Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards
Information dashboards are everywhere. They support knowledge discovery in a huge variety of contexts and domains. Although powerful, these tools can be complex, not only for the end-users but also for developers and designers. Information dashboards encode complex datasets into different visual mar...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-03-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/10/7/2306 |
| _version_ | 1797626481161011200 |
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| author | Andrea Vázquez-Ingelmo Francisco José García-Peñalvo Roberto Therón Miguel Ángel Conde |
| author_facet | Andrea Vázquez-Ingelmo Francisco José García-Peñalvo Roberto Therón Miguel Ángel Conde |
| author_sort | Andrea Vázquez-Ingelmo |
| collection | DOAJ |
| description | Information dashboards are everywhere. They support knowledge discovery in a huge variety of contexts and domains. Although powerful, these tools can be complex, not only for the end-users but also for developers and designers. Information dashboards encode complex datasets into different visual marks to ease knowledge discovery. Choosing a wrong design could compromise the entire dashboard’s effectiveness, selecting the appropriate encoding or configuration for each potential context, user, or data domain is a crucial task. For these reasons, there is a necessity to automatize the recommendation of visualizations and dashboard configurations to deliver tools adapted to their context. Recommendations can be based on different aspects, such as user characteristics, the data domain, or the goals and tasks that will be achieved or carried out through the visualizations. This work presents a dashboard meta-model that abstracts all these factors and the integration of a visualization task taxonomy to account for the different actions that can be performed with information dashboards. This meta-model has been used to design a domain specific language to specify dashboards requirements in a structured way. The ultimate goal is to obtain a dashboard generation pipeline to deliver dashboards adapted to any context, such as the educational context, in which a lot of data are generated, and there are several actors involved (students, teachers, managers, etc.) that would want to reach different insights regarding their learning performance or learning methodologies. |
| first_indexed | 2024-03-11T10:11:01Z |
| format | Article |
| id | doaj.art-92952c9e56c54035b428e05817f6df95 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T10:11:01Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-92952c9e56c54035b428e05817f6df952023-11-16T14:30:53ZengMDPI AGApplied Sciences2076-34172020-03-01107230610.3390/app10072306Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information DashboardsAndrea Vázquez-Ingelmo0Francisco José García-Peñalvo1Roberto Therón2Miguel Ángel Conde3GRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainGRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainVisUSAL, GRIAL Research Group, Computer Science Department, University of Salamanca, 37008 Salamanca, SpainDepartment of Mechanics, Computer Science and Aerospace Engineering, University of León, 24007 León, SpainInformation dashboards are everywhere. They support knowledge discovery in a huge variety of contexts and domains. Although powerful, these tools can be complex, not only for the end-users but also for developers and designers. Information dashboards encode complex datasets into different visual marks to ease knowledge discovery. Choosing a wrong design could compromise the entire dashboard’s effectiveness, selecting the appropriate encoding or configuration for each potential context, user, or data domain is a crucial task. For these reasons, there is a necessity to automatize the recommendation of visualizations and dashboard configurations to deliver tools adapted to their context. Recommendations can be based on different aspects, such as user characteristics, the data domain, or the goals and tasks that will be achieved or carried out through the visualizations. This work presents a dashboard meta-model that abstracts all these factors and the integration of a visualization task taxonomy to account for the different actions that can be performed with information dashboards. This meta-model has been used to design a domain specific language to specify dashboards requirements in a structured way. The ultimate goal is to obtain a dashboard generation pipeline to deliver dashboards adapted to any context, such as the educational context, in which a lot of data are generated, and there are several actors involved (students, teachers, managers, etc.) that would want to reach different insights regarding their learning performance or learning methodologies.https://www.mdpi.com/2076-3417/10/7/2306information dashboardsmetamodelingvisualization goalsvisualization tasksdata visualizationeducational dashboards |
| spellingShingle | Andrea Vázquez-Ingelmo Francisco José García-Peñalvo Roberto Therón Miguel Ángel Conde Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards Applied Sciences information dashboards metamodeling visualization goals visualization tasks data visualization educational dashboards |
| title | Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards |
| title_full | Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards |
| title_fullStr | Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards |
| title_full_unstemmed | Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards |
| title_short | Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards |
| title_sort | representing data visualization goals and tasks through meta modeling to tailor information dashboards |
| topic | information dashboards metamodeling visualization goals visualization tasks data visualization educational dashboards |
| url | https://www.mdpi.com/2076-3417/10/7/2306 |
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