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Bisaloo committed Jul 9, 2024
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Expand Up @@ -11,7 +11,7 @@ Presentation (20min including questions) at the useR!2024 conference, under the

## Abstract

It is common for R packages answering the same need to have different input and output formats. This may result in a large amount of spent time to reformat the inputs and outputs whenever a specific part of the data pipeline is swapped out to use a different R package. This time can come at a huge cost whenever results are needed quickly, such as in pandemic response. Using S3 classes providing standard formats that all downstream packages use may be a good solution to this issue, thus improving the interoperability within the global R package ecosystem. However, this approach comes with technical and social challenges. Here, I present the work we are doing to implement and encourage the adoption of standard S3 classes in epidemiology. I highlight key findings and challenges such as how to preserve backward compatibility in existing packages and give recommendation for future similar endeavors.
It is common for R packages answering the same need to have different input and output formats. This may result in a large amount of spent time to reformat the inputs and outputs whenever a specific part of the data pipeline is swapped out to use a different R package. This time can come at a huge cost whenever results are needed quickly, such as in pandemic response. Using S3 classes providing standard formats that all downstream packages use may be a good solution to this issue, thus improving the interoperability within the global R package ecosystem. However, this approach comes with technical and social challenges. Here, I present the work we are doing to implement and encourage the adoption of standard S3 classes in epidemiology. I highlight key findings and challenges such as how to preserve backward compatibility in existing packages and give recommendation for future similar endeavors.

## Slides

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