The CODATA Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts. 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 open data.
All data is in scope, whether born digital or converted from other sources.
Posted on 09 May 2022
The Data Science Journal is excited to be celebrating 20 years of publication!
When the first issue of the Data Science Journal was published by CODATA in 2002, it was perhaps the first publication dedicated to the new concept of “data science.” Since the beginning, Data Science Journal papers have advanced understanding of many aspects of the science of data, including the capture of data, their analysis, metadata, retrieval, archiving, exchange, mining to find unexpected knowledge and data relationships, and visualization, along with intellectual property rights and other legal and ethical issues related to data.
Data science has evolved significantly over the past two decades, becoming a topic of significant interest in academic research, public and private sector workplaces, and in government policies and practices. The boom of data science has been stimulated by the large volumes and varieties of data being made public on the internet, via the explosive growth in digital technologies such as personal computers, cell phones, social media, smart devices, and sensor networks. Data science has also grown with a recognition that research integrity is enhanced with the increased availability of the data that underpins research. All this has resulted in a need for new infrastructure, skills and support in the research process and the ability to work with data.
Data science has emerged as a panoply of techniques, tools, and skills that can be applied to derive value (economical or intellectual) out of the growing piles of data. We recognize that this includes advanced analytics and must also include concerns of ethics, infrastructure development, information theory, pragmatics, and more. Data science must consider the science of data and issues of data in science.
What have we learned?
Where are we now?
The journal plans several activities to celebrate the anniversary and explore these questions. We welcome your contributions and ideas.
Special collection: The evolution and future directions of data science.
Throughout 2022, DSJ encourages submissions related to the evolution and future directions of data science (broadly defined), including recent advances, retrospective analyses, and community inspirations and provocations. We encourage a broad range of contributions. Please contribute.
Events at International Data Week
We plan several events at IDW including a research session, community discussion, and convivial reception. We’ll provide more information as the program develops.
Posted on 31 Jan 2022
Posted on 25 Aug 2021