computational techniques from big data, information integration, information management, information retrieval, knowledge representation and logical reasoning, we design and evaluate tools to support users in finding, combining and visualising information and in creating, assimilating, critiquing and sharing knowledge. We explore the use of social network analysis to understand how people collaborate with and influence each other and how knowledge diffuses through such networks.


We explore the use of semantic web technologies to design more effective ways of searching and integrating information, for example by accessing rich datasets through ontologies, which enable the retrieval of information according to conceptual relations established iteratively between domain experts and computer scientists. We work with experts from across the arts and humanities, sciences and social sciences on the digitisation and management of specialist datasets and the design of analyses and visualisations that can support knowledge creation and knowledge discovery, in domains such as cultural heritage preservation, historical text analysis, and health informatics.

Large volumes of information are being published on the Web in the form of Linked Open Data and are being increasingly used in areas such as formal and informal learning, careers guidance, entertainment, health and culture. Due to the volumes, complexity and heterogeneity of the data, users may not be familiar with its full structure, leading to the need for mechanisms to support users in finding and questioning useful information. We are researching techniques from heterogeneous data integration, ontology-based data access and flexible query processing to assist users in their exploration and querying of large complex knowledge graphs across a variety of application domains.

Projects

Data Integration in Dataspaces

Flexible Querying and Integration of Linked Data

Mapping Museums

Ontop

SAMTLA

Weaving Communities of Practice

Completed projects

ASSIST

AutoMed

BioMap

Classification-based Search

Classification using Discernibility

Clustering for Large-scale Social Networks

Computational Logic of Euclidean Spaces

Database Query Optimisation Under Uncertainty

ePALS : Expertise Profiling

ExODA: Ontology-Based Data Access

Finding and Summarizing Answers from Online Communities

Flexible Querying of Semi-Structured Data

Flexible Querying of Network-Structured Data

Genetic Programming Representations for Complex Systems Modelling

iSPIDER: A Pilot Grid for Integrative Proteomics

Meaningful mining and visualisation of data from RSS feeds

Personalisation of Web Search Results

Quality-driven Heterogenous Data Integration

Reliable XML Message Management for Web Services