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Acquiring the skills

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This page lists selected literature and online resources. Some are related to existing tutorial pages, while others are not. They are supposed to be of high interest to this site’s users.

Several of the resources were added based on an inspiring talk by Julia Lowndes at the SAFRED conference, Brussels, 27 Feb 2018.

These resources focus on the learning and teaching aspect, while they often also give an overview of scientific computing workflows.

Open data science in general

  • Lowndes et al. (2017): learning open data science tools
  • Hampton et al. (2017): training approaches and needed skills in data science
  • Stevens et al. (2018): local community of practice for scientific programming: why, how (including scheme), challenges
  • National Center for Ecological Analysis & Synthesis (2020): resources for learning, collaborating and inspiring others

In relation to statistics teaching

  • Kaplan (2017): ten organizing blocks for introductory statistics teaching in the present data science context
  • Cetinkaya-Rundel & Rundel (2017): computational infrastructure and toolkit choices to allow for the necessary pedagogical innovations in statistics education

Bibliography

Cetinkaya-Rundel M. & Rundel C.W. (2017). Infrastructure and tools for teaching computing throughout the statistical curriculum. PeerJ Preprints 5: e3181v1. https://doi.org/10.7287/peerj.preprints.3181v1.

Hampton S.E., Jones M.B., Wasser L.A., Schildhauer M.P., Supp S.R., Brun J., Hernandez R.R., Boettiger C., Collins S.L., Gross L.J., Fernández D.S., Budden A., White E.P., Teal T.K., Labou S.G. & Aukema J.E. (2017). Skills and Knowledge for Data-Intensive Environmental Research. BioScience 67 (6): 546–557. https://doi.org/10.1093/biosci/bix025.

Kaplan D.T. (2017). Teaching stats for data science. PeerJ Preprints 5: e3205v1. https://doi.org/10.7287/peerj.preprints.3205v1.

Lowndes J.S.S., Best B.D., Scarborough C., Afflerbach J.C., Frazier M.R., O’Hara C.C., Jiang N. & Halpern B.S. (2017). Our path to better science in less time using open data science tools. Nature Ecology & Evolution 1 (6): s41559-017-0160-017. https://doi.org/10.1038/s41559-017-0160.

National Center for Ecological Analysis & Synthesis (2020). Openscapes Resources [WWW document]. https://www.openscapes.org/resources/ (accessed September 22, 2020).

Stevens S.L.R., Kuzak M., Martinez C., Moser A., Bleeker P.M. & Galland M. (2018). Building a local community of practice in scientific programming for Life Scientists. bioRxiv 265421. https://doi.org/10.1101/265421.