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j.websem.2017.12.003 author me.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 author tom_seymoens.
j.websem.2017.12.003 author erik_mannens.
j.websem.2017.12.003 author dimitri_schuurman.
j.websem.2017.12.003 author aron_levi_herregodts.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 creator me.
j.websem.2017.12.003 creator me.
j.websem.2017.12.003 creator tom_seymoens.
j.websem.2017.12.003 creator erik_mannens.
j.websem.2017.12.003 creator dimitri_schuurman.
j.websem.2017.12.003 creator aron_levi_herregodts.
j.websem.2017.12.003 creator me.
j.websem.2017.12.003 creator me.
j.websem.2017.12.003 about visualization.
j.websem.2017.12.003 about RML.
j.websem.2017.12.003 about rules.
j.websem.2017.12.003 about Research.
j.websem.2017.12.003 about Linked_Data.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 author tom_seymoens.
j.websem.2017.12.003 author erik_mannens.
j.websem.2017.12.003 author dimitri_schuurman.
j.websem.2017.12.003 author aron_levi_herregodts.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 author me.
j.websem.2017.12.003 coparticipatesWith me.
j.websem.2017.12.003 coparticipatesWith me.
j.websem.2017.12.003 coparticipatesWith tom_seymoens.
j.websem.2017.12.003 coparticipatesWith erik_mannens.
j.websem.2017.12.003 coparticipatesWith dimitri_schuurman.
j.websem.2017.12.003 coparticipatesWith aron_levi_herregodts.
j.websem.2017.12.003 coparticipatesWith me.
j.websem.2017.12.003 coparticipatesWith me.
j.websem.2017.12.003 type PublicationVolume.
j.websem.2017.12.003 type ScholarlyArticle.
j.websem.2017.12.003 type Article.
j.websem.2017.12.003 type Document.
j.websem.2017.12.003 type Document.
j.websem.2017.12.003 type Document.
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j.websem.2017.12.003 type Work.
j.websem.2017.12.003 P50 me.
j.websem.2017.12.003 P50 me.
j.websem.2017.12.003 P50 tom_seymoens.
j.websem.2017.12.003 P50 erik_mannens.
j.websem.2017.12.003 P50 dimitri_schuurman.
j.websem.2017.12.003 P50 aron_levi_herregodts.
j.websem.2017.12.003 P50 me.
j.websem.2017.12.003 P50 me.
j.websem.2017.12.003 maker me.
j.websem.2017.12.003 maker me.
j.websem.2017.12.003 maker tom_seymoens.
j.websem.2017.12.003 maker erik_mannens.
j.websem.2017.12.003 maker dimitri_schuurman.
j.websem.2017.12.003 maker aron_levi_herregodts.
j.websem.2017.12.003 maker me.
j.websem.2017.12.003 maker me.
j.websem.2017.12.003 title "Specification and Implementation of Mapping Rule Visualization and Editing: MapVOWL and the RMLEditor".
j.websem.2017.12.003 isPartOf journal_of_web_semantics.
j.websem.2017.12.003 name "Specification and Implementation of Mapping Rule Visualization and Editing: MapVOWL and the RMLEditor".
j.websem.2017.12.003 label "Specification and Implementation of Mapping Rule Visualization and Editing: MapVOWL and the RMLEditor".
j.websem.2017.12.003 name "Specification and Implementation of Mapping Rule Visualization and Editing: MapVOWL and the RMLEditor".
j.websem.2017.12.003 topic visualization.
j.websem.2017.12.003 topic RML.
j.websem.2017.12.003 topic rules.
j.websem.2017.12.003 topic Research.
j.websem.2017.12.003 topic Linked_Data.
j.websem.2017.12.003 subject visualization.
j.websem.2017.12.003 subject RML.
j.websem.2017.12.003 subject rules.
j.websem.2017.12.003 subject Research.
j.websem.2017.12.003 subject Linked_Data.
j.websem.2017.12.003 authorList b0_b2113.
j.websem.2017.12.003 topic visualization.
j.websem.2017.12.003 topic RML.
j.websem.2017.12.003 topic rules.
j.websem.2017.12.003 topic Research.
j.websem.2017.12.003 topic Linked_Data.
j.websem.2017.12.003 abstract "Visual tools are implemented to help users in defining how to generate Linked Data from raw data. This is possible thanks to mapping languages which enable detaching mapping rules from the implementation that executes them. However, no thorough research has been conducted so far on how to visualize such mapping rules, especially if they become large and require considering multiple heterogeneous raw data sources and transformed data values. In the past, we proposed the RMLEditor, a visual graph-based user interface, which allows users to easily create mapping rules for generating Linked Data from raw data. In this paper, we build on top of our existing work: we (i) specify a visual notation for graph visualizations used to represent mapping rules, (ii) introduce an approach for manipulating rules when large visualizations emerge, and (iii) propose an approach to uniformly visualize data fraction of raw data sources combined with an interactive interface for uniform data fraction transformations. We perform two additional comparative user studies. The first one compares the use of the visual notation to present mapping rules to the use of a mapping language directly, which reveals that the visual notation is preferred. The second one compares the use of the graph-based RMLEditor for creating mapping rules to the form-based RMLx Visual Editor, which reveals that graph-based visualizations are preferred to create mapping rules through the use of our proposed visual notation and uniform representation of heterogeneous data sources and data values.".
j.websem.2017.12.003 datePublished "2018".
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