This paper describes the Pegasus framework that can be used to map complex scientific workflows onto distributed resources. Pegasus enables users to represent the workflows at an abstract level without needing to worry about the particulars of the target execution systems. The paper describes general issues in mapping applications and the functionality of Pegasus. We present the results of improving application performance through workflow restructuring which clusters multiple tasks in a workflow into single entities. A real-life astronomy application is used as the basis for the study.

Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.

This study explores community college student mental health by comparing the responses of California community college and traditional university students on the American College Health Association–National College Health Assessment II (ACHA-NCHA II). Using MANOVA, we compared community college and traditional university students, examining overall group differences on four multicomponent questions; pairwise comparisons also were used to examine individual survey items. This study found significant differences in reported mental health issues and needs between the students. More specifically, a pattern of difference in psychological concerns, available resources, and resource utilization emerged, with community college students having more severe psychological concerns and less institutional mental health resources than traditional university students. Findings suggest that both community colleges and traditional universities would benefit from increased mental health resources, though community colleges are particularly in need.

Software is increasingly essential in most research, and much of this software is developed specifically for and during research. To make this research software findable, accessible, interoperable, and reusable (FAIR), we need to define exactly what FAIR means for research software and acknowledge that software is a living and complex object for which it is impossible to propose one solution that fits all software.