Summary

Scientific research is built on the notion of sharing experimental results for peer review, verification, replication and validation. To facilitate this, many scientific disciplines not only share their experimental protocols and results through academic papers but also share their datasets and related experimental meta-data to facilitate replication, evaluation and benchmarking. Within the pervasive healthcare community, the Open Data Initiative (ODI) has been proposed and prototyped to address this need. Key features of this initiative are an ontology representation for description and interrogation of experiment meta-data (activities, devices, participants, protocols, locations), XES (eXtensible Event Stream) mark-up for describing event data in a semantically consistent manner, and integration with open platforms for dataset management. Through this work, many ideas have been generated and questions raised as to the optimum manner in which to specify, model and share experimental datasets in pervasive computing.

The aim of this project is to revise and extend existing work in the Open Data Initiative to address:

*what is the appropriate level of granularity at which to specify concepts in the ODI ontology to maximize both relevance of a dataset to other researchers and also reproducibility of the experiment? This includes the extent to which a dataset repository can facilitate transfer learning methods in activity recognition.

*what is the most useful format for representing event data? Using simple mark-up such as labelled csv files facilitates ease of use but is limited in the semantic information conveyed in the dataset and related meta-data. On the other hand, rich mark-up such as XES embraces semantic richness at the expense of simplicity.

*how should such a standardized approach to data sharing accommodate varying levels of experimental setup and data quality? For example, on the one hand, the experiment protocol might precisely specify dataset features as part of a randomized control trial. On the other hand, the protocol might only specify such features at a high level of abstraction (device, number of participants), to facilitate the quick sharing of results for data exploration.

Given this aim, the proposed project is expected to focus on:

*automated ontological modelling of experimental configurations in pervasive computing to enable flexible modelling granularity, supporting a range of experimental protocols.

*modelling of a workflow which will assist researchers in preparing and assembling their data for sharing with others through the ODI. This will include necessary steps and checks to ensure data integrity and quality before dissemination.

*how to automate the mark-up of collected data in a way which is (a) compliant with open data interchange formats and (b) in a format which facilitates rich semantic description of the data for dataset sharing, matching and reuse by other researchers.

*prototyping the above ideas in an ODI tool through which feedback and evaluation can be meaningfully conducted.

In summary, the aim of the work is to lead towards an ODI tool which will support pervasive computing researchers in the preparation and conduct of experiments which are ready for rapid dissemination within the research community.


Essential criteria

  • To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
  • Sound understanding of subject area as evidenced by a comprehensive research proposal

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • Publications record appropriate to career stage
  • A comprehensive and articulate personal statement
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Vice Chancellors Research Studentship (VCRS)

    Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Bursary (VCRB)

    Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    Fees only award (PhD fees + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £15,285 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies


Other information


The Doctoral College at Ulster University


Reviews

Profile picture of Adrian Johnston

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

Watch Video  

Profile picture of Xin Wei

I received the bachelor’s of engineering degree in computer science and technology from Shangrao Normal University, Jiangxi, China, in 2013; and the master’s degree in computer application and technology from the School of Mathematics and Computer Science, Fujian Normal University, China. When I was pursuing a PhD degree at Ulster University, I continued my research on face recognition and image representation.This long journey has only been possible due to the constant support and encouragement of my first supervisor. I also like to thank my second supervisor for his patience, support and guidance during my research studies. My favourite memory was the days of exercising, gathering and playing with my friends here. If I could speak to myself at the start of my PhD, the best piece of advice I would give myself would be "submit more papers to Journals instead of conferences".

Xin Wei - PhD in Computer Science and Informatics


Profile picture of Jyotsna Talreja Wassan

In the whole PhD ordeal, my supervisory team played a tremendous role:- they are three in a million. They are perfect supervisors who perfectly know which milestones or pathways to be taken during research initiatives, and they understand the roles of virtually all stages in the journey of PhD. They showcased superior abilities in managing and motivating me evoking high standards; demonstrating a commitment to excellence. Jane and Haiying guided me as their daughter and Fiona turned out to be the best of friends.I heard from “Eleanor Roosevelt” that “The future belongs to those who believe in the beauty of their dreams.” The dream with which I grew up to become a Doctor one day, has finally come true. In the journey of PhD, I embraced that a PhD is not just the highest degree in Education but rather it is a life experience where perseverance is the key. I can never forget words from my external examiner Prof Yike Guo, from Imperial College London. His words

Jyotsna Talreja Wassan - PhD in Computer Science and Informatics