About KMi

Visual Exploration of Research Spaces


Knowledge Media Institute, The Open University, Milton Keynes, UK
3 year fully-funded PhD (Oct. 2012-Sept.2015)
Stipend: £40,770 (£13,590/year)

A PhD studentship is available at the Knowledge Media Institute of the Open University on the Visual Exploration of Research Spaces. This project is inherently interdisciplinary and the successful candidate will contribute to our established research in one or more areas, including human-computer interaction, semantic, statistical and natural language technologies.

Project Description

While there are several systems which allow students and researchers to explore information about research and scholarship, support for this complex interpretation task is still insufficient. In particular most solutions are still steeped in the 'bibliographic server' paradigm, which assumes that the main task of interest to a researcher is to locate one or more papers of interest. While of course making sense of research areas indeed requires locating and understanding papers, the notion of 'paper' itself is much too fine-grained to support an exploratory search [1] process adequately, especially when the user is new to an area and her primary aim is to create a conceptual map of the main authors, approaches, events, etc. Even when a variety of visualizations are provided, e.g., by Microsoft Academic Search [2], these visualizations are only partially integrated and only reflect a subset of the various dimensions which are important to the research exploration space. Hence, the aim of this project is to investigate methods for improving the ability of users to explore the rich set of data which are now available about scholarly research, by developing i) new knowledge-based methods for aggregating data from both traditional (e.g., bibliographic servers) and other sources (e.g., blogs, tweets, conference web sites, etc), as well as ii) novel visual analytics solutions, able to support a seamless and flexible exploration of this rich set of aggregated types of data. The proposed system is expected to provide (among other things) support for multiple views over the data; adequate abstraction mechanisms able to generalize from very large data spaces; and the ability to home in and explore in depth specific subsets of the data, on the basis of flexible, user-specified criteria. In particular, we are interested in building on the work carried out on the KC-Viz system for ontology navigation and visualization [3], which relies on a novel abstraction mechanism based on the notion of key concepts, which denote the most important elements of an ontology and act as 'islands' to structure the exploration process and abstract from the large space of concepts in an ontology. Thus, we are interested in developing new methods that can employ this navigation metaphor in the context of research spaces, by identifying the appropriate notions and abstraction techniques, which apply in the research domain. Finally, this project may also need to handle the 'noisy' aspects related to research data, including the use of multiple terms for characterizing the same research areas, the use of the same term to denote different research topics in different domains, the evolution of terminology etc. Hence, the project may require developing a richer semantic framework than what available at the moment, as well as appropriate methods for data linking and disambiguation, to classify and integrate the different types of relevant information.

Person Specification

PhD research is about generating new knowledge, hence we are looking for creative individuals, able to generate and pursue original ideas. Candidates are expected to have an MSc or a first class/2:1 honours degree in computing or a closely related subject and a strong interest in visual, statistical, and semantic technologies. Strong numerical, programming, and communication skills are also essential.

Contact

For further information on this PhD project please contact:

Professor Enrico Motta
Professor of Knowledge Technologies
Email | Professor Enrico Motta Website | Professor Enrico Motta
+44 (0)1908 653506


References

[1] Gary Marchionini. 2006. Exploratory search: from finding to understanding. Commun. ACM 49, 4 (April 2006), 41-46. DOI=10.1145/1121949.1121979

[2] http://academic.research.microsoft.com/

[3] Enrico Motta, Paul Mulholland, Silvio Peroni, Mathieu d'Aquin, Jose Manuel Gomez-Perez, Victor Mendez, and Fouad Zablith. 2011. A novel approach to visualizing and navigating ontologies. In Proceedings of the 10th International Semantic Web Conference (ISWC'11), Lora Aroyo, Chris Welty, Harith Alani, Jamie Taylor, and Abraham Bernstein (Eds.), Vol. Part I. Springer-Verlag, Berlin, Heidelberg, 470-486.

Applications

The relevant application form can be found at http://www.open.ac.uk/research/research-degrees/overview.php.

It is essential that you include both a proposal and a CV with your application. These are central to our judging of applications, both at shortlisting time and afterwards.

Application submissions can be directed to KMi Recruitment Coordinator at the Knowledge Media Institute, Open University, Milton Keynes, MK7 6AA, UK, Tel. +44 (0)1908 654774, Fax +44 (0)1908 653169.

Application Deadline

7th June 2012

 
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Journal | 25 years of knowledge acquisition