eRaUI – e-Research adaptive User Interface.

1. eRaUI – e-Research adaptive User Interface. Prof FarhiMarir (MSc PhD FBCS CITP) Dr Sahithi Siva (PhD MTechBEng FHEA) Dr Yanguo Jing (PhD) E Ramsay (MSc)

2. eRaUI Aims and Objectives • 1. Identify different types of users and carry out user modelling. Two approaches: • An explicit approach where each user can choose a default user model at the very starting point and depending on his/her behaviour the user model will evolve accordingly. • A machine learning approach in which the user model is built iteratively based on the user behaviour and the pattern of his/her preferences and/or searches.

3. 2. Implement advanced filtering algorithm(s) for extracting appropriate digital content to match user needs. • Content methods will suggest topics similar to ones the user has requested in the past. • Collaborative methods will suggest items outside the user's normal area that the user may find interesting. • These methods will be supported by the user models produced in Objective 1 in recommending choices rating them on some scale, • or giving some similar form of evaluation to help the user in their selections.

4. 3. Analyse and design adaptive UI with workflow system capabilities to support different groups’ activities and learning. • Once the behaviour and the needs of user are identified from Objective 1 & 2, • a workflow process will be implemented to generate actions and plans to guide the users in their learning process through an adaptive minimal interface or • “onion” model of user interfaces in which each layer exposes a different level of complexity providing a graduated learning curve to novice researchers.

5. 4. Use visualisation techniques for better navigation, information display and action planning. • Visualisation techniques will be incorporated to help users develop and widen their search. Search results will be displayed in window panes or an interlinked network similar to the approach used in KartOO (http://www.kartoo.com/).

6. 5. Evaluation and Testing • Provide some mechanisms to measure the engagement of the users with the new eRaUI interface against the existing interface of NaCTeM and other tools. • Evaluate eRaUI interface by our local researchers (PhD, research associates and research academics) • eRaUI interface will be progressively evaluated by a steering committee composed of • Three internal members of staff: Prof Dominic Palmer-Brown who is specialised in machine learning and neural networks, Mr Alan Stuart project manager for the development of the university research management tools, and Mr George Knapp who supports researchers in using online library research tools and services. • Two e-research tools managers: Professor Sophia Ananiadou director of NaCTeM e-research tool and Mr Richard Milton who developed and maintains MapTube (http://www.maptube.org/) e-research tool.

7. eRaUI – Current Progress • eRaUI Blog – logging all the activities and ideas of the eRaUI team: http://eraui.blogspot.com/ • Work Plan published on the blog • eRaUI Storyboard and Implementation Plan published on the blog • Meetings published on the blog • eRaUI Prototype – Under Development