Journal:Data without software are just numbers

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Full article title Data without software are just numbers
Journal Data Science Journal
Author(s) Davenport, James H.; Grant, James; Jones, Catherine M.
Author affiliation(s) University of Bath, Science and Technology Facilities Council
Primary contact Email: J dot H dot Davenport at bath dot ac dot uk
Year published 2020
Volume and issue 19(1)
Article # 3
DOI 10.5334/dsj-2020-003
ISSN 1683-1470
Distribution license Creative Commons Attribution 4.0 International
Website https://datascience.codata.org/articles/10.5334/dsj-2020-003/
Download https://datascience.codata.org/articles/10.5334/dsj-2020-003/galley/929/download/ (PDF)

Abstract

Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally, it is recognized that data are meaningless unless their provenance is preserved, through appropriate metadata. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation and control of experiment or data collection, and that which analyzes, modifies, and draws value from raw data. In order to meet the aims of reproducibility, we argue that data management alone is insufficient: it must be accompanied by good software practices, the training to facilitate it, and the support of stakeholders, including appropriate recognition for software as a research output.

Keywords: software citation, software management, reproducibility, archiving, research software engineer

Introduction

Context

References

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article lists references in alphabetical order; however, this version lists them in order of appearance, by design.