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About the Event Computer software is foundational in many fields of research, and its contributions to all stages of the research process continue to grow. According to a study carried out by the Software Sustainability institute, 7 out of 10 researchers reported that their work would be impossible without software. This sentiment points to the importance of software development practices being considerate of the future, when others may need to use or modify the same software that you have created in order to carry out further work. Sustainable software development is closely coupled with open and reproducible research practices. For results created with software to be reproducible, others need to be able find, understand, and run your software. Are they likely to understand what your software does without appropriate documentation? Are they likely to be able to get your software running if it can't be straightforwardly installed? Will they be able to credit your software if they can't find it? These are just a few issues that will prevent research outputs from being truly open and reproducible, and that sustainable software development practices can help with. This event hopes to bring together interested researchers from any field to learn about software sustainability. Through talks and discussion, the aims are to share resources, highlight practices that individuals / teams have found useful (or not useful!), and encourage opportunities for future skill sharing at the University.
Software Sustainability in Practice event organised by the Open Research Team, University of York on 20 April 2021. This talk discusses the challenges of teaching software sustainability to Biologist who do not see themseves as software developers. It discusses how these challenges arise and proposes several approaches to meet them
reproducibility, teaching and training, data analysis, higher education
reproducibility, teaching and training, data analysis, higher education
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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