O ver the past few years there has been increased interest in open data access. However, data retrieval represents a major bottleneck for many organizations, including funding agencies such as the US National Science Foundation (NSF). This is due to the multimodal, high-volume nature of funding data that is often disconnected and diffuse. In effect, deriving meaningful insights from an existing funding portfolio is challenging. Issues arise not only in data representation, but also in the way that data is accessed and communicated to the end user. Providing multiple ways to visualize data, enabling users to "see" relationships, gaps, or other connections, could lead to new insights that facilitate a better overview of existing funded research and more informed decision making for future funding.As with any federal funding agency, there is complexity of data within NSF's portfolio, and it increases continuously as new proposals get submitted, reviewed, and funded or declined. NSF awards approximately 11,000 grants a year with an average performance duration of three years. The NSF staff includes 1,400 career employees, 200 scientists from research institutions on temporary duty (rotators), and 450 contract workers and staff (data obtained from www.nsf.gov). Given the relatively high percentage of turnover among temporary NSF staff, there are always new individuals that need to be trained on funding processes. It is crucial for them to familiarize themselves quickly with the funding portfolio. For example, science assistants are typically hired for a period of two years and are expected to help program of cers with queries on the data using various criteria. Because information increases continuously, and the staff need to make decisions in a short period of time, there is a need to make the existing portfolio easy to access and understand.In this environment, however, the gap between data visualization and actual insights can be difcult to bridge. To address this problem, we developed Deep Insights Anytime, Anywhere (DIA2), a data-mining and Web-based platform that uses metadata about funding information from the NSF to produce interactive data visualizations. 1 DIA2 provides an overview in an easy-to-understand format, allowing users to search, view, and analyze the NSF funding portfolio.This article presents an assessment of DIA2's usability. We attempted to evaluate its perceived utility among the target user group. Speci cally, we inquired whether and how the system leads to insights that can facilitate further decision making, such as estimates about the impact of speci c research projects. Our results show that DIA2 has good usability. Furthermore, participants identied several indicators of impact as a result of the visualizations that can be realized through DIA2.
DIA2During the design and implementation of DIA2, we followed an iterative, user-centered design process. 2 To determine DIA2 requirements, we