The Internet of Things (IoT) refers to the seamless integration of physical objects, sensors and mobile devices into the information network. The IoT encompasses numerous technologies, services and standards and is seen by many as the cornerstone of the emerging ICT market. The UK Government Office for Science report The Internet of Things: Making the Most of the Second Digital Revolution identifies trust and public acceptability both as central to IoT and as sources of considerable uncertainty.
Data provenance is recognised as one of the key enablers of a trusted information infrastructure – as it exposes the history of data and any subsequent manipulation/modifications. Consider the case of a faulty IoT device that reports incomplete or erroneous data – that has the potential to result in real physical consequences. Only by understanding the context of the device and the data it produces can we (or automated systems) determine if the data are reliable and actionable. While veracity is often listed as one of the seven Vs of Big Data, along with volume, velocity, variety, variability, visualization and value – it is perhaps the most important and least studied.
You will explore the following questions:
How can data veracity measures (metrics) be encoded and enacted within an IoT ecosystem?
How can data provenance be used to support new forms of veracity checking and anomaly detection?
How can data policies be framed to reason about data veracity, and recommend appropriate decision-making actions?
Real-world examples drawn from the EPSRC TrustLens project will be used, including scenarios based on data generated by Internet of Things devices.
The successful candidate will have or expect to have a UK First Class Honours Degree (or equivalent) or a UK Honours Degree at 2.1 (or equivalent) in COMPUTER SCIENCE or related discipline, ALONG WITH an MSc Degree (or equivalent) at Commendation or Distinction.
Essential background: Data science; programming in Python or Java.
Knowledge of: Desirable - Semantic Web, knowledge representation and reasoning.
this project is advertised in relation to the research areas of the discipline of Computing Science. Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php
You should apply for Degree of Doctor of Philosophy in Computing Science, to ensure that your application is passed to the correct person for processing. NOTE CLEARLY THE NAME OF THE SUPERVISOR and EXACT PROJECT TITLE ON THE APPLICATION FORM. IF YOU DO NOT MENTION ELPHINSTONE FUNDING ON YOUR APPLICATION THEN IT WILL NOT BE CONSIDERED FOR THE SCHOLARSHIP. Applicants are limited to applying for a maximum of 2 Elphinstone funded projects. Any further applications received will be automatically withdrawn.
Informal inquiries can be made to Professor P Edwards ([email protected]
) with a copy of your curriculum vitae and cover letter indicating your interest in the project and why you wish to undertake it. All general enquiries should be directed to the Postgraduate Research School ([email protected]