Research Software Engineering

A Guide to the Open Source Ecosystem

By:

Matthias Bannert

Format:

Hardback

Series:

Chapman & Hall/CRC Data Science Series

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Description

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

Author Biography:

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.

Release date NZ

April 12th, 2024

Author

Matthias Bannert

Audience

Professional & Vocational

Illustrations

6 Tables, black and white; 16 Line drawings, color; 5 Line drawings, black and white; 14 Halftones, color; 30 Illustrations, color; 5 Illustrations, black and white

Pages

182

Series

Chapman & Hall/CRC Data Science Series

ISBN-13

9781032261645

Product ID

38221138

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