Published January 16, 2025 | Version v1
Figure Open

Brick by Brick: A Human-Centered Approach to Effective Dashboard Design for Smart Building and Energy Management

Description

This online appendix offers the interview guide, evaluation guide, ideation process, wireframes, and screenshots of the final prototype for my Master's thesis at Vrije Universiteit Amsterdam. If there are any questions feel free to contact me at g.l.m.noor@student.vu.nl. 

 

ABSTRACT

Dashboards play a crucial role in data-driven decision-making and monitoring across various industries, including non-profits, and service organizations. Despite the prevalence of dashboards, there is a lack of research on effective and applicable dashboard design, particularly for smart building and energy management. Every organization or project brings unique visual design challenges that often do not fit ready-made dashboarding tools. At Arnhems Buiten, a HEDGE-IoT pilot site, a specialized dashboard is being developed to help monitor various Internet of Things devices. This research adopts a human-centered approach to effective dashboard design. Using this approach, I have conducted four stakeholder interviews with a project manager, building owner, property manager, and director to identify pain points, key needs, and objectives. Insights from user interviews guided the development of an initial concept that was further refined into a high-fidelity prototype. This prototype was then evaluated with two stakeholders using the think-aloud technique. Three tasks were conducted to assess design choices, user satisfaction, and usability. The findings demonstrate that effective dashboard design extends beyond user interface patterns and user experience principles, highlighting the importance of storytelling and designing for predictive analytics. These results offer valuable implications for designing dashboards for smart building and energy management needs and for improving the visualization of predictive analytics.

Files

Online_Appendix.pdf

Files (14.1 MB)

Name Size Download all
md5:655b4518be90349cf89daa4d21191acf
14.1 MB Preview Download

Additional details