No abstract

Food insecurity is a serious problem and non-profit humanitarian relief agencies such as foodbanks play a significant role in fighting hunger. Each foodbank collects a lot of data every day. However, the complexity of the data collected from the relief operations provide a challenge for the foodbank managers to make informed decisions. Working with a local foodbank, we have developed dashboards that provide visualized information and allow users to interact with the tool. The effectiveness of the dashboard interactivity was evaluated in an empirical study. Results revealed that different types of interactivity had an impact on user performance. Findings from this research can help designers improve their dashboard design.

Abstract:Hunger relief is one of the major needs during humanitarian emergencies. It presents significant challenges to aid organizations trying to manage data, information and knowledge about the situation or event. Food banks receive donations from a variety of sources to meet their demand. The distribution of donated food to meet the unmet hunger needs is a critical issue faced by the food banks across the nation. This paper presents a methodology to apply interactive dashboards to a food bank's decision making process. The first step of this research focuses on understanding the existing decision making process of a food bank. Data from a local food bank was used for this research. Data mining tools were employed to develop predictive models for food bank decision making. Appropriate visualization techniques were identified that can be used to visualize the data mining results. An interactive dashboard was developed and evaluated to enable effective decision making. The results indicated that interactive dashboards were highly effective as compared to the traditional data retrieval system for decision making in food bank operations. The new methodology can be extended to other food banks and hunger-relief organizations which deal with big data.