![]() (iii) In order to provide full transparency of the workflow, the code should allow users to retrace and inspect the intermediate results generated at every step of the pipeline this can be achieved using a container object that records all functions, parameters and results in a central location. (ii) The source code should be modular to enable rapid development and efficient maintenance of its functionality. (i) To allow users to quickly start developing their own customized workflows, the toolbox must be straightforward to use with easily readable code pipelines. Adapting data analysis workflows to these new guidelines requires the development of code that is easily readable and maintainable, which often demands substantial time and effort.Īn effective way to mitigate this burden is to utilize computational toolboxes that include the following features. This has led to substantial changes in scientific publishing, including new rules for the mandatory sharing of source code and accompanying data for publication in peer-reviewed journals ( Baker, 2016b). ![]() A major shift in the biomedical community in recent years has been a push to promote reproducibility in research ( Baker, 2016a Brito et al., 2020 Sandve et al., 2013 Winchester, 2018).
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