Faculty and Staff

Objectives: While PhD dissertations are typically accessible as part of a university library’s general collection, or as content within a proprietary database, many other terminal degree projects remain invisible and inaccessible to a greater audience. This poster will describe the development and creation of a digital repository collection containing doctor of nursing practice (DNP) student’s final projects.

Methods: The “Doctor of Nursing Practice (DNP) Final Projects Collection” was created over the course of one semester and included initial discussions with program faculty and administrators, the creation of a student consent form, the development of a process for adding student work to the repository collection, and a presentation to graduating students. This poster will describe the process in more detail, discuss benefits and challenges, as well as highlight the considerations to keep in mind when developing and creating a digital collection of student work. Additionally, best practices and lessons learned will also be described to provide valuable information to others considering creating this type of collection at their own institution.

Results: At the end of the first semester of implementation, twenty student projects existed in our public collection. On the whole, both faculty and students were pleased to have a collection highlighting the work being done in their program. Valuable lessons were learned that can be applied in the next semester of implementation. Specifically, metadata consistency was an issue during the initial uploading process. Gaining select faculty and student buy-in by allaying concerns related to some student’s wanting to publish in a peer-reviewed journal on the topic of their final project remains vital.

Conclusion: Creating open access collections of student applied final projects or capstone projects allows for greater visibility of this type of often overlooked student scholarship. Specifically, the final projects showcased can now be found and accessed by potential employers, researchers, other schools, and other DNP students. In many cases these final projects have applied real-world impact related to answering clinical questions or patient care that should be shared with the world.

The Future of Wastewater Sensing workshop is part of a collaboration between Arizona State University Center for Nanotechnology in Society in the School for the Future of Innovation in Society, the Biodesign Institute’s Center for Environmental Security, LC Nano, and the Nano-enabled Water Treatment (NEWT) Systems NSF Engineering Research Center. The Future of Wastewater Sensing workshop explores how technologies for studying, monitoring, and mining wastewater and sewage sludge might develop in the future, and what consequences may ensue for public health, law enforcement, private industry, regulations and society at large. The workshop pays particular attention to how wastewater sensing (and accompanying research, technologies, and applications) can be innovated, regulated, and used to maximize societal benefit and minimize the risk of adverse outcomes, when addressing critical social and environmental challenges.

Accessibility is increasingly used as a metric when evaluating changes to public transport systems. Transit travel times contain variation depending on when one departs relative to when a transit vehicle arrives, and how well transfers are coordinated given a particular timetable. In addition, there is necessarily uncertainty in the value of the accessibility metric during sketch planning processes, due to scenarios which are underspecified because detailed schedule information is not yet available. This article presents a method to extend the concept of "reliable" accessibility to transit to address the first issue, and create confidence intervals and hypothesis tests to address the second.

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.