The Data Science Journal (ISSN: 1683-1470) was founded in 2002, relaunched in 2014 in partnership with Ubiquity Press, and celebrated 20 years of publication in 2022. For more information about the Data Science Journal, to submit an article or to get involved as a reviewer, please visit the Data Science Journal website: https://datascience.codata.org/.
Talk of a ‘data revolution’ is not hyperbole. Recent decades have seen an unprecedented explosion in the human capacity to acquire, store and manipulate data and information. It is a world historical event involving a revolution in knowledge creation, communication and utilisation as profound as and more pervasive than that associated with Gutenberg’s invention of the printing press. These developments involve profound transformations in the conduct of research. They raise issues that affect science policy, the conduct and methods of research and the data systems, standards and infrastructure that are integral to research. The evidence-based study of these things is Data Science.
The Data Science Journal is dedicated to the advancement of data science and its application in policies, practices and management as Open Data to ensure that data are used in the most effective and efficient way in promoting knowledge and learning. It is a peer-reviewed, open access, electronic journal that is relevant to 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 articles, practice papers, review articles and essays). Our ISSN is 1683-1470.
Scope of the Data Science Journal
Please visit this page for a detailed description of the scope of the Data Science Journal.
Mark A. Parsons was appointed Editor-in-Chief in April 2019. Mark is a research scientist at the University of Alabama in Huntsville supporting NASA’s Chief Science Data Office, and former Secretary General of the Research Data Alliance. He took over from Dr Sarah Callaghan, of the British Atmospheric Data Centre, and previously a co-chair of a number of CODATA Task Groups, including the TG on Data Citation, who was appointed as the first Editor-in-Chief of the next generation Data Science Journal upon its move to Ubiquity Press.
Matt Mayernik began working alongside Mark as joint Editor-in-Chief in August 2021. Matt is a Project Scientist and Research Data Services Specialist in the NCAR/UCAR Library. He is also the Deputy Director of the NCAR Library. His work is focused on research and service development related to research data curation and digital science generally. His research interests include metadata practices and standards, data curation education, data citation and identity, and social and institutional aspects of research data.
Please visit this page for information on previous Editors in Chief.
Data Science Journal and Indigenous knowledge
The following statement was published by the joint Editors-in-Chief in May 2022:
“The Data Science Journal values the perspectives of all data professionals and practitioners and explicitly wants to recognize the insight that comes from Indigenous knowledge and how it is understood and managed. Indigenous knowledge has long been undervalued, misrepresented, and exploited in science, and the Indigenous contributors often remain invisible.
The DSJ is honoured to have published The CARE Principles for Indigenous Data Governance and seeks to live up to those principles of Collective benefit, Authority to control, Responsibility, and Ethics. We are also inspired by the recent position statement from a consortium of rural health journals who will publish “nothing about Indigenous peoples, without Indigenous peoples”.
DSJ will adopt the same principle. How this will be precisely applied will vary depending on the people and knowledge in question, but in essence, we will reject submitted papers that concern Indigenous communities but do not provide evidence of the care taken towards engagement with Indigenous communities including appropriate attribution, appropriate access, and ideally Indigenous authorship. We encourage authors to include details of their perspective and background in the author description.
DSJ will continue to explore how we can foster inclusive principles of data science in our publications and practice, and we always welcome your feedback.”
Special Collections of Data Science Journal
For more about special collections, please visit https://datascience.codata.org/collections/special/.
Page last updated: 2023-02-16.