Aba-Sah Dadzie

Approaches to visualising linked data: a survey

Abstract. The uptake and consumption of Linked Data is currently restricted almost entirely to the Semantic Web community. While the utility of Linked Data to non-tech savvy web users is evident, the lack of technical knowledge and an understanding of the intricacies of the semantic technology stack limit such users in their ability to interpret and make use of the Web of Data. A key solution in overcoming this hurdle is to visualise Linked Data in a coherent and legible manner, allowing nondomain and non-technical audiences to obtain a good understanding of its structure, and therefore implicitly compose queries, identify links between resources and intuitively discover new pieces of information. In this paper we describe key requirements which the visualisation of Linked Data must fulfil in order to lower the technical barrier and make the Web of Data accessible for all. We provide an extensive survey of current efforts in the Semantic Web community with respect to our requirements, and identify the potential for visual support to lead to more effective, intuitive interaction of the end user with Linked Data. We conclude with the conclusions drawn from our survey and analysis, and present proposals for advancing current Linked Data visualisation efforts. Keywords: Linked Data, information visualisation, visual analytics, user-centred design, users, consumption

Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses ontologies as a central modelling strategy for the capture of knowledge from legacy documents via automated means, or directly in systems interfacing with knowledge workers, via user-defined, web-based forms. The domain ontologies used for knowledge capture also guide the retrieval of the knowledge extracted from the data using a semantic search system that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale.

Seeing is believing: linking data with knowledge

The analysis of data using a visual tool is rarely a task done in isolation, it tends to be part of a wider goal: that of making sense of the current situation, often to support decision-making. A user-centred approach is needed in order to properly design interaction that supports sense-making incorporating visual data analysis. This paper reports the experience gained in X-Media, a project that aims to support knowledge management (KM), sharing and reuse across different media in large enterprises. We report the user-centred design approach adopted and the design phases that led to the first prototype. A user evaluation was conducted to assess the design and how different levels of data, information and knowledge were mapped using alternative visual tools. The results show that a clear separation of the visual data analysis from other sense-making sub-tasks helps users in focussing their attention. Users particularly appreciated the data analysis across different media and formats, as well as the support for contextualising information within the broader perspective of KM. Further work is needed to develop more fully intuitive visualisations that exploit the richer information in multimedia documents and make the multiple connections between data more easily accessible.

A theory-based online health behavior intervention for new university students: study protocol

BackgroundToo few young people engage in behaviors that reduce the risk of morbidity and premature mortality, such as eating healthily, being physically active, drinking sensibly and not smoking. The present research developed an online intervention to target these health behaviors during the significant life transition from school to university when health beliefs and behaviors may be more open to change. This paper describes the intervention and the proposed approach to its evaluation.Methods/designPotential participants (all undergraduates about to enter the University of Sheffield) will be emailed an online questionnaire two weeks before starting university. On completion of the questionnaire, respondents will be randomly assigned to receive either an online health behavior intervention (U@Uni) or a control condition. The intervention employs three behavior change techniques (self-affirmation, theory-based messages, and implementation intentions) to target four heath behaviors (alcohol consumption, physical activity, fruit and vegetable intake, and smoking). Subsequently, all participants will be emailed follow-up questionnaires approximately one and six months after starting university. The questionnaires will assess the four targeted behaviors and associated cognitions (e.g., intentions, self-efficacy) as well as socio-demographic variables, health status, Body Mass Index (BMI), health service use and recreational drug use. A sub-sample of participants will provide a sample of hair to assess changes in biochemical markers of health behavior. A health economic evaluation of the cost effectiveness of the intervention will also be conducted.DiscussionThe findings will provide evidence on the effectiveness of online interventions as well as the potential for intervening during significant life transitions, such as the move from school to university. If successful, the intervention could be employed at other universities to promote healthy behaviors among new undergraduates.Trial registrationCurrent Controlled Trials, ISRCTN67684181.

Hide the stack: toward usable linked data

The explosion in growth of the Web of Linked Data has provided, for the first time, a plethora of information in disparate locations, yet bound together by machine-readable, semantically typed relations. Utilisation of the Web of Data has been, until now, restricted to the members of the community, eating their own dogfood, so to speak. To the regular web user browsing Facebook and watching YouTube, this utility is yet to be realised. The primary factor inhibiting uptake is the usability of the Web of Data, where users are required to have prior knowledge of elements from the Semantic Web technology stack. Our solution to this problem is to hide the stack, allowing end users to browse the Web of Data, explore the information it contains, discover knowledge, and use Linked Data. We propose a template-based visualisation approach where information attributed to a given resource is rendered according to the rdf:type of the instance.

Visualisation of Linked Data - Reprise

Linked Data promises to serve as a disruptor of traditional approaches to data management and use, promoting the push from the traditional Web of documents to a Web of data. The ability for data consumers to adopt a follow your nose approach, traversing links defined within a dataset or across independently-curated datasets, is an essential feature of this new Web of Data, enabling richer knowledge retrieval thanks to synthesis across multiple sources of, and views on, interrelated datasets. But for the Web of Data to be successful, we must design novel ways of interacting with the corresponding very large amounts of complex, interlinked, multi-dimensional data throughout its management cycle. The design of user interfaces for Linked Data, and more specifically interfaces that represent the data visually, play a central role in this respect. Contributions to this special issue on Linked Data visualisation investigate different approaches to harnessing visualisation as a tool for exploratory discovery and basic-to-advanced analysis. The papers in this volume illustrate the design and construction of intuitive means for end-users to obtain new insight and gather more knowledge, as they follow links defined across datasets over the Web of Data.

Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data

Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the users ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data. We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive.

Providing visualisation support for the analysis of anatomy ontology data

BackgroundImprovements in technology have been accompanied by the generation of large amounts of complex data. This same technology must be harnessed effectively if the knowledge stored within the data is to be retrieved. Storing data in ontologies aids its management; ontologies serve as controlled vocabularies that promote data exchange and re-use, improving analysis.The Edinburgh Mouse Atlas Project stores the developmental stages of the mouse embryo in anatomy ontologies. This project is looking at the use of visual data overviews for intuitive analysis of the ontology data.ResultsA prototype has been developed that visualises the ontologies using directed acyclic graphs in two dimensions, with the ability to study detail in regions of interest in isolation or within the context of the overview. This is followed by the development of a technique that layers individual anatomy ontologies in three-dimensional space, so that relationships across multiple data sets may be mapped using physical links drawn along the third axis.ConclusionUsability evaluations of the applications confirmed advantages in visual analysis of complex data. This project will look next at data input from multiple sources, and continue to develop the techniques presented to provide intuitive identification of relationships that span multiple ontologies.

Who's who: a linked data visualisation tool for mobile environments

Reduced size in hand-held devices imposes significant usability and visualisation challenges. Semantic adaptation to specific usage contexts is a key feature for overcoming usability and display limitations on mobile devices. We demonstrate a novel application which: (i) links the physical world with the semantic web, facilitating context-based information access, (ii) enhances the processing of semantically enriched, linked data on mobile devices, (iii) provides an intuitive interface for mobile devices, reducing information overload.

Public science communication on Twitter: a visual analytic approach

Purpose – The purpose of this paper is to assess high-dimensional visualisation, combined with pattern matching, as an approach to observing dynamic changes in the ways people tweet about science topics. Design/methodology/approach – The high-dimensional visualisation approach was applied to three science topics to test its effectiveness for longitudinal analysis of message framing on Twitter over two disjoint periods in time. The paper uses coding frames to drive categorisation and visual analytics of tweets discussing the science topics. Findings – The findings point to the potential of this mixed methods approach, as it allows sufficiently high sensitivity to recognise and support the analysis of non-trending as well as trending topics on Twitter. Research limitations/implications – Three topics are studied, these illustrate a range of frames, but results may not be representative of all science topics. Social implications – Funding bodies increasingly encourage scientists to participate in public enga...