An invitation to scholars, industry practitioners and post-graduate students with research interests in the fields of Decision Science, Data Science, Information Science, Information Management, Knowledge Management, Information Systems, and other information studies. The Generative Decision Sciences Conference 2026 is hosted by CODATA and The Centre for Applied Data Science from the University of Johannesburg.
Full paper submission due dates
You are cordially invited to submit your conference paper by August 31st for double-blind peer review (cf Programme Committee and review panel). To ensure personal information is removed before peer review, visit Microsoft Support on how to remove hidden data. The review process is completed in English as the standard conference language. Posters are reviewed separately (cf Poster criteria). Kindly ensure that conference papers conform to the criteria below; otherwise, your research contributions may not make the review process for inclusion in DHET-accredited published proceedings. Work-in-progress papers are also allowed (submit 500-word abstracts).
Conference Overview
The Generative Decision Science Conference brings together researchers, policymakers, industry leaders, and practitioners to explore the transformative role of data-driven decision-making in addressing complex societal challenges. Aligned with CODATA’s global mission, the conference emphasises open science, data stewardship, and evidence-based decision-making as critical enablers of inclusive development, particularly in emerging economies. This hybrid conference enables participation from across the globe, allowing delegates to attend either in person in Johannesburg or virtually, thereby expanding access and inclusivity. Importantly, registration for the conference is free, reinforcing the commitment to equitable knowledge sharing and broad participation, especially for researchers and practitioners from the Global South.
Conference Objectives
- Advance scholarship in decision science and data-driven methodologies.
- Promote open data, FAIR principles, and responsible data governance.
- Bridge the gap between research, policy and practice.
- Strengthen collaboration across academia, government, and industry.
- Support early-career researchers and emerging scholars.
- Enable accessible participation through hybrid delivery and free registration.
Themes and Tracks
Track 1: Applied Data Science for Decision-Making:
- Data analytics, machine learning, and predictive modelling.
- Data pipelines and real-time analytics.
- Data visualisation and decision intelligence.
- Big data architectures supporting decision processes.
- Data quality and data integration challenges.
Track 2: Information & Knowledge Management Systems:
- Knowledge management frameworks and strategies.
- Organisational knowledge systems and decision support.
- Knowledge sharing, transfer, and retention.
- Digital knowledge platforms and repositories.
- Information architecture and metadata systems.
Track 3: Data Governance, Stewardship & Open Science:
- Data governance frameworks and policy.
- FAIR data principles implementation.
- Open data ecosystems and data sharing.
- Ethical, legal, and social implications (ELSI).
- Data sovereignty and African data governance models.
Track 4: Decision Science & Decision Support Systems:
- Decision support systems (DSS).
- Multi-criteria decision analysis (MCDA).
- Risk and uncertainty modelling.
- Evidence-based decision-making frameworks.
- Integration of data and knowledge into decision processes.
Track 5: Artificial Intelligence & Knowledge-Driven Decision Systems:
- AI and machine learning in decision environments.
- Explainable AI (XAI) and transparency.
- Human-AI collaboration in decision-making.
- Generative AI in knowledge creation and decision support.
- Algorithmic bias and ethical AI.
Track 6: Applied Data Science & IKM for Sustainable Development:
- Data-driven approaches to the United Nations Sustainable Development Goals (SDGs).
- Climate and environmental data systems.
- Agriculture, health, and energy decision systems.
- Smart cities and urban data ecosystems.
- Public sector data and service delivery.
Track 7: Indigenous Knowledge Systems & Inclusive Data Practices:
- Integration of indigenous knowledge with data science.
- Community-based knowledge systems.
- Data justice and inclusion.
- Multilingual knowledge systems.
- Participatory data governance.
Track 8: Education, Skills & Capacity Development:
- Data literacy and decision-making skills.
- Teaching applied data science and IKM.
- Curriculum innovation and interdisciplinarity.
- Workforce readiness and digital transformation.
- Industry-academic partnerships.
Track 9: Industry Applications & Case Studies:
- Business intelligence and analytics.
- Financial decision systems and fintech.
- Supply chain optimisation.
- Healthcare data systems.
- Real-world applications of data-to-decision pipelines.
For further information please visit the conference announcement.
For more information, authors are welcome to contact the 2026 Programme Committee Co-Chairs. Prof Tanya du Plessis (IKM Chair): tduplessis@uj.ac.za and Dr Kagiso Mabe (CODATA SA Chair): kmabe@uj.ac.za.