To me the engineering audience group is a big deal. Regular engineers that do no research per-se might be interested in following research related to their application field to ensure that their developments follow the state of the art. As such they would qualify as more than "casual followers of science" but ain't researchers either.
Two examples come to mind: first developers of distributed databases might want to follow the progress on distributed data-structures such as CRDTs [1]. Apparently Riak developers at Basho are fast at implementing such new theoretical results into their product [2].
I am pretty sure that Basho as an organization is not a subscriber to any pay-walled CS journals. So having such articles as Open Access helps make it discoverable by the engineering community, just by googling, sharing links over social networks, mailing lists or news sites such as HN and reddit.
Similarly developers of (big or small) data analytics tools might want to follow the research on machine learning algorithms so as to implement the state of the art and empirically evaluate it against the previous baselines. As an engineer contributing to the scikit-learn project this is basically my job. I am no researcher myself but I (and the many other scikit-learn developers) try to help transfer the results from academic research to make it available to our users community that reaches out of the traditional academic circles.
Having researchers publish their results in Open Access venues reduces the friction to transfer new results to practical, productionalized implementations (e.g. as open source projects maintained over the years). Open Access is one of the tools to help break the traditional Researcher / Engineering boundary as agile development tools and the devops movement helped break the Developer / Sysadmin boundary. To me Open Access is a fundamental building block of "Agile Science".
Two examples come to mind: first developers of distributed databases might want to follow the progress on distributed data-structures such as CRDTs [1]. Apparently Riak developers at Basho are fast at implementing such new theoretical results into their product [2].
[1] http://pagesperso-systeme.lip6.fr/Marc.Shapiro/papers/RR-695... [2] http://vimeo.com/43903960
I am pretty sure that Basho as an organization is not a subscriber to any pay-walled CS journals. So having such articles as Open Access helps make it discoverable by the engineering community, just by googling, sharing links over social networks, mailing lists or news sites such as HN and reddit.
Similarly developers of (big or small) data analytics tools might want to follow the research on machine learning algorithms so as to implement the state of the art and empirically evaluate it against the previous baselines. As an engineer contributing to the scikit-learn project this is basically my job. I am no researcher myself but I (and the many other scikit-learn developers) try to help transfer the results from academic research to make it available to our users community that reaches out of the traditional academic circles.
Having researchers publish their results in Open Access venues reduces the friction to transfer new results to practical, productionalized implementations (e.g. as open source projects maintained over the years). Open Access is one of the tools to help break the traditional Researcher / Engineering boundary as agile development tools and the devops movement helped break the Developer / Sysadmin boundary. To me Open Access is a fundamental building block of "Agile Science".