PUMA publications for /user/diglezakis/visualizationhttps://puma.ub.uni-stuttgart.de/user/diglezakis/visualizationPUMA RSS feed for /user/diglezakis/visualization2024-03-29T15:23:52+01:00Prov Viewer: A Graph-Based Visualization Tool for Interactive Exploration of Provenance Datahttps://puma.ub.uni-stuttgart.de/bibtex/2137cddb38ddebf08ad6e10a6a5995d1d/diglezakisdiglezakis2018-05-11T11:08:59+02:00forschungsdaten metadata provenance visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Troy Kohwalter" itemprop="url" href="/person/1486df7ee5e4e6d9b3c1566d4dfbbf0f2/author/0"><span itemprop="name">T. Kohwalter</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Thiago Oliveira" itemprop="url" href="/person/1486df7ee5e4e6d9b3c1566d4dfbbf0f2/author/1"><span itemprop="name">T. Oliveira</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Juliana Freire" itemprop="url" href="/person/1486df7ee5e4e6d9b3c1566d4dfbbf0f2/author/2"><span itemprop="name">J. Freire</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Esteban Clua" itemprop="url" href="/person/1486df7ee5e4e6d9b3c1566d4dfbbf0f2/author/3"><span itemprop="name">E. Clua</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Leonardo Murta" itemprop="url" href="/person/1486df7ee5e4e6d9b3c1566d4dfbbf0f2/author/4"><span itemprop="name">L. Murta</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Provenance and Annotation of Data and Processes</span>, </em></span><em>page <span itemprop="pagination">71--82</span>. </em><em>Cham, </em><em><span itemprop="publisher">Springer International Publishing</span>, </em>(<em><span>2016<meta content="2016" itemprop="datePublished"/></span></em>)</span>Fri May 11 11:08:59 CEST 2018ChamProvenance and Annotation of Data and Processes71--82Prov Viewer: A Graph-Based Visualization Tool for Interactive Exploration of Provenance Data2016forschungsdaten metadata provenance visualization The analysis of provenance data for an experiment is often crucial to understand the achieved results. For long-running experiments or when provenance is captured at a low granularity, this analysis process can be overwhelming to the user due to the large volume of provenance data. In this paper we introduce, Prov Viewer, a provenance visualization tool that enables users to interactively explore provenance data. Among the visualization and exploratory features, we can cite zooming, filtering, and coloring. Moreover, we use of other properties such as shape and size to distinguish visual elements. These exploratory features are linked to the provenance semantics to ease the comprehension process. We also introduce collapsing and filtering strategies, allowing different levels of granularity exploration and analysis. We describe case studies that show how Prov Viewer has been successfully used to explore provenance in different domains, including games and urban data.Prov Viewer: A Graph-Based Visualization Tool for Interactive Exploration of Provenance Data | SpringerLinkStatistical Modeling by Gesture: A graphical, Browser-based Statistical Interface for Data Repositories.https://puma.ub.uni-stuttgart.de/bibtex/26ead8b362af6e29f42225c4a4b712c95/diglezakisdiglezakis2018-11-19T08:40:13+01:00data dataverse forschungsdaten statistics tools visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="James Honaker" itemprop="url" href="/person/1832232a507428484cc9aedf97bcce01b/author/0"><span itemprop="name">J. Honaker</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Vito D'Orazio" itemprop="url" href="/person/1832232a507428484cc9aedf97bcce01b/author/1"><span itemprop="name">V. D'Orazio</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">HT (Doctoral Consortium / Late-breaking Results / Workshops)</span>, </em></span><em>volume 1210 of CEUR Workshop Proceedings, </em><em><span itemprop="publisher">CEUR-WS.org</span>, </em>(<em><span>2014<meta content="2014" itemprop="datePublished"/></span></em>)</span>Mon Nov 19 08:40:13 CET 2018HT (Doctoral Consortium / Late-breaking Results / Workshops)conf/ht/2014dcCEUR Workshop ProceedingsStatistical Modeling by Gesture: A graphical, Browser-based Statistical Interface for Data Repositories.12102014data dataverse forschungsdaten statistics tools visualization TwoRavens: Analyse und Visualisierung tabellarischer DatenA User Guide to TwoRavens: An overview of features and capabilitieshttps://puma.ub.uni-stuttgart.de/bibtex/2183c9818318897cca829040887a931d9/diglezakisdiglezakis2018-11-19T09:03:25+01:00forschungsdaten statistics tools visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Vito D’Orazio" itemprop="url" href="/person/14290c728e7cafdf5f097f179ba61e5e1/author/0"><span itemprop="name">V. D’Orazio</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="James Honaker" itemprop="url" href="/person/14290c728e7cafdf5f097f179ba61e5e1/author/1"><span itemprop="name">J. Honaker</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"> </span>(<em><span>2016<meta content="2016" itemprop="datePublished"/></span></em>)</span>Mon Nov 19 09:03:25 CET 2018A User Guide to TwoRavens: An overview of features and capabilities2016forschungsdaten statistics tools visualization Visualizing the Provenance of Personal Data Using Comicshttps://puma.ub.uni-stuttgart.de/bibtex/2c0c0706face2cb6fbf52b8816c5b20ef/diglezakisdiglezakis2018-11-26T15:13:30+01:00comics metadata provenance visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Schreiber" itemprop="url" href="/person/1f13e70c0f4c79fbae5c07c808fb50b66/author/0"><span itemprop="name">A. Schreiber</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Regina Struminski" itemprop="url" href="/person/1f13e70c0f4c79fbae5c07c808fb50b66/author/1"><span itemprop="name">R. Struminski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Computers</span>, </em> </span>(<em><span>February 2018<meta content="February 2018" itemprop="datePublished"/></span></em>)</span>Mon Nov 26 15:13:30 CET 2018ComputersFebruar1Quantified Self and Personal InformaticsVisualizing the Provenance of Personal Data Using Comics72018comics metadata provenance visualization Personal health data is acquired, processed, stored, and accessed using a variety of different devices, applications, and services. These are often complex and highly connected. Therefore, use or misuse of the data is hard to detect for people, if they are not capable to understand the trace (i.e., the provenance) of that data. We present a visualization technique for personal health data provenance using comic strips. Each strip of the comic represents a certain activity, such as entering data using a smartphone application, storing or retrieving data on a cloud service, or generating a diagram from the data. The comic strips are generated automatically using recorded provenance graphs. The easy-to-understand comics enable all people to notice crucial points regarding their data such as, for example, privacy violations.Visualizing Provenance using Comicshttps://puma.ub.uni-stuttgart.de/bibtex/2bbc844f2ad063748b8959a4e3b0740ff/diglezakisdiglezakis2018-11-26T15:17:23+01:00comics metadata provenance visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Schreiber" itemprop="url" href="/person/1e7fe72028e0738dde630a67748dd23e9/author/0"><span itemprop="name">A. Schreiber</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Regina Struminski" itemprop="url" href="/person/1e7fe72028e0738dde630a67748dd23e9/author/1"><span itemprop="name">R. Struminski</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">9th USENIX Workshop on the Theory and Practice of Provenance (TaPP 2017)</span>, </em></span><em><span itemprop="publisher">USENIX Association</span>, </em>(<em><span>June 2017<meta content="June 2017" itemprop="datePublished"/></span></em>)</span>Mon Nov 26 15:17:23 CET 20189th USENIX Workshop on the Theory and Practice of Provenance (TaPP 2017)Proceedings of the 9th USENIX Workshop on the Theory and Practice of Provenance (TaPP 2017)JuniVisualizing Provenance using Comics2017comics metadata provenance visualization Understanding how a piece of data was produced, where it was stored, and by whom it was accessed, is crucial information in many processes. To understand the trace of data, the provenance of that data can be recorded and analyzed. But it is sometimes hard to understand this provenance information, especially for people who are not familiar with software or computer science. To close this gap, we present a visualization technique for data provenance using comics strips. Each strip of the comic represents an activity of the provenance graph, for example, using an app, storing or retrieving data on a cloud service, or generating a diagram. The comic strips are generated automatically using recorded provenance graphs. These provenance comics are intended to enable people to understand the provenance of their data and realize crucial points more easily.Provenance for the People: An HCI Perspective on the W3C PROV Standard Through an Online Gamehttps://puma.ub.uni-stuttgart.de/bibtex/29a146547cc27b3e14b56a66ecd61b118/diglezakisdiglezakis2018-11-27T10:10:51+01:00game human-computer-interaction provenance visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Khaled Bachour" itemprop="url" href="/person/1fd24a786e4e4f7c1e831bbdb40afeed4/author/0"><span itemprop="name">K. Bachour</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Richard Wetzel" itemprop="url" href="/person/1fd24a786e4e4f7c1e831bbdb40afeed4/author/1"><span itemprop="name">R. Wetzel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Martin Flintham" itemprop="url" href="/person/1fd24a786e4e4f7c1e831bbdb40afeed4/author/2"><span itemprop="name">M. Flintham</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Trung Dong Huynh" itemprop="url" href="/person/1fd24a786e4e4f7c1e831bbdb40afeed4/author/3"><span itemprop="name">T. Huynh</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tom Rodden" itemprop="url" href="/person/1fd24a786e4e4f7c1e831bbdb40afeed4/author/4"><span itemprop="name">T. Rodden</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Luc Moreau" itemprop="url" href="/person/1fd24a786e4e4f7c1e831bbdb40afeed4/author/5"><span itemprop="name">L. Moreau</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems</span>, </em></span><em>page <span itemprop="pagination">2437--2446</span>. </em><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM</span>, </em>(<em><span>2015<meta content="2015" itemprop="datePublished"/></span></em>)</span>Tue Nov 27 10:10:51 CET 2018New York, NY, USAProceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems2437--2446CHI '15Provenance for the People: An HCI Perspective on the W3C PROV Standard Through an Online Game2015game human-computer-interaction provenance visualization A Framework for Provenance Analysis and Visualizationhttps://puma.ub.uni-stuttgart.de/bibtex/2cdc5ccf1fbbde6134160e2fd126e5b6f/diglezakisdiglezakis2018-11-27T11:46:18+01:00provenance visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Weiner Oliveira" itemprop="url" href="/person/176a03ad792f1fceda5c8489067d72d0b/author/0"><span itemprop="name">W. Oliveira</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lenitta M. Ambrósio" itemprop="url" href="/person/176a03ad792f1fceda5c8489067d72d0b/author/1"><span itemprop="name">L. Ambrósio</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Regina Braga" itemprop="url" href="/person/176a03ad792f1fceda5c8489067d72d0b/author/2"><span itemprop="name">R. Braga</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Victor Ströele" itemprop="url" href="/person/176a03ad792f1fceda5c8489067d72d0b/author/3"><span itemprop="name">V. Ströele</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="José Maria David" itemprop="url" href="/person/176a03ad792f1fceda5c8489067d72d0b/author/4"><span itemprop="name">J. David</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Fernanda Campos" itemprop="url" href="/person/176a03ad792f1fceda5c8489067d72d0b/author/5"><span itemprop="name">F. Campos</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Procedia Computer Science</span>, </em> </span>(<em><span>2017<meta content="2017" itemprop="datePublished"/></span></em>)<em>International Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland.</em></span>Tue Nov 27 11:46:18 CET 2018Procedia Computer ScienceInternational Conference on Computational Science, ICCS 2017, 12-14 June 2017, Zurich, Switzerland1592 - 1601A Framework for Provenance Analysis and Visualization1082017provenance visualization Data provenance is a fundamental concept in scientific experimentation. However, for their proper understanding and use, efficient and user-friendly mechanisms are needed. Research in software visualization, ontologies and complex networks can help in this process. This paper presents a framework to assist in the understanding and use of data provenance using visualization techniques, ontologies and complex networks. The framework capture the provenance data and generates new information using ontologies and provenance graph analysis. The graph is analyzed through complex networks techniques and provide some metrics to help in each node analyzes. The visualization presents and highlights the inferences and results. The framework was used in the E-SECO scientific ecosystem to support the scientific experimentation.Provenance map orbiter: Interactive exploration of large provenance graphs.https://puma.ub.uni-stuttgart.de/bibtex/2263489bb008879e8aee40546ffe85a18/diglezakisdiglezakis2018-11-27T11:50:43+01:00metadata provenance tools visualization <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Macko" itemprop="url" href="/person/1942c30c84f70ae3ff687864a277e15cd/author/0"><span itemprop="name">P. Macko</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Margo Seltzer" itemprop="url" href="/person/1942c30c84f70ae3ff687864a277e15cd/author/1"><span itemprop="name">M. Seltzer</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">TaPP</span>, </em></span>(<em><span>2011<meta content="2011" itemprop="datePublished"/></span></em>)</span>Tue Nov 27 11:50:43 CET 2018TaPPProvenance map orbiter: Interactive exploration of large provenance graphs.2011metadata provenance tools visualization DATA PROVENANCE VISUALIZATION METHODOLOGIEShttps://puma.ub.uni-stuttgart.de/bibtex/2d14efae20c64ccfa62ac860648e79734/diglezakisdiglezakis2023-09-22T15:44:04+02:00metadata provenance visualization <meta content="thesis" itemprop="educationalUse"/><span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ilkay Melek Yazıcı" itemprop="url" href="/person/1ae056def168c423453394fdd098ea1c8/author/0"><span itemprop="name">I. Yazıcı</span></a></span></span>. </span><span class="additional-entrytype-information"><em>YILDIZ TECHNICAL UNIVERSITY, </em>(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Fri Sep 22 15:44:04 CEST 2023DATA PROVENANCE VISUALIZATION METHODOLOGIES2023metadata provenance visualization