Research Software Engineering

A Guide to the Open Source Ecosystem

Matthias Bannert (KOF Swiss Economic Institute, Zurich, Switzerland)

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English

Chapman & Hall/CRC
17 April 2024

Probability & statistics; Operating systems; Software Engineering; Databases; Computer science

Series: Chapman & Hall/CRC Data Science Series

"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"

By: Matthias Bannert (KOF Swiss Economic Institute Zurich Switzerland)
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 370g
ISBN: 9781032261270
ISBN 10: 1032261277
Series: Chapman & Hall/CRC Data Science Series
Pages: 182
Publication Date: 17 April 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

1. Introduction 2. Stack - A Developer’s Toolkit 3. Programming 101 4. Interaction Environment 5. Git Version Control 6. Data Management 7. Infrastructure 8. Automation 9. Community 10. Publishing & Reporting 11. Case Studies Appendix

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.