The Information Management Group (IMG) conducts research into the design, development and use of data and knowledge management systems. Research activities are broad in nature and scope, including basic research on models and languages that underpins research on algorithms, technologies and architectures. Challenging applications motivate and validate our research, in particular in the Semantic Web and e-Science.
Our research includes work in the following specialist areas:
Data scientists are employed to obtain insights from data through analysis. However, it is widely reported that data scientists are spending as much as 80% of their time discovering, integrating and cleaning data prior to analysis; these tasks are known as data preparation or data wrangling. To increase the cost-effectiveness of data preparation, we investigate techniques for hands-off data preparation, where the user describes what is needed, and the system works out how to wrangle this from available datasets. Such research brings together data integration, data cleaning, decision support, program synthesis and data discovery. Research in data preparation has been funded by the EPSRC, and we are working through a Knowledge Transfer Partnership to deploy innovative data preparation techniques with Peak. Some of our results are being commercialised by The Data Value Factory.
Network and distributed system security
We are interested in designing smart security solutions for smart systems. We have been working on cryptographic methods, security protocols and system architectures to protect networks, devices, and data from security attacks or unauthorized access in networked and distributed systems. The settings for our work include wireless sensor networks, mobile ad hoc networks, ubiquitous computing, electronic commerce, Internet of Things (IoT), and Cloud computing, with a focus on threat identification, risk assessment and countermeasure designs. Example projects include secure routing protocols for ad hoc networks, malware detections and preventions, cryptographic methods for protecting Big Data, security protocols for privacy-preserving data collections, risk-based authentication, dynamic access control, and trust management.