Reflections on Data Science and the role of the CODATA Data Science Journal from IDW and SciDataCon 2025, Brisbane, 15 October 2025, by Gita Yadav, DSJ Editorial Board, Matthew Mayernik, DSJ Editor-in-Chief, and Mark Parsons, past DSJ Editor-in-Chief.
What is the evolving role of data scientists in ensuring that automation and AI serve the long-term goals of science, integrity, and openness?
This question shaped a lively and deeply reflective session at the 2025 International Data Week (IDW) in Brisbane, Australia, organised by members of the CODATA Data Science Journal (DSJ) editorial board together with partners from CODATA, the World Data System (WDS), and the International Science Council (ISC).
What made this session particularly rewarding was the high level of engagement from both speakers and audience participants, who actively examined practical pathways to support a new generation of research-aware, ethically grounded, and infrastructure-integrated data scientists. Their discussions demonstrated that the evolution of data science is not only a technical or institutional shift, but also a shared community project; one that redefines how knowledge, responsibility, and innovation intersect in the age of intelligent automation.
The session explored how data scientists must adapt to ethical, infrastructural, and community-centric expectations, and how organisations such as CODATA, WDS, ISC, and the Research Data Alliance (RDA) can collectively guide this evolution. Speakers reflected on the historical roots of data science while identifying forward-looking strategies for building capacity, governance, and trust in the expanding data ecosystem.
Background: Data Science as a Field in Motion!
The Data Science Journal was launched by CODATA in 2002 as a peer-reviewed venue to publish, share, and preserve knowledge on data-focused topics. As far as can be determined, it was the first scholarly journal to include the term “data science” in its title. In a retrospective essay, founding editor F. Jack Smith reflected that the title was initially contentious, with some members of the CODATA Publications Committee concerned that “data science” might be misunderstood. Ultimately, the committee agreed that “it was up to CODATA to ensure that it became understood” (Smith, 2023).
Over two decades later, that mission remains both prophetic and relevant. Data science has evolved dramatically, becoming central to academic research, policy, and industrial practice. The term itself has multiplied in meaning, encompassing everything from machine learning and analytics to data curation, visualization, and ethics. Today, as the volume, variety, and velocity of data continue to expand, the field faces another inflection point, while data veracity has become a critical fourth “V” in the landscape.
In an era of intelligent automation, large language models (LLMs) and ubiquitous sensing, data science has become not only a technical discipline but also a pillar of policy, infrastructure, and ethics. Yet, as the IDW2025 meeting made clear, the scientific community places distinct demands on data science, emphasizing provenance, traceability, transparency, and FAIR principles that are not always prioritized in commercial or governmental applications.
This tension raises an important question: What does it now mean to be a data scientist working in and for science, rather than for profit or production?
Read more on the CODATA blog https://codata.org/blog/2025/10/31/evolving-roles-for-data-scientists-in-the-age-of-intelligent-automation/