Food insecurity is defined as an individual or household’s inability or limited access to safe and nutritious food that every person in the household need for an active, healthy life. In this research, we apply visual analytics, the integration of data analytics and interactive visualization, to provide evidence-based decision-making for a local food bank to better understand the people and communities in its service area and improve the reach and impact of the food bank. We have identified the indicators of the need, rates of usage, and other factors related to the general accessibility of the food bank and its programs. Interactive dashboards were developed to allow decision-makers of the food bank to combine their field knowledge with the computing power to make evidence-based informed decisions in complex hunger relief operations.
- Award ID(s):
- 1718672
- NSF-PAR ID:
- 10066342
- Date Published:
- Journal Name:
- A Visual Analytics Approach to Combat Confirmation Bias for a Local Food Bank
- Volume:
- 778
- Page Range / eLocation ID:
- 13-23
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/https://doi.org/10.1007/978-3-319-94391-6_2
