Research relies heavily on scientific software, and a large and growing fraction of researchers are engaged in developing software as part of their own research ([Hannay et al 2009](https://doi.org/10.1109/SECSE.2009.5069155 "How do scientists develop and use scientific software?")). Despite this, _infrastructure to support the preservation, discovery, reuse, and attribution of software_ lags substantially behind that of other research products such as journal articles and research data. This lag is driven not so much by a lack of technology as it is by a lack of unity: existing mechanisms to archive, document, index, share, discover, and cite software contributions are heterogeneous among both disciplines and archives and rarely meet best practices ([Howison 2015](https://doi.org/10.1002/asi.23538 "Software in the scientific literature: Problems with seeing, finding, and using software mentioned in the biology literature")). Fortunately, a rapidly growing movement to improve preservation, discovery, reuse and attribution of academic software is now underway: a recent [NIH report](http://softwarediscoveryindex.org), conferences and working groups of [FORCE11](https://www.force11.org/), [WSSSPE](http://wssspe.researchcomputing.org.uk/) & [Software Sustainability Institute](http://www.software.ac.uk/), and the rising adoption of repositories like [GitHub](https://github.com), [Zenodo](https://zenodo.org), [figshare](https://figshare.com) & [DataONE](https://www.dataone.org) by academic software developers. Now is the time to improve how these resources can talk to each other.
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