Faculty and Staff

Background & Objective:
Over the past several decades, systematic reviews have become a major part of the biomedical research literature landscape. While systematic reviews were originally developed for medicine and its related fields, they are now published in other disciplines. Our initial goal was to broadly investigate and describe the non-health sciences subject areas and disciplines that are publishing systematic reviews. Specifically, our research questions were,“What disciplines outside of the health sciences are adopting systematic reviews as a research method?” and “What implications may this have for health sciences librarianship?” Based on our initial findings, we will propose avenues for future research.

Methods & Discussion:
We conducted a search in the Scopus database to serve as a representative sample of the research literature. We searched for the phrase “systematic review*” in the article title or abstract, and limited the results to review articles from journals. We filtered out articles published in health sciences disciplines using the Scopus subject categories, and examined the articles that remained. The resulting set of titles was screened by two independent reviewers in a stepwise fashion. First we read the titles, then the abstracts, then the full text of remaining articles to determine if each was a systematic review and addressed a topic outside of the health sciences. We reconciled any differences for citations on which there was not initial consensus between reviewers. Lastly, we examined each remaining article to categorize its subject area or discipline. Our initial search included a number of systematic reviews outside the health science disciplines, and will yield data that has implications for librarians in the health sciences and in disciplines outside the health sciences field.

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.