Research Software Engineering (Paperback)

Matthias Bannert

ISBN 10: 1032261277 / ISBN 13: 9781032261270

Published by Taylor & Francis Ltd, 2024

About this Item

Paperback. 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 Featuresoverview: breakdown of complex data science software stacks into core componentsapplied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source softwarereader guidance: different entry points and rich references to deepen the understanding of selected aspects Research Software Engineering: A Guide to the Open Source Ecosystem strives for a big picture overview and to give an understanding of the opportunities of programming as an approach to analytics and statistics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781032261270

Bibliographic Details

• Title: Research Software Engineering (Paperback)
• Publisher: Taylor & Francis Ltd
• Publication Date: 2024
• Language: English
• ISBN 10: 1032261277
• ISBN 13: 9781032261270
• Binding: Paperback
• Condition: new

About this title

Synopsis

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

About the Author

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.