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Building a local community of practice in scientific programming for Life Scientists

View ORCID ProfileSarah L. R. Stevens, View ORCID ProfileMateusz Kuzak, Carlos Martinez, View ORCID ProfileAurelia Moser, Petra Bleeker, View ORCID ProfileMarc Galland
doi: https://doi.org/10.1101/265421
Sarah L. R. Stevens
1Department of Bacteriology, University of Wisconsin–Madison, Microbial Sciences Building, 1550 Linden Drive, Madison, WI 53706, USA.
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Mateusz Kuzak
2Dutch Techcentre for Life Sciences (foundation office), Catharijnesingel 54, 3511 GC Utrecht, Netherlands.
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Carlos Martinez
3Netherlands eScience Center, Science Park 140, Amsterdam, 1098 XG, Netherlands.
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Aurelia Moser
4Mozilla Foundation, 331 East Evelyn Avenue, Mountain View, CA 94041, USA.
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Petra Bleeker
5Department of Plant Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH Amsterdam, Netherlands
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Marc Galland
5Department of Plant Physiology, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH Amsterdam, Netherlands
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  • For correspondence: m.galland@uva.nl
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Abstract

For most experimental biologists, handling the avalanche of data generated is similar to self-learn how to drive. Although that might be doable, it is preferable and safer to learn good practices. One way to achieve this is to build local communities of practice by bringing together scientists that perform code-intensive research to spread know-how and good practices.

Here, we indicate important challenges and issues that stand in the way of establishing these local communities of practice. For a given researcher working for an academic institution, their capacity to conduct data-intensive research will be arbitrarily relying on the presence of well-trained bioinformaticians in their neighborhood.

In this paper, we propose a model to build a local community of practice for scientific programmers. First, Software/Data Carpentry (SWC) programming workshops designed for researchers new to computational biology can be organized. However, while they provide an immediate solution for learning, more regular long-term assistance is also needed. Researchers need persisting, local support to continue learning and to solve programming issues that hamper their research progress. The solution we describe here is to implement a study group where researchers can meet-up and help each other in a “safe-learning atmosphere”. Based on our experience, we describe two examples of building local communities of practice: one in the Netherlands at the Amsterdam Science Park and one in the United States at the University of Wisconsin-Madison.

The current challenge is to make these local communities self-sustainable despite the high turnover of researchers at any institution and the lack of academic reward (e.g. publication). Here, we present some lessons learned from our experience. We believe that our local communities of practice will prove useful for other scientists that want to set up similar structures of researchers involved in scientific programming and data science.

Author summary In this paper, we describe why and how to build a community of practice for life scientists that start to make more use of computers and programming in their research. A community of practice is a small group of scientists that meet regularly to help each other and promote good practices in scientific computing. While most life scientists are well-trained in the laboratory to conduct experiments, good practices with (big) datasets and their analysis are often missing. This paper proposes a field-guide on how to build such a community of practice at a local academic institution. Based on two real-life examples, some recommendations are provided. We believe that the current data deluge that life scientists will increasingly face can benefit from the implementation of these small communities. Good practices spread among experimental scientists will foster open, transparent, sound scientific results beneficial to society.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 15, 2018.
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Building a local community of practice in scientific programming for Life Scientists
Sarah L. R. Stevens, Mateusz Kuzak, Carlos Martinez, Aurelia Moser, Petra Bleeker, Marc Galland
bioRxiv 265421; doi: https://doi.org/10.1101/265421
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Building a local community of practice in scientific programming for Life Scientists
Sarah L. R. Stevens, Mateusz Kuzak, Carlos Martinez, Aurelia Moser, Petra Bleeker, Marc Galland
bioRxiv 265421; doi: https://doi.org/10.1101/265421

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