A new journal on all aspects of big data is being launched at the Strata conference. It is open access, peer reviewed and it  charges for the paper and online version. How does that work?

Big Data looks like a quality journal dedicated to the subject of using data. The research papers it contains are peer reviewed and published under a creative commons license. This makes it possible to download any paper as a pdf for free. Yet the Journal is also available in a paper print edition and as an online access service for a subscription - $412 for print and online to individual subscribers and $2,085 to institutions.

If you are wondering how this magic works the answer is surprisingly simple. The journal contains two types of article - reviewed papers and premium articles. The premium articles aren't research papers but think pieces, opinions, case studies, best practice - in fact anything that isn't pure research that needs peer review. It combines a magazine with a journal using the magazine element to pay for the cost of printing the journal plus a profit to the publisher.

If you consider that charging for access to publicly funded research is something of a dubious practice, this approach gets around the problem quite nicely. The cost to institutions is, of course, ridiculously high, but if all the students want is access to the research then this is free. It will be interesting to see if the premium articles can be compelling enough to make the journal a commercial success.

The first issue is free to download, including the premium content. The editorial board includes Edd Dumbill, principal analyst for O'Reilly Radar, and program chair for the O'Reilly Strata conference as editor in chief and a range of experts from universities and companies such as Google and Microsoft.

Topics covered include:

• Big data industry standards
• New technologies being developed specifically for big data
• Data acquisition, cleaning, distribution, and best practices
• Data protection, privacy, and policy 
• Business interests from research to product
• The changing role of business intelligence
• Visualization and design principles of big data infrastructures
• Physical interfaces and robotics
• Social networking advantages for Facebook, Twitter, Amazon, Google, etc.
• Opportunities around big data and how companies can harness it to their advantage

The first issue has five articles which appear to be peer reviewed paper and eight which appear to be premium content - the distinction isn't clearly made. The research articles are:

• Mapreduce is Good Enough?
• What Do RDF and SPARQL bring to Big Data Projects? no access
• Unraveling the Complexities of Life Sciences Data
• Data Science and its Relationship to Big Data and Data-Driven Decision Making
• Benchmarking Big Data Systems and the BigData Top100 List