Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation

Fu, Bo; Noy, Natalya F.; Storey, Margaret-Anne

doi:10.1007/978-3-642-41335-3_8

Cited by 45 publications

(44 citation statements)

References 22 publications

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“…Regarding our study, one limitation, that needs to be addressed in future work, is that all systems in the interface evaluations represent ontologies as trees. It was shown in [9] that a graph representation may be more suitable when dealing with multiple inheritance.…”

Section: Discussionmentioning

confidence: 99%

Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment

Іванова

Lambrix

Åberg

2015

The Semantic Web. Latest Advances and New Domains

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Currently one of the challenges for the ontology alignment community is the user involvement in the alignment process. At the same time, the focus of the community has shifted towards large-scale matching which introduces an additional dimension to this issue. This paper aims to provide a set of requirements that foster the user involvement for large-scale ontology alignment tasks.Further, we present and discuss the results of a literature study for 7 ontology alignments systems as well as a heuristic evaluation and an observational user study for 3 ontology alignment systems to reveal the coverage of the requirements in the systems and the support for the requirements in the user interfaces

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Section: Discussionmentioning

confidence: 99%

Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment

Іванова

Lambrix

Åberg

2015

The Semantic Web. Latest Advances and New Domains

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“…In contrast, this paper applies direct measures through eye tracking to gain a deeper understanding of why one visualization is better than the other. Complementary to what has been explored previously in [9], we present eye movement data analysis in this paper. In particular, we aim to answer the following research questions:…”

Section: Introductionmentioning

confidence: 99%

Eye tracking the user experience – An evaluation of ontology visualization techniques

Noy

Storey

2016

Self Cite

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Abstract. Various ontology visualization techniques have been developed over the years, offering essential interfaces to users for browsing and interacting with ontologies, in an effort to assist with ontology understanding. Yet few studies have focused on evaluating the usability of existing ontology visualization techniques. This paper presents an eye-tracking user study that evaluates two commonly used ontology visualization techniques, namely, indented list and graph. The eye-tracking experiment and analysis presented in this paper complements the set of existing evaluation protocols for ontology visualization. In addition, the results found from this study contribute to a greater understanding of the strengths and weaknesses of the two visualization techniques, and in particular, how and why one is more effective than the other. Based on approximately 500MB of eye movement data containing around 30 million rows of gaze data generated by a Tobii eye tracker, we found evidence suggesting indented lists are more efficient at supporting information searches and graphs are more efficient at supporting information processing.

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“…Displaying the output of a query as a graph provides the user with an overarching perspective of the field of interest, which is not available (or, at best, severely obscured) when presenting query results in the form of a list (such as relevant job adverts are formatted by http://indeed.co.uk, for instance). Moreover, from a human computer interaction perspective, research shows that displaying knowledge as graphs is more informative than lists (indented trees) [15,24]. Another, indirect, advantage of displaying a career connectivity map rather than a list is the possibility of uncovering new, potentially relevant careers that the user may not have considered otherwise.…”

Section: Perspectivementioning

confidence: 99%

An architecture for the autonomic curation of crowdsourced knowledge

et al. 2017

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Human knowledge curators are intrinsically better than their digital counterparts at providing relevant answers to queries. That is mainly due to the fact that an experienced biological brain will account for relevant community expertise as well as exploit the underlying connections between knowledge pieces when offering suggestions pertinent to a specific question, whereas most automated database managers will not. We address this problem by proposing an architecture for the autonomic curation of crowdsourced knowledge, that is underpinned by semantic technologies. The architecture is instantiated in the career data domain, thus yielding Aviator, a collaborative platform capable of producing complete, intuitive and relevant answers to career related queries, in a time effective manner. In addition to pro- The Good Careers Guide, London, UK viding numeric and use case based evidence to support these research claims, this extended work also contains a detailed architectural analysis of Aviator to outline its suitability for automatically curating knowledge to a high standard of quality.

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Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation

Cited by 45 publications

References 22 publications

Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment

Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment

Eye tracking the user experience – An evaluation of ontology visualization techniques

An architecture for the autonomic curation of crowdsourced knowledge

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