Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases
Decision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limits their flexibility and portability. They also ra...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Agriculture |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0472/12/7/1027 |
| _version_ | 1797407882008854528 |
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| author | Nyi-Nyi Htun Diego Rojo Jeroen Ooge Robin De Croon Aikaterini Kasimati Katrien Verbert |
| author_facet | Nyi-Nyi Htun Diego Rojo Jeroen Ooge Robin De Croon Aikaterini Kasimati Katrien Verbert |
| author_sort | Nyi-Nyi Htun |
| collection | DOAJ |
| description | Decision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limits their flexibility and portability. They also rarely provide interactivity, visualise uncertainty and are evaluated with end-users. To address these gaps, we developed six web-based visual-assisted DSSs for various agricultural use cases, including biological efficacy correlation analysis, water stress and irrigation requirement analysis, product price prediction, etc. We then evaluated our DSSs with domain experts, focusing on usability, workload, acceptance and trust. Results showed that our systems were easy to use and understand, and participants perceived them as highly performant, even though they required a slightly high mental demand, temporal demand and effort. We also published the source code of our proposed systems so that they can be re-used or adapted by the agricultural community. |
| first_indexed | 2024-03-09T03:49:09Z |
| format | Article |
| id | doaj.art-19d8a8df9c6a45be95b92351fed22331 |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-09T03:49:09Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-19d8a8df9c6a45be95b92351fed223312023-12-03T14:29:22ZengMDPI AGAgriculture2077-04722022-07-01127102710.3390/agriculture12071027Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use CasesNyi-Nyi Htun0Diego Rojo1Jeroen Ooge2Robin De Croon3Aikaterini Kasimati4Katrien Verbert5Department of Computer Science, Celestijnenlaan 200A, 3001 Leuven, BelgiumDepartment of Computer Science, Celestijnenlaan 200A, 3001 Leuven, BelgiumDepartment of Computer Science, Celestijnenlaan 200A, 3001 Leuven, BelgiumDepartment of Computer Science, Celestijnenlaan 200A, 3001 Leuven, BelgiumDepartment of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, GreeceDepartment of Computer Science, Celestijnenlaan 200A, 3001 Leuven, BelgiumDecision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limits their flexibility and portability. They also rarely provide interactivity, visualise uncertainty and are evaluated with end-users. To address these gaps, we developed six web-based visual-assisted DSSs for various agricultural use cases, including biological efficacy correlation analysis, water stress and irrigation requirement analysis, product price prediction, etc. We then evaluated our DSSs with domain experts, focusing on usability, workload, acceptance and trust. Results showed that our systems were easy to use and understand, and participants perceived them as highly performant, even though they required a slightly high mental demand, temporal demand and effort. We also published the source code of our proposed systems so that they can be re-used or adapted by the agricultural community.https://www.mdpi.com/2077-0472/12/7/1027precision agriculturedata analyticsinteractive visualisationsdecision support systemsuser evaluation |
| spellingShingle | Nyi-Nyi Htun Diego Rojo Jeroen Ooge Robin De Croon Aikaterini Kasimati Katrien Verbert Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases Agriculture precision agriculture data analytics interactive visualisations decision support systems user evaluation |
| title | Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases |
| title_full | Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases |
| title_fullStr | Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases |
| title_full_unstemmed | Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases |
| title_short | Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases |
| title_sort | developing visual assisted decision support systems across diverse agricultural use cases |
| topic | precision agriculture data analytics interactive visualisations decision support systems user evaluation |
| url | https://www.mdpi.com/2077-0472/12/7/1027 |
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