research-article

Formal Linked Data Visualization Model

Authors:

Josep Maria Brunetti,

Roberto García,

Martin NečaskýAuthors Info & Claims

IIWAS '13: Proceedings of International Conference on Information Integration and Web-based Applications & Services

Pages 309 - 318

https://doi.org/10.1145/2539150.2539162

Published: 02 December 2013 Publication History

Abstract

Recently, the amount of semantic data available in the Web has increased dramatically. The potential of this vast amount of data is enormous but in most cases it is difficult for users to explore and use this data, especially for those without experience with Semantic Web technologies. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. In this article we devise a formal Linked Data Visualization Model (LDVM), which allows to dynamically connect data with visualizations. We report about our implementation of the LDVM comprising a library of generic visualizations that enable both users and data analysts to get an overview on, visualize and explore the Data Web and perform detailed analyzes on Linked Data.

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Cited By

Bushati GRasmusen SKurteva AVats ANako PFensel A(2024)What is in your cookie box? Explaining ingredients of web cookies with knowledge graphsSemantic Web10.3233/SW-23343515:5(1593-1609)Online publication date: 9-Oct-2024
https://doi.org/10.3233/SW-233435
Renda GDaquino MPresutti V(2023)MelodyProceedings of the 34th ACM Conference on Hypertext and Social Media10.1145/3603163.3609035(1-8)Online publication date: 4-Sep-2023
https://dl.acm.org/doi/10.1145/3603163.3609035
Menin AMaillot PFaron CCorby OFreitas CGandon FWinckler M(2023)LDViz: A Tool to Assist the Multidimensional Exploration of SPARQL EndpointsWeb Information Systems and Technologies10.1007/978-3-031-24197-0_9(149-173)Online publication date: 18-Jan-2023
https://doi.org/10.1007/978-3-031-24197-0_9
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Index Terms

Formal Linked Data Visualization Model
1. Human-centered computing
  1. Human computer interaction (HCI)

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IIWAS '13: Proceedings of International Conference on Information Integration and Web-based Applications & Services

December 2013

753 pages

ISBN:9781450321136

DOI:10.1145/2539150

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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@WAS: International Organization of Information Integration and Web-based Applications and Services

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Association for Computing Machinery

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Publication History

Published: 02 December 2013

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IIWAS '13

IIWAS '13: The 15th International Conference on Information Integration and Web-based Applications & Services

December 2 - 4, 2013

Vienna, Austria

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https://doi.org/10.3233/SW-233435
Renda GDaquino MPresutti V(2023)MelodyProceedings of the 34th ACM Conference on Hypertext and Social Media10.1145/3603163.3609035(1-8)Online publication date: 4-Sep-2023
https://dl.acm.org/doi/10.1145/3603163.3609035
Menin AMaillot PFaron CCorby OFreitas CGandon FWinckler M(2023)LDViz: A Tool to Assist the Multidimensional Exploration of SPARQL EndpointsWeb Information Systems and Technologies10.1007/978-3-031-24197-0_9(149-173)Online publication date: 18-Jan-2023
https://doi.org/10.1007/978-3-031-24197-0_9
Menin ADo MDal Sasso Freitas CCorby OFaron CGiboin AWinckler M(2022)Using Chained Views and Follow-Up Queries to Assist the Visual Exploration of the Web of Big Linked DataInternational Journal of Human–Computer Interaction10.1080/10447318.2022.211252940:2(224-240)Online publication date: 23-Aug-2022
https://doi.org/10.1080/10447318.2022.2112529
Koubarakis MBereta KNikolaou CStamoulis G(2022)Linked Geospatial DataEncyclopedia of Big Data Technologies10.1007/978-3-319-63962-8_71-3(1-8)Online publication date: 26-Nov-2022
https://doi.org/10.1007/978-3-319-63962-8_71-3
Sobral TGalvão TBorges J(2021)VUMO: Towards an ontology of urban mobility events for supporting semi-automatic visualization tools2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC.2016.7795787(1700-1705)Online publication date: 10-Mar-2021
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Reda RPiccinini FMartinelli GCarbonaro A(2021)Heterogeneous self-tracked health and fitness data integration and sharing according to a linked open data approachComputing10.1007/s00607-021-00988-w104:4(835-857)Online publication date: 5-Aug-2021
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Destandau MAppert CPietriga E(2020)S-Paths: Set-based visual exploration of linked data driven by semantic pathsSemantic Web10.3233/SW-200383(1-18)Online publication date: 16-Sep-2020
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Po LBikakis NDesimoni FPapastefanatos G(2020)Linked Data Visualization: Techniques, Tools, and Big DataSynthesis Lectures on the Semantic Web: Theory and Technology10.2200/S00967ED1V01Y201911WBE01910:1(1-157)Online publication date: 18-Mar-2020
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Krommyda MKantere V(2020)Visualization Systems for Linked Datasets2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00171(1790-1793)Online publication date: Apr-2020
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