ASU Scholarship Showcase

Students in Organic Chemistry for Majors were required to write a paper as the culminating course assignment. Prior to completing this assignment, students could attend a library instruction session covering relevant databases and resources. Upon submission of their papers, bibliographies from 53 students were collected. Calculations were made to attempt a holistic account of costs associated with completing the assignment. Factors such as the cost of journals, databases, and librarian time were all included in the overall cost estimate, totalling $7,189.22 for this single assignment.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.