[CODATA-international] 20 Years of Data Science - DSJ Call for Submissions

DSJ Editor editor at codata.org
Mon Jan 31 10:00:00 EST 2022

Throughout 2022, the Data Science Journal invites submissions related to
the evolution and future directions of data science (broadly defined),
including recent advances, retrospective analyses, and community
inspirations and provocations.

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, intellectual, cultural) 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.

We encourage a broad range of contributions. Specific topics of interest
include (but are not limited to):


   What are the most significant advances in data science (broadly defined)
   over the past 20 years?

   How does data science differ from its beginnings 20 years ago?

   What are the main gaps and opportunities that must be addressed in data
   science going forward?

   How have changes in the way that data are or should be shared influenced
   data science?

Submit articles at https://datascience.codata.org/

We look forward to hearing from you.


Matt Mayernik and Mark Parsons
Joint Editors-in-Chief
*Data Science Journal*
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