Welcome to the DS4EIW 2026 Workshop

DS4EIW is a workshop to promote and share research and innovation on data science solutions with the final challenge to study, promote, and guarantee equality, inclusion, and well-being, significantly impacting society. This is an essential subject of debate in engineering and sociology, also involving governments, private and public companies, activists, and the press because discrimination and biases have to be avoided, stereotypes have to be removed, and well-being opportunities have to be designed and promoted.

The workshop will be held in person in conjunction with the IEEE International Conference on Data Engineering (ICDE) 2026 conference in Montréal, Canada, on May 4, 2026 and will be a great opportunity to share experiences and results with the international community. The workshop will allow researchers and practitioners from various research areas -- data mining, machine learning, digital ethics, applied statistics, sociology, psychology, journalism, linguistics -- to share their experiences on studying, designing, and developing cutting-edge methodologies addressing societal challenges and derive policies, strategies, and solutions to support the government bodies to derive guidelines to create more inclusive, innovative and reflective societies.

The methodological approach should consider any aspect of the diversity in a community (e.g., gender, special needs, age, ethnic and religious origin) to collect, study, and analyze data with the final aim at, effectively supporting policymakers in the decision process to promote and guarantee equality, inclusion, and well-being.

Overview

We live in challenging times, but the complexity of our daily activities needs diversity in skills, knowledge, approaches to be interpreted: the more the context is diversified, the more it needs to be managed by a society capable of understanding and governing it.

Developing an inclusive society with a strong respect for diversity is a challenging issue but an urgent topic to be addressed to build more reflexive societies. Strategic, innovative, and human-readable methodologies are needed to collect and analyze data to enhance awareness about the societal phenomena, guarantee equality and define ad-hoc policies to fill the gap between the present and an equity society promoting inclusion and well-being policies.

Data science is an interdisciplinary field about scientific processes, methodologies, and systems to extract valuable knowledge or insights from data in various forms. From the perspective of societal challenges, data can be analyzed using data mining, machine learning, data analysis, and statistics, optimizing processes and maximizing knowledge exploitation in societies with positive effects on enhancing talents and a sense of belonging.

On the other hand, data science algorithms are powerful and necessary tools behind a large part of the information we use every day; rendering them more transparent (i.e., human-readable relationships among the input and the algorithm's outcomes, understanding of the inner functionalities of black-box models) should improve their usability in various areas, not least because discrimination and biases have to be avoided. Innovative approaches should be devised to make the algorithm software human-readable and usable by both analysts and end-users to increase transparency and user control significantly. We believe that transparent algorithms will have a high impact shortly because they should improve algorithm usability in various application domains and support the definition of policies to build better societies.

The workshop aims to allow academics and practitioners from various research areas to share their experiences studying, analyzing, designing, and developing innovative methodologies centered on societal challenges to derive insights, characterize sociological phenomena, and support policymakers in promoting more inclusive reflexive and innovative societies.

Industrial implementations of explainable/transparent data algorithm applications, design and deployment experience reports on various issues raising data transparency projects, and avoiding bias and discrimination, are particularly welcome. We call for research and experience papers and demonstration proposals covering any aspect of data algorithmic transparency and accountability in real-life applications, fundamental properties to avoid bias and discrimination.

Important Dates

  • Paper Submission: January 18, 2026 (AoE 23:59 PM) Feb 28th, 2026 (AoE 23:59 PM)
  • Notification of acceptance: February 16, 2026 March 5, 2026 (AoE 23:59 PM)
  • Camera-ready copies: March 9, 2026 (AoE 23:59 PM)
  • DS4EIW Workshop: May 4, 2026

All deadlines refer to midnight (23:59) in the AoE (Anywhere on Earth) time zone.

Submission Tracks

  • Regular research papers (up to 8 pages)
  • Short research, application, and vision papers (up to 4 pages)

Page limits exclude references. No appendix is allowed. All accepted papers will appear in the IEEE ICDE 2026 conference proceedings. At least one author is required to register for the workshop.

News

  • November 6, 2024
    Call for Papers is now live!
    The call for papers for DS4EIW 2026 has been published. Check out the submission guidelines for more information. The submission site is now open! Please submit your papers through the official CMT submission system.

  • Official workshop website is live!
    The official website for DS4EIW 2026 workshop is now live. Stay tuned for updates!

Previous Editions

Co-location with IEEE ICDE 2026