TY - JOUR
T1 - Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases
AU - Htun, Nyi Nyi
AU - Rojo, Diego
AU - Ooge, Jeroen
AU - De Croon, Robin
AU - Kasimati, Aikaterini
AU - Verbert, Katrien
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - data analytics
KW - decision support systems
KW - interactive visualisations
KW - precision agriculture
KW - user evaluation
UR - http://www.scopus.com/inward/record.url?scp=85138054451&partnerID=8YFLogxK
U2 - 10.3390/agriculture12071027
DO - 10.3390/agriculture12071027
M3 - Article
AN - SCOPUS:85138054451
SN - 2077-0472
VL - 12
JO - Agriculture (Switzerland)
JF - Agriculture (Switzerland)
IS - 7
M1 - 1027
ER -