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dc.contributor.authorBrunetti Fernández, Josep Maria
dc.contributor.authorGarcía González, Roberto
dc.date.accessioned2015-02-11T13:35:08Z
dc.date.available2015-02-11T13:35:08Z
dc.date.issued2014
dc.identifier.issn0001-253X
dc.identifier.urihttp://hdl.handle.net/10459.1/47938
dc.description.abstractPurpose: The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach: The Visual Information-Seeking Mantra"Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings: The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value: Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherEmerald
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1108/AJIM-12-2013-0153
dc.relation.ispartofAslib Proceedings, 2014, vol. 66, núm. 5, p. 519-536
dc.rights(c) Emerald, 2014
dc.subjectHuman computer interaction
dc.subjectSearch
dc.subjectLinked data
dc.subjectExploration
dc.subject.classificationWeb semàntic
dc.subject.otherSemantic web
dc.titleUser-centered design and evaluation of overview components for semantic data exploration
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2015-02-11T13:35:08Z
dc.identifier.idgrec021988
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1108/AJIM-12-2013-0153


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