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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.
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Advances in Human Error, Reliability, Resilience, and Performance. AHFE 2018. Advances in Intelligent Systems and Computing
In the fight against hunger, Food Banks must routinely make strategic distribution decisions under uncertain supply (donations) and demand. One of the challenges facing the decision makers is that they tend to rely heavily on their prior experiences to make decisions, a phenomenon called cognitive bias. This preliminary study seeks to address cognitive bias through a visual analytics approach in the decision-making process. Using certain food bank data, interactive dashboards were prepared as an alternative to the customary spreadsheet format. A preliminary study was conducted to evaluate the effectiveness of the dashboard and results indicated dashboards reduced the amount of confirmation bias.
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- Award ID(s):
- 1718672
- 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
