#GenR Software Citation Round-up

A concluding summary of headline issues from the Open Science theme of ‘software citation’. Software citation is an important building block in the future of Open Science and has run as Generation R’s launch editorial theme. As with all of the topics of focus on Gen R editorially the issue will be revisited on regular occasions as major developments occur.

What is intrinsically important about software citation?

For the main part it would appear to be the case that until recently no one had indexed, or cataloged, research software. If we compared this situation to the cataloging of literature, and somehow nobody had cataloged publications for the last fifty years, then this would just be unimaginable. But for software this has been the case — for the last half-century there has been virtually no widespread and systematic indexing of software, or its citation in literature. There are exceptions, and the Astrophysics Source Code Library is such an exception and worthy of mention, started in 1999. (ASCL >1999)

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Make Your Code Citable Using GitHub and Zenodo: A How-to Guide

This how-to guide is designed for researchers who want to create and re-use GitHub-based repositories in academic literature.

Open Science MOOC

The following guide has been made by the Open Science MOOC as part of preparation work on its first module release ‘Open Research Software and Open Source‘. The Open Science MOOC is made by an international volunteer group of over a hundred contributors, which you are free to join.

Gen R is a partner contributor to Open Science MOOC and over time as our editorial paths cross we will look to make a variety of contributions to the MOOC as a free and open learning resource for all.

Software Citation

It’s hard to overstate how important it is to have a record of what software has been produced, and also how little has been done in the past to create such indexes and catalogs of software. It’s like no one cataloged books for the last half-century and only now retrospectively took up the task.

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Concrete Advice for FAIR Software

Image: Video screen grab from The Leibniz “Mathematical Modeling and Simulation” (MMS) Days 2018 Leipzig, Feb / Mar 2018. (The video can be viewed at the bottom of the article)

This post was originally published in German on the TIB Blog (March 21.2018)

Findability Through Persistent Identifiers

In addition to implementing the FAIR Data Principles for research data there is a need to support the sustainable development, use, and publication of research software. This blog post represents an interim status of the development of these competences.

In addition, it shall introduce a series of articles, which similarly to the already explained FAIR Data Principles for research data (Kraft 2017) will recommend: concrete examples and actions to scientific software projects, summarizes specialist literature (see the bibliography), and also sets goals for our own software projects and those we supports.

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