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Implementing Visual Analytics Pipelines with Simulation Data

  • Visual analytics has been widely studied in the past decade both in academia and industry to improve data exploration, minimize the overall cost, and improve data analysis. In this chapter, we explore the idea of visual analytics in the context of simulation data. This would then provide us with the capability to not only explore our data visually but also to apply machine learning models in order to answer high-level questions with respect to scheduling, choosing optimal simulation parameters, finding correlations, etc. More specifically, we examine state-of-the-art tools to be able to perform these above-mentioned tasks. Further, to test and validate our methodology we followed the human-centered design process to build a prototype tool called ViDAS (Visual Data Analytics of Simulated Data). Our preliminary evaluation study illustrates the intuitiveness and ease-of-use of our approach with regards to visual analysis of simulated data.

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Author:Taimur Khan, Syed Samad Shakeel, Afzal Gul, Hamza Masud, Achim Ebert
URN (permanent link):urn:nbn:de:hbz:386-kluedo-64366
Parent Title (English):Software Usability
Publisher:INTECHOPEN LIMITED
Place of publication:England and Wales
Document Type:Article
Language of publication:English
Publication Date:2021/03/12
Year of Publication:2021
Publishing Institute:Technische Universität Kaiserslautern
Date of the Publication (Server):2021/06/28
Tag:visual analytics, machine learning, interaction, user experience, assistive technologies
Number of page:25
Source:https://www.intechopen.com/online-first/implementing-visual-analytics-pipelines-with-simulation-data
Faculties / Organisational entities:Fachbereich Informatik
CCS-Classification (computer science):H. Information Systems / H.5 INFORMATION INTERFACES AND PRESENTATION (e.g., HCI) (I.7)
DDC-Cassification:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):Zweitveröffentlichung