The Data Science Journal is, as its title suggests, a journal dedicated to the advancement of data science. The first thing that’s good about it is that you won’t get random emails about it with poor grammar and wild claims about its impact factor that begin with DEAR ESTEEMED RESEARCHER….
Even though it’s about data science, it’s not obsessed with building ever better recommender algorithms for Netflix or mining twitter feeds. Its focus is very much on its application in the policies, practices, and management of open data. It tries to take as wide a definition as possible when considering the subject. Data can be originally digital or converted from other sources, and it also considers every research discipline. The journal will have digital humanities papers rubbing shoulders with bioinformatics papers with social science papers.
It’s also a journal that is interested in applications, so papers that are descriptions of data systems are great. Naturally, it’s entirely electronic and open access. The journal has been in existance since 2002 but has recently been relaunched by CODATA and moved to the Ubiquity Press platform with the excellent Sarah Callaghan (@sorcha_ni) as editor (full disclosure: I am on the board). There is a call for papers for the journal which is discussed in detail here.
If you are interested have a look at its web site to find out more about the types of articles they are interested in receiving.