A survey of the state of the practice for research software in the United States

Research software is a critical component of contemporary scholarship. Yet, most research software is developed and managed in ways that are at odds with its long-term sustainability. This paper presents findings from a survey of 1,149 researchers, primarily from the United States, about sustainability challenges they face in developing and using research software. Some of our key findings include a repeated need for more opportunities and time for developers of research software to receive training. These training needs cross the software lifecycle and various types of tools. We also identified the recurring need for better models of funding research software and for providing credit to those who develop the software so they can advance in their careers. The results of this survey will help inform future infrastructure and service support for software developers and users, as well as national research policy aimed at increasing the sustainability of research software.

Investigating the Impact of Usability on Energy Efficiency of Web-based Personal Health Records

Usability plays an important role in eHealth applications for their widespread adoption. These software systems have been studied in depth in the literature from this perspective. However, the energy consumption of information systems in the eHealth domain lacks comprehensive research. In this paper, the relationship between the energy consumption of the main components of a PC and the usability evaluations of graphical user interfaces (GUI) were studied in client applications. For this purpose, personal health records (PHR) were used as a case study. A set of 4 web-based PHRs were evaluated with the performance of 20 common tasks in the aforementioned systems. The usability evaluations were carried out by 4 experts. A total of 8 heuristics particularly designed for electronic health record systems and based on the Nielsen usability heuristics were employed. The instantaneous energy values of the power supply and the monitor were collected with an energy consumption measuring equipment. As a result, the following significant correlations were found. In NoMoreClipboard between the Memory heuristic and the power supply (r_s = 0.495, p = 0.044), and the Minimalist heuristic and the monitor (r_s = - 0.513, p = 0.035). In PatientsLikeMe between the Minimalist heuristic and the power supply (r_s = - 0.479, p = 0.083), as well as in the Error heuristic and the power supply (r_s = - 0.638, p = 0.014). Finally, in Health Companion between the Match heuristic and the power supply (r_s = - 0.481, p = 0.043), and the Error heuristic and the power supply again (r_s = - 0.602, p = 0.008). Apart from that, the tasks were divided into those with excellent and fair usability. Those tasks with high usability scores were evaluated to detect whether they also had low energy consumption during task performance. Significant differences were found in PatientsLikeMe with respect to the Error heuristic and the power supply (212.39 ± 18.85W). Significant differences were also found in Health Companion with respect to the Match heuristic and the power supply (199.91 ± 7.19W). The results were discussed to reveal the fundamentals of how implementing usability can impact on energy costs when running client applications.

Towards computational reproducibility: researcher perspectives on the use and sharing of software

Research software, which includes both source code and executables used as part of the research process, presents a significant challenge for efforts aimed at ensuring reproducibility. In order to inform such efforts, we conducted a survey to better understand the characteristics of research software as well as how it is created, used, and shared by researchers. Based on the responses of 215 participants, representing a range of research disciplines, we found that researchers create, use, and share software in a wide variety of forms for a wide variety of purposes, including data collection, data analysis, data visualization, data cleaning and organization, and automation. More participants indicated that they use open source software than commercial software. While a relatively small number of programming languages (e.g., Python, R, JavaScript, C++, MATLAB) are used by a large number, there is a long tail of languages used by relatively few. Between-group comparisons revealed that significantly more participants from computer science write source code and create executables than participants from other disciplines. Differences between researchers from computer science and other disciplines related to the knowledge of best practices of software creation and sharing were not statistically significant. While many participants indicated that they draw a distinction between the sharing and preservation of software, related practices and perceptions were often not aligned with those of the broader scholarly communications community.