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Featured researches published by Fan Yang-Turner.


international conference on semantic systems | 2011

A priori ontology modularisation in ill-defined domains

Dhavalkumar Thakker; Vania Dimitrova; Lydia Lau; Ronald Denaux; Stan Karanasios; Fan Yang-Turner

Modularisation is crucial to create re-usable and manageable ontologies. The modularisation is usually performed a posteriori, i.e. after the ontology is developed, and has been applied mainly to well-structured domains. With the increasing popularity of social media, Semantic web technologies are moving towards ill-defined domains that involve cognitively-complex processes carried out by humans and require tacit knowledge (e.g. decision-making, sensemaking, interpersonal communication, negotiating, motivating). In such domains, a priori modularisation can enable ontology creation to handle the complexity and the dynamic nature of knowledge. This paper outlines an a priori modularisation methodology for multi-layered development of ontologies in ill-defined domains, including an upper ontology layer, high-level and reusable domain layers, and case-specific layers. The methodology is being applied in several use cases in two EU projects -- Dicode and ImREAL.


Archive | 2014

Requirements for Big Data Analytics Supporting Decision Making: A Sensemaking Perspective

Lydia Lau; Fan Yang-Turner; Nikos I. Karacapilidis

Big data analytics requires technologies to efficiently process large quantities of data. Moreover, especially in decision making, it not only requires individual intellectual capabilities in the analytical activities but also collective knowledge. Very often, people with diverse expert knowledge need to work together towards a meaningful interpretation of the associated results for new insight. Thus, a big data analysis infrastructure must both support technical innovation and effectively accommodate input from multiple human experts. In this chapter, we aim to advance our understanding on the synergy between human and machine intelligence in tackling big data analysis. Sensemaking models for big data analysis were explored and used to inform the development of a generic conceptual architecture as a means to frame the requirements of such an analysis and to position the role of both technology and human in this synergetic relationship. Two contrasting real-world use case studies were undertaken to test the applicability of the proposed architecture for the development of a supporting platform for big data analysis. Reflection on this outcome has further advanced our understanding on the complexity and the potential of individual and collaborative sensemaking models for big data analytics.


Proceedings of the 2nd International Workshop on Intelligent Exploration of Semantic Data | 2013

Exploring exploratory search: a user study with linked semantic data

Vania Dimitrova; Lydia Lau; Dhavalkumar Thakker; Fan Yang-Turner; Dimoklis Despotakis

The maturation of semantic technologies and the growing popularity of the Linked Open Data (LOD) cloud make it possible to expose linked semantic data sets to end users in order to empower a range of analytical tasks taking advantage of knowledge integration and semantic linking. Linked semantic data appears to offer a great potential for exploratory search, which is open-ended, multi-faceted, and iterative in nature. However, there is limited insight into how browsing through linked semantic data sets can support exploratory search. This paper presents a user study with a uni-focal semantic browsing interface for exploratory search through several data sets linked via domain ontologies. The study, which is qualitative and exploratory in nature and uses music as an illustrative domain, examines (i) obstacles and challenges related to user exploratory search in LOD and (ii) the serendipitous learning effect and the role semantics plays in that. The approach and lessons learnt can benefit future human factor studies to evaluate interactive exploration of linked semantic data, as well as technology developers to become aware of issues that have to be addressed in to facilitate exploratory search with LOD.


international conference on web engineering | 2013

Assisting user browsing over linked data: requirements elicitation with a user study

Dhavalkumar Thakker; Vania Dimitrova; Lydia Lau; Fan Yang-Turner; Dimoklis Despotakis

There are growing arguments that linked data technologies can be utilised to enable user-oriented exploratory search systems for the future Internet. Recently, search over linked data has been studied in different domains and contexts. However, there is still limited insight into how conventional semantic browsers over linked data can be extended to empower exploratory search, which is open-ended, multi-faceted and iterative in nature. Empirical user studies in representative domains can identify problems and elicit requirements for innovative functionality to assist user exploration. This paper presents such an approach --- a user study with a uni-focal semantic data browser over several datasets linked via domain ontologies is used to inform what intelligent features are needed in order to assist exploratory search through linked data. We report main problems experienced by users while conducting exploratory search tasks, based on which requirements for algorithmic support to address the observed issues are elicited. A semantic signposting approach for extending a semantic data browser is proposed as a way to address the derived requirements.


International Journal of Distributed Systems and Technologies | 2016

User Interaction with Linked Data: An Exploratory Search Approach

Dhavalkumar Thakker; Fan Yang-Turner; Dimoklis Despotakis

It is becoming increasingly popular to expose government and citywide sensor data as linked data. Linked data appears to offer a great potential for exploratory search in supporting smart city goals of helping users to learn and make sense of complex and heterogeneous data. However, there are no systematic user studies to provide an insight of how browsing through linked data can support exploratory search. This paper presents a user study that draws on methodological and empirical underpinning from relevant exploratory search studies. The authors have developed a linked data browser that provides an interface for user browsing through several datasets linked via domain ontologies. In a systematic study that is qualitative and exploratory in nature, they have been able to get an insight on central issues related to exploratory search and browsing through linked data. The study identifies obstacles and challenges related to exploratory search using linked data and draws heuristics for future improvements. The authors also report main problems experienced by users while conducting exploratory search tasks, based on which requirements for algorithmic support to address the observed issues are elicited. The approach and lessons learnt can facilitate future work in browsing of linked data, and points at further issues that have to be addressed.


Archive | 2014

The Dicode Collaboration and Decision Making Support Services

Manolis Tzagarakis; Nikos I. Karacapilidis; Spyros Christodoulou; Fan Yang-Turner; Lydia Lau

As broadly admitted, supporting collaboration and decision making in today’s knowledge intensive environment is far from being easy. This is because collaboration settings are often associated with ever-increasing amounts of multiple types of data, obtained from diverse sources that often have a low signal-to-noise ratio for addressing the problem at hand. Towards addressing such concerns, we have developed a series of innovative collaboration and decision making services in the context of the Dicode project. The adopted approach facilitates and augments sense-making and decision making by incrementally formalizing the collaboration context.


asia-pacific software engineering conference | 2012

A Model-Driven Prototype Evaluation to Elicit Requirements for a Sensemaking Support Tool

Fan Yang-Turner; Lydia Lau; Vania Dimitrova

This paper presents a model-driven evaluation approach to elicit requirements. This approach has been applied to evaluate a technology-driven prototype designed to help analysts make sense of Internet forums. Due to the complexity of sensemaking and the immature nature of the prototype, we believe a user evaluation informed by a sensemaking model is beneficial for requirement elicitation. From the evaluation, we have revealed how this tool can be improved by providing a set of requirements in the design space of people, activity in context and technology. Our case study illustrates how a cognitive model can be used in an evaluation to elicit requirements for issues with cognitive complexity.


2011 Workshop on Requirements Engineering for Systems, Services and Systems-of-Systems | 2011

Extending use case diagrams to support requirements discovery

Fan Yang-Turner; Lydia Lau

Requirements discovery is important in the context of system-of-systems because the requirements are not clear at the outset of the project and the future system may bring innovation to users through integration and orchestration. Modelling the existing systems in order to understand the current work practice of domain users is the first step towards requirements elicitation. Use case diagrams can be used for this modelling as they are powerful to express the behaviour of the system in way that all stakeholders can easily understand. However, with the aim of discovering the hidden interaction among humans, systems and data, use case diagrams need to be extended. This paper introduces some extended features of use case diagrams developed in an EU project, which helped project team discover requirements in their three use cases.


Archive | 2014

Collaboration and Decision Making in Data-Intensive and Cognitively-Complex Settings: Lessons Learned from the Dicode Project

Spyros Christodoulou; Manolis Tzagarakis; Nikos I. Karacapilidis; Fan Yang-Turner; Lydia Lau; Vania Dimitrova

This chapter reports on practical lessons learned during the development of innovative collaboration and decision making support services in the context of the Dicode project. These lessons concern: (i) the methodology followed and process carried out for the development of the abovementioned Dicode services (ii) the facilitation and enhancement of collaboration and decision making in data intensive and/or cognitively complex settings, and (iii) related technological and integration issues. Detailed evaluation reports, interviews and discussions within the development teams, as well as analysis of the use of the developed services by end-users through the associated log files, provided valuable feedback for the formulation and compilation of these lessons. By sharing insights gained in the context of the Dicode project, this chapter aims to help people engaged in developing similar services.


Archive | 2014

Making Sense of Linked Data: A Semantic Exploration Approach

Dhavalkumar Thakker; Vania Dimitrova; Lydia Lau; Fan Yang-Turner; Dimoklis Despotakis

There are growing arguments that Linked Data technologies can be utilised to enable user-oriented exploratory search systems for the future Internet. Recently, search over Linked Data has been studied in different domains and contexts. However, there is still limited insight into how conventional semantic browsers over Linked Data can be extended to empower exploratory search, which is open-ended, multi-faceted and iterative in nature. Empirical user studies in representative domains can identify problems and elicit requirements for innovative functionality to assist user exploration. This chapter presents such an approach—a user study with a unifocal semantic data browser over several datasets linked via domain ontologies is used to inform what intelligent features are needed in order to assist exploratory search through Linked Data. We report main problems experienced by users while conducting exploratory search tasks, based on which requirements for algorithmic support to address the observed issues are elicited. A semantic signposting approach for extending a semantic data browser is proposed as a way to address the derived requirements.

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