Join us in celebrating Love Data Week 2020

Federica Fina
Wednesday 5 February 2020
“Love Data Week 2018 CC Licensed Materials”

Love Data Week 2020 is almost here! Like the past two years we will join other institutions in celebrating Love Data Week.

Normally we invite researchers to contribute with blog posts. However, this year we went a bit further than that and in addition to the usual blog posts we have organised two talks by St Andrews researches who will demonstrate their love for data and code by talking about their experiences and by sharing practical advice. Join us next week for talks by Alexander Konovalov (School of Computer Science) and Faye Moyes (School of Biology):

  • Modern practices of sharing computational research by Alexander Konovalov (School of Computer Science). Tuesday 11 February, 3pm, Physics Lecture Theatre C.

“Have you been frustrated by trying to use someone else’s code which is non-trivial to install? Have you tried to make supplementary code for your paper to be easily accessible for the reader? If so, you certainly know that this may require non-trivial efforts. I will demonstrate some tools that may help to create reproducible computational experiments, and will explain which skills will be needed to use these tools. The talk will demonstrate examples in Python and R runnable in Jupyter notebooks. You are welcome to bring your laptop to try these examples online. No prior knowledge of programming is required.”

  • BioTIME – building an interactive open access database by Faye Moyes (School of Biology). Thursday 13 February, 2.30pm, United College School II.

“The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is a community‐led open‐source database of biodiversity time series which has expanded exponentially since inception and is continuing to grow. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.”

For more details visit the University’s Events page or get in touch with the Research Data Management team at [email protected].

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