Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards
Exploring and analyzing data using visualizations is at the heart of many decision-making tasks. Typically, people perform visual data analysis using mouse and touch interactions. While such interactions are often easy to use, they can be inadequate for users to express complex information and may r...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9303381/ |
| _version_ | 1818988561217617920 |
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| author | Imran Chowdhury Abdul Moeid Enamul Hoque Muhammad Ashad Kabir Md. Sabir Hossain Mohammad Mainul Islam |
| author_facet | Imran Chowdhury Abdul Moeid Enamul Hoque Muhammad Ashad Kabir Md. Sabir Hossain Mohammad Mainul Islam |
| author_sort | Imran Chowdhury |
| collection | DOAJ |
| description | Exploring and analyzing data using visualizations is at the heart of many decision-making tasks. Typically, people perform visual data analysis using mouse and touch interactions. While such interactions are often easy to use, they can be inadequate for users to express complex information and may require many steps to complete a task. Recently natural language interaction has emerged as a promising technique for supporting exploration with visualization, as the user can express a complex analytical question more easily. In this paper, we investigate how to synergistically combine language and mouse-based direct manipulations so that the weakness of one modality can be complemented by the other. To this end, we have developed a novel system, named Multimodal Interactions System for Visual Analysis (MIVA), that allows user to provide input using both natural language (e.g., through speech) and direct manipulation (e.g., through mouse or touch) and presents the answer accordingly. To answer the current question in the context of past interactions, the system incorporates previous utterances and direct manipulations made by the user within a finite-state model. The uniqueness of our approach is that unlike most previous approaches which typically support multimodal interactions with a single visualization, MIVA enables multimodal interactions with multiple coordinated visualizations of a dashboard that visually summarizes a dataset. We tested MIVA's applicability on several dashboards including a COVID-19 dashboard that visualizes coronavirus cases around the globe. We further empirically evaluated our system through a user study with twenty participants. The results of our study revealed that MIVA system enhances the flow of visual analysis by enabling fluid, iterative exploration and refinement of data in a dashboard with multiple-coordinated views. |
| first_indexed | 2024-12-20T19:24:32Z |
| format | Article |
| id | doaj.art-f23951dccd7a4a03a782e561ec423404 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T19:24:32Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f23951dccd7a4a03a782e561ec4234042022-12-21T19:28:55ZengIEEEIEEE Access2169-35362021-01-019607110.1109/ACCESS.2020.30466239303381Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With DashboardsImran Chowdhury0Abdul Moeid1Enamul Hoque2https://orcid.org/0000-0002-9789-6645Muhammad Ashad Kabir3https://orcid.org/0000-0002-6798-6535Md. Sabir Hossain4Mohammad Mainul Islam5Department of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chittagong, BangladeshDepartment of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chittagong, BangladeshSchool of Information Technology, York University, Toronto, ON, CanadaSchool of Computing and Mathematics, Charles Sturt University, Bathurst, NSW, AustraliaDepartment of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chittagong, BangladeshVerizon Media Australia, Sydney, NSW, AustraliaExploring and analyzing data using visualizations is at the heart of many decision-making tasks. Typically, people perform visual data analysis using mouse and touch interactions. While such interactions are often easy to use, they can be inadequate for users to express complex information and may require many steps to complete a task. Recently natural language interaction has emerged as a promising technique for supporting exploration with visualization, as the user can express a complex analytical question more easily. In this paper, we investigate how to synergistically combine language and mouse-based direct manipulations so that the weakness of one modality can be complemented by the other. To this end, we have developed a novel system, named Multimodal Interactions System for Visual Analysis (MIVA), that allows user to provide input using both natural language (e.g., through speech) and direct manipulation (e.g., through mouse or touch) and presents the answer accordingly. To answer the current question in the context of past interactions, the system incorporates previous utterances and direct manipulations made by the user within a finite-state model. The uniqueness of our approach is that unlike most previous approaches which typically support multimodal interactions with a single visualization, MIVA enables multimodal interactions with multiple coordinated visualizations of a dashboard that visually summarizes a dataset. We tested MIVA's applicability on several dashboards including a COVID-19 dashboard that visualizes coronavirus cases around the globe. We further empirically evaluated our system through a user study with twenty participants. The results of our study revealed that MIVA system enhances the flow of visual analysis by enabling fluid, iterative exploration and refinement of data in a dashboard with multiple-coordinated views.https://ieeexplore.ieee.org/document/9303381/Direct manipulationnatural language interfacemultimodal interactionmultiple-coordinated views |
| spellingShingle | Imran Chowdhury Abdul Moeid Enamul Hoque Muhammad Ashad Kabir Md. Sabir Hossain Mohammad Mainul Islam Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards IEEE Access Direct manipulation natural language interface multimodal interaction multiple-coordinated views |
| title | Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards |
| title_full | Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards |
| title_fullStr | Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards |
| title_full_unstemmed | Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards |
| title_short | Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards |
| title_sort | designing and evaluating multimodal interactions for facilitating visual analysis with dashboards |
| topic | Direct manipulation natural language interface multimodal interaction multiple-coordinated views |
| url | https://ieeexplore.ieee.org/document/9303381/ |
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