https:\/\/www.nature.com\/articles\/d41586-019-02046-0<\/a><\/p>\nOn 10 April, astrophysicists announced that they had captured the first ever image of a black hole. This was exhilarating news, but none of the giddy headlines mentioned that the image would have been impossible without open-source software. The image was created using Matplotlib, a Python library for graphing data, as well as other components of the open-source Python ecosystem. Just five days later, the US National Science Foundation (NSF) rejected a grant proposal to support that ecosystem, saying that the software lacked sufficient impact.<\/p>\n
It\u2019s a familiar problem: open-source software is widely acknowledged as crucially important in science, yet it is funded non-sustainably. Support work is often handled ad hoc by overworked graduate students and postdocs, and can lead to burnout. \u201cIt\u2019s sort of the difference between having insurance and having a GoFundMe when their grandma goes to the hospital,\u201d says Anne Carpenter, a computational biologist at the Broad Institute of Harvard and MIT in Cambridge, Massachusetts, whose lab developed the image-analysis tool CellProfiler. \u201cIt\u2019s just not a nice way to live.\u201d<\/p>\n
Scientists writing open-source software often lack formal training in software engineering, which means that they might never have learnt best practices for code documentation and testing. But poorly maintained software can waste time and effort, and hinder reproducibility. Biologists who use computational tools routinely spend \u201chours and hours\u201d trying to get other researchers\u2019 code to run, says Adam Siepel, a computational biologist at Cold Spring Harbor Laboratory in New York, and a maintainer of PHAST, a tool used for comparative and evolutionary genomics. \u201cThey try to find it and there\u2019s no website, or the link is broken, or it no longer compiles, or crashes when they\u2019ve tried to run it on their data.\u201d<\/p>\n
But there are resources that can help, and models to emulate. If your research group is planning to release open-source software, you can prepare for the support work and the questions that will arise as others begin to use it. It isn\u2019t easy, but the effort can yield citations and name recognition for the developers, and improve efficiency in the field, says Wolfgang Huber, a computational biologist at the European Molecular Biology Laboratory in Heidelberg, Germany. Plus, he adds, \u201cI think it\u2019s fun.\u201d<\/p>\n
Have a plan<\/h2>\n
For developers of scientific software, release day isn\u2019t the end of the labour, but often the beginning. Tim Hopper, a data scientist at Cylance in Raleigh, North Carolina, says on Twitter, \u201cGive a man a fish and you feed him for a day. Write a program to fish for him and you maintain it for a lifetime.\u201d Carpenter hired a full-time software engineer to handle maintenance for CellProfiler, which logs about 700 questions and 100 bug reports or feature requests per year, or about 15 per week. But most open-source software maintenance is done on a volunteer basis. \u201cI did this myself, like after midnight,\u201d says Siepel of his tech-support efforts on PHAST….<\/p>\n","protected":false},"excerpt":{"rendered":"
*Generally speaking, if nobody’s hired to maintain it, nobody maintains it. \u00a0This article is from 2019. https:\/\/www.nature.com\/articles\/d41586-019-02046-0 On 10 April, astrophysicists announced that they had captured the first ever image of a black hole. This was exhilarating news, but none of the giddy headlines mentioned that the image would have been impossible without open-source software. […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2336","post","type-post","status-publish","format-standard","hentry","category-uncategorised"],"yoast_head":"\n
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