Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach

We investigate the design of ontology-supported, progressively disclosed visual analytics interfaces for searching and triaging large document sets. The goal is to distill a set of criteria that can help guide the design of such systems. We begin with a background of information search, triage, mach...

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Main Authors: Jonathan Demelo, Kamran Sedig
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/13/1/8
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author Jonathan Demelo
Kamran Sedig
author_facet Jonathan Demelo
Kamran Sedig
author_sort Jonathan Demelo
collection DOAJ
description We investigate the design of ontology-supported, progressively disclosed visual analytics interfaces for searching and triaging large document sets. The goal is to distill a set of criteria that can help guide the design of such systems. We begin with a background of information search, triage, machine learning, and ontologies. We review research on the multi-stage information-seeking process to distill the criteria. To demonstrate their utility, we apply the criteria to the design of a prototype visual analytics interface: VisualQUEST (Visual interface for QUEry, Search, and Triage). VisualQUEST allows users to plug-and-play document sets and expert-defined ontology files within a domain-independent environment for multi-stage information search and triage tasks. We describe VisualQUEST through a functional workflow and culminate with a discussion of ongoing formative evaluations, limitations, future work, and summary.
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spelling doaj.art-706bef57d1024f4792f23661093f45d12023-11-23T14:08:16ZengMDPI AGInformation2078-24892021-12-01131810.3390/info13010008Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics ApproachJonathan Demelo0Kamran Sedig1Department of Computer Science, Western University, London, ON N6A 3K7, CanadaDepartment of Computer Science, Western University, London, ON N6A 3K7, CanadaWe investigate the design of ontology-supported, progressively disclosed visual analytics interfaces for searching and triaging large document sets. The goal is to distill a set of criteria that can help guide the design of such systems. We begin with a background of information search, triage, machine learning, and ontologies. We review research on the multi-stage information-seeking process to distill the criteria. To demonstrate their utility, we apply the criteria to the design of a prototype visual analytics interface: VisualQUEST (Visual interface for QUEry, Search, and Triage). VisualQUEST allows users to plug-and-play document sets and expert-defined ontology files within a domain-independent environment for multi-stage information search and triage tasks. We describe VisualQUEST through a functional workflow and culminate with a discussion of ongoing formative evaluations, limitations, future work, and summary.https://www.mdpi.com/2078-2489/13/1/8interface designontologiesvisual analyticsvisualizationsinteractionmachine learning
spellingShingle Jonathan Demelo
Kamran Sedig
Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach
Information
interface design
ontologies
visual analytics
visualizations
interaction
machine learning
title Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach
title_full Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach
title_fullStr Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach
title_full_unstemmed Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach
title_short Interfaces for Searching and Triaging Large Document Sets: An Ontology-Supported Visual Analytics Approach
title_sort interfaces for searching and triaging large document sets an ontology supported visual analytics approach
topic interface design
ontologies
visual analytics
visualizations
interaction
machine learning
url https://www.mdpi.com/2078-2489/13/1/8
work_keys_str_mv AT jonathandemelo interfacesforsearchingandtriaginglargedocumentsetsanontologysupportedvisualanalyticsapproach
AT kamransedig interfacesforsearchingandtriaginglargedocumentsetsanontologysupportedvisualanalyticsapproach