Track 1 Paper: Good Usability Practices in Scientific Software Development

Queiroz, Francisco; Silva, Raniere; Miller, Jonah; Brockhauser, Sándor; Fangohr, Hans

doi:10.6084/m9.figshare.5331814.v3

Cited by 3 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…WSSSPE5.1 included the presentation of four 12-minute talks based on accepted papers [10,11,12,13], and seven 6-minute lightning talks [14,15,16,17,18,19,20].…”

Section: Presentationsmentioning

confidence: 99%

The State of Sustainable Research Software: Learning from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1)

Druskat

Haines

Jay

et al. 2019

JORS

View full text Add to dashboard Cite

This article summarizes motivations, organization, and activities of the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1) held in Manchester, UK in September 2017. The WSSSPE series promotes sustainable research software by positively impacting principles and best practices, careers, learning, and credit. This article discusses the Code of Conduct, idea papers, position papers, experience papers, demos, and lightning talks presented during the workshop. The main part of the article discusses the speed-blogging groups that formed during the meeting, along with the outputs of those sessions.

show abstract

“…WSSSPE5.1 included the presentation of four 12-minute talks based on accepted papers [10,11,12,13], and seven 6-minute lightning talks [14,15,16,17,18,19,20].…”

Section: Presentationsmentioning

confidence: 99%

The State of Sustainable Research Software: Learning from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1)

Druskat

Haines

Jay

et al. 2019

JORS

View full text Add to dashboard Cite

show abstract

“…The presence of a graphical user interface (GUI) is sometimes seen as an indication of usability (Remy, 2005;Rubin et al, 2018). However, a GUI does not necessarily make software more user-friendly, almost always limits flexibility, increases the programming effort, and makes reproducibility of results and workflows harder or even unfeasible (Queiroz et al, 2017). Also note that in recent years pow-erful tools emerged in data science to represent data along with code snippets, documentation and results in interactive computational notebooks provided by Jupyter (Perkel, 2018;Beg et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

GSTools v1.3: a toolbox for geostatistical modelling in Python

et al. 2022

View full text Add to dashboard Cite

Abstract. Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of, for example, earth sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity. Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics. We therefore present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields; it can perform kriging, variogram estimation and much more. We demonstrate its abilities by virtue of a series of example applications detailing their use.

show abstract

“…Hence, authors of this foundational layer in scientific software stacks need to take into account the continued use and possibly further development outside the field of mathematics. Best practices for mathematical software [6] and numerical software [20,3] are long known (yet still not established), and properties such as reliability, robustness or transportability [5], the numerical experiment attributes replicability, reproducibility and reusability [9], code as a form of scientific notation [11], as well as basic guidelines for research software [23] have been discussed in the literature, yet, sustainable hand-over strategies for (mathematical) research software projects have not been documented to the best knowledge of the authors.…”

Section: Introductionmentioning

confidence: 99%

Sustainable Research Software Hand-Over

Fehr,

Himpe,

Rave

et al. 2019

Preprint

View full text Add to dashboard Cite

Scientific software projects evolve rapidly in their initial development phase, yet at the end of a funding period, the completion of a research project, thesis, or publication, further engagement in the project may slow down or cease completely. To retain the invested effort for the sciences, this software needs to be preserved or handed over to a succeeding developer or team, such as the next generation of (PhD) students.Comparable guides provide top-down recommendations for project leads. This paper intends to be a bottom-up approach for sustainable hand-over processes from a developer's perspective. An important characteristic in this regard is the project's size, by which this guideline is structured. Furthermore, checklists are provided, which can serve as a practical guide for implementing the proposed measures.

show abstract

Track 1 Paper: Good Usability Practices in Scientific Software Development

Cited by 3 publications

References 0 publications

The State of Sustainable Research Software: Learning from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1)

The State of Sustainable Research Software: Learning from the Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE5.1)

GSTools v1.3: a toolbox for geostatistical modelling in Python

Sustainable Research Software Hand-Over

Contact Info

Product

Resources

About