User Stories-Based Requirement Elicitation for Data Visualization to Support Decision Making in Water Resource Management at Bago River Basin

JOURNAL OF DISASTER RESEARCH(2020)

引用 1|浏览8
暂无评分
摘要
Understanding of system requirements that satisfy end users' needs is fundamental of system development, yet challenging when end users are unable to address their needs explicitly. Although a number of scholars have been designing and applying requirement elicitation techniques, there is a research gap in Spatial Decision Support System (SDSS) with Web-based Geographical Information System (Web-GIS) in water resource management for disaster risk reduction. The gap addresses especially design elicitation techniques and their performances 1) to understand data types used for decision making, 2) set timing for sharing the data to accomplish end users' tasks, and 3) compile the data to be represented so as to facilitate end users' decision making. This study therefore designed a requirement elicitation technique by advancing User Story Mapping (USM) and validated through a workshop using mock-up system interface with potential end users who are in charge of water resource management in Myanmar's Bago River Basin. Through the research it could be validated that the user stories-based approach enabled end users to decompose their operation activities into tasks. It also allowed them to link to necessary data with visual image for facilitating their task accomplishments and decision making for water resource management. It was revealed that the benefits of using the designed approach are not only just to summarize necessary data and information for end users' decision making but also to encourage them to proactively consider data utilization into their operations. For further development of the requirement elicitation to understand end users needs, insights and recommendations for the proposed technique designing and conducting of the workshop were obtained.
更多
查看译文
关键词
requirement elicitation,decision making,water resource management,disaster,Myanmar
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要