Open Access Journal in Machine Learning JMLR, valuable lessons

In my future research, I will always give priority to publish in open access journals, One of the most important things I achieved from this class. I am really surprised about the big number of computer science open access journals, more taken by the high impact factors of many of these journals.

A good example isĀ  JMLR (Journal of Machine Learning Research). As a researcher in Machine Learning, I am very proud of the founders of this journal in 2000. Back then, in what seems like a revolution, forty members of the editorial board of a prestigious Machine Learning journal resigned to work in this open access journal. Their resignation letter (http://sigir.org/files/forum/F2001/sigirFall01Letters.html) is a nice piece that Machine Learning researchers should use to show how we learn and adapt and exploit technological advancements as humans before we look for ways to inject learning behavior to machines.
They stated it is detrimental for researchers to continue publishing in expensive journals with pay-access archives in the Internet era.

That was 15 years ago! Since then, JMLR continued to publish cutting-edge research that can be accessed online for free while authors’ copyright is retained. JMLR has been always in connection with MIT which used to publish paper issues of the journal papers till 2004. It is really one of the best journals in the field. In 2008, it was included in top 20 computer science journals in terms of average citations per paper, where each paper is cited more than 6 times on average. In 2004, its impact factor was the second highest in all computer science journals in general.

JMLR gave students and researchers around the world easy and free access to top research in the field. It has been steadily growing from 17 accepted papers (from 143 submitted) in 2003 to 135 papers accepted in 2013 after one decade (from 764 submitted in the same year). But for students and researchers, JMLR is more than a place to download a paper to read for free by supporting open-source software for research!

Like the lesson of the editorial board, humans should learn and allow free access to their publications online, also machine learning researchers should make their software developed for ML research available for other researchers to start from where they ended. Through JMLR, any student or researcher can easily access more than 80 open-source software tools and programs that can be used for machine learning and related artificial intelligence and statistics fields.

JMLR is a successful example of a scientific community that respects copyright but knows that it does not mean that accessing scientific achievements should be paid for.

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