Datafront Skill Surge: Future directions in interdisciplinary research

Course description

What do we mean when we talk about administrative data? Why is administrative data considered such a powerful tool?

Routinely collected administrative data captures interactions across the entire population, offering an unparalleled breadth and depth of information.

This on-demand series aims to equip researchers with the knowledge and skills to harness data for societal and sustainable change. This series covers important topics such as the use of administrative data in policymaking, circular economy models, climate resilience, and the impact of digital media on behaviour, with emphasis on the importance of interdisciplinary collaboration and innovative strategies to address global challenges.

Participants will gain insights from experts, study case studies, and explore practical examples that illustrate how data-driven approaches and emerging technologies are transforming urban planning, agriculture, and health – that will empower researchers to shape the future of the data landscape!

• Session 35 we’ll address one of the most layered, difficult, and crucial aspects of research – ethics and social impact.

 

Learning mode

On-demand, self-paced 

 

Who should attend

This course is intended for:

• Data Analysts and Researchers: Those working with administrative or big data who want to deepen their understanding of its characteristics and uses.
• Policymakers and Government Officials: Decision-makers who rely on data to shape public policies.
• Public Sector Managers: Managers in government institutions seeking to optimise data usage for service improvements.
• Health and Social Care Professionals: Individuals looking to use data for improving service delivery and outcomes.
• Urban Planners and Public Health Professionals: Individuals interested in using administrative data to inform planning and health policies.

 

Aims and objectives

• Explore emerging shifts in the role, structure, and expectations of interdisciplinary research.
• Examine the growing importance of co-creation, systems integration, and anticipatory practice.
• Identify barriers to innovation, including institutional inertia and outdated research incentives.

 

Skills area and competencies

Based on the Datacise Open Learning framework, the relevant skills and competencies for this video include:

Skills Areas:

• Strategic Foresight and Futures Thinking: Ability to anticipate and plan for long-term implications of research decisions.
• Systems Integration and Design: Skills in aligning data, knowledge, and action across sectors and infrastructures.
• Transdisciplinary Practice: Capacity to work with non-academic partners in co-creating meaningful, implementable research.

Competencies:

• Governance and Policy Literacy: Understanding how research interfaces with decision-making structures and regulatory ecosystems.
• Ethical Anticipation: Competence in evaluating downstream impacts, emergent risks, and justice-oriented outcomes.
• Collaboration Infrastructure Agility: Ability to work across digital platforms, distributed teams, and hybrid collaboration models.

 

Pre-requisite

• Familiarity with challenges in research-policy-community interfaces.
• Interest in futures thinking, co-creation, or transdisciplinary transformation.
• Openness to navigating ethical, political, and institutional tensions in research design.

 

Learning outcomes

• Identify strategic shifts shaping the future of interdisciplinary research.
• Articulate the importance of transdisciplinarity, systems integration, and co-creation.
• Recognise ethical and institutional barriers to adaptive and responsible research.

 

Transferable skills

• Futures Literacy: Capacity to explore multiple possible, plausible, and preferable futures in research design.
• Scenario Analysis: Ability to anticipate unintended consequences and stress-test research strategies.
• Strategic Collaboration: Skills to lead and participate in hybrid, distributed, and co-creative research teams.

 

Assessment

Multiple choice quiz to self-check understanding. 

 

This training content was originally developed and produced by Professor Adam Chee, Datacise Education Lead at Swansea University, with narration enhanced by advanced text-to-speech technology.