Research Software Engineering

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A01=Matthias Bannert
academic data infrastructure
Author_Matthias Bannert
Automation
Category=PBT
Category=ULJ
Category=UMZ
Category=UN
Category=UY
Data Management
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
interdisciplinary collaboration
open source analytics
Programming
programming for scientific data analysis
reproducible research methods
Research Software Engineering
scientific computing tools
Stack
version control workflows

Product details

  • ISBN 9781032261645
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 17 Apr 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Research Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.

Key Features

  • overview: breakdown of complex data science software stacks into core components
  • applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software
  • reader guidance: different entry points and rich references to deepen the understanding of selected aspects

Matthias Bannert, Ph.D. gained his hands-on data science and data engineering at ETH Zürich in more than a decade of working for the KOF Swiss Economic Institute. Today, he works as a data engineering expert advisor at cynkra and supports ETH as a section lead in the innovation-minded KOF Lab. In 2021, he was a co-chair of useR!, the annual user conference of the R Project for Statistical Computing. He remains an active contributor to extension packages of the R language and the open source community in general.

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