Category Archives: Data Science Journal

Posts relating to the data science journal

Call for Papers – Data Science Journal

The Data Science Journal is a peer-reviewed, open access, electronic journal dedicated to the advancement of data science and its application in policies, practices and management of Open Data.

We are currently soliciting submissions for papers on a wide range of data science topics, across the whole range of computational, natural and social science, and the humanities. The scope of the journal includes descriptions of data systems, their implementations and their publication, applications, infrastructures, software, legal, reproducibility and transparency issues, the availability and usability of complex datasets, and with a particular focus on the principles, policies and practices for data.

All data is in scope, whether born digital or converted from other sources, and all research disciplines are covered. Data is a cross-domain, cross-discipline topic, with common issues, regardless of the domain it serves. The Data Science Journal publishes a variety of article types (research papers, practice papers, review articles and essays). The Data Science Journal also publishes data articles, describing datasets or data compilations, if the potential for reuse of the data is significant or if considerable efforts were required in compilation. Similarly, the Data Science Journal also publishes descriptions of online simulation, database, and other experiments, partnering with digital repositories on ‘meta articles’ or ‘overlay articles’, which link to and allow visualisation of the data, thereby adding an entirely new dimension to the communication and exchange of data research results and educational materials.

For further information, and to submit a manuscript, please visit http://datascience.codata.org/

Introducing the new Data Science Journal Editorial Board

dsj_coverThis post comes from Sarah Callaghan, new Editor-in-Chief of the Data Science Journal, recently relaunched with Ubiquity Press.

It is my great pleasure to be able to introduce the new editorial team for the Data Science Journal. We have gathered an exceptional team, with members from all around the world, covering data science topics as diverse as data stewardship, databases, large scale data facilities, data visualisation, geospatial aspects of data, semantics, data policy and much, much more. Our editorial board members also bring expertise in research fields such as (but not limited to) Earth sciences, libraries, scientific computing, public health, humanities, mathematics, genomics, computational biology, physics and statistics.

It can be slightly nerve-racking when putting a call out for nominations for editors for a newly re-launched journal – what if no one applies? Thankfully, this wasn’t the case for us, and we received nearly 50 applications, which is a great sign of the feeling in the data science community that this journal is needed and wanted. Many of the applicants I already know through their active engagement in the CODATA and other research data communities, and I am very much looking forward to working with all of the editorial team in the future.

I would also like to take the opportunity to thank the previous members of the Data Science Journal editorial board, in particular the previous Editors-in-Chief, Shuichi Iwata and John Rumble, for their past work.

SarahCallaghanPortrait_2013Introducing myself

I was honoured to be asked to take on the role of Editor-in-Chief of the Data Science Journal earlier this year. My scientific background is in radio propagation, where I created, managed and archived long term, irreproducible datasets, with all the aggravation that goes with that work. I then changed roles and became a data and project manager for the Centre for Environmental Data Analysis (CEDA) at STFC Rutherford Appleton, UK – poacher turning gamekeeper, so to speak.

My main research interests are in data citation and publication. Simply put, I want to change the research culture so that publishing data, and getting credit for it, is the norm rather than the exception. (And yes, I do know how difficult that particular culture change is likely to be.)

In the past I have managed several data citation and publication projects, including the Jisc funded OJIMS and PREPARDE projects, and the NERC Data Citation and Publication project. I was co-chair of the CODATA-ICSTI Task Group on Data Citation (before being co-opted to the CODATA Executive Committee) and am currently a co-chair of the RDA/WDS Working Group on Publishing Data Bibliometrics.

In my day job, I currently project manages several large scale projects including the EU FP7 project CLIPC .  My formal publication list can be found here, and I also blog informally about data topics here.

My aim is to make the Data Science Journal the primary journal for high quality academic publications in data science, providing a focus and discussion space for the wider community. I know that with the support of the editorial team, we will make this happen!