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Research software is an integral part of scientific investigations. The paper identifies challenges, risks and new opportunities in research software publication and discovery. The diverse code discovery landscape is mapped and agents with their business models identified. Examples for discovery tools and strategies are given to support the classification. Reproducibility of research and reuse of code may improve if software discovery was easier. Researcher conducting a search for existing software in the context of a state-of-the-art report or a software management plan could use this paper as a guideline for their information retrieval strategy.
published by IEEE Computer Society with DOI 10.1109/eScience.2018.00016
communities, sustainable development, scientific computing, research software, information retrieval
communities, sustainable development, scientific computing, research software, information retrieval
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 31 | |
| downloads | 12 |

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