What are ontologies, and why do they matter in behavioural science?

Behavioural science often grapples with a familiar problem: as research grows and insights multiply, so do the terms, models, and frameworks we use to describe human behaviour. Different researchers can use different words to talk about the same phenomenon, creating confusion and fragmentation. In a field where precision matters, how can we ensure we’re all speaking the same language?

This is where ontologies come in. Ontologies provide a structured vocabulary for behavioural science, organising concepts and relationships so we can streamline research, integrate data across fields, and collaborate more effectively. Far from being a purely academic exercise, ontologies are a powerful tool for making sense of complex behavioural phenomena.

But why should behavioural scientists—and anyone working to change behaviour—care about ontologies? In this post, we’ll explore the critical role ontologies play in advancing research and creating practical, real-world interventions.

What exactly is an ontology, and why should behavioural scientists care?

Let’s start with the basics. An ontology, in the simplest terms, is a structured map of knowledge—a system for defining the concepts in a field and how they relate to one another. Think of it as a blueprint for understanding a domain. It categorises, organises, and connects key terms, offering a shared language that researchers can use to describe behaviour in a consistent way.

For example, an ontology for health interventions might define the term ‘physical activity’ and its relationship to ‘exercise’ and ‘sedentary behaviour,’ ensuring that studies on different aspects of activity can be meaningfully compared.

More importantly, they help make sense of vast amounts of data. In today’s world, we’re dealing with an overwhelming amount of behavioural data from diverse sources—whether it’s from clinical trials, public health campaigns, or consumer behaviour studies. Ontologies provide the structure needed to organise this data and identify patterns that might otherwise remain hidden.

How do ontologies make behavioural science research more reliable?

Ontologies don’t just organise terms - they offer something far more critical: consistency. When every researcher in a field uses the same framework, we reduce the chance of misinterpretation, miscommunication, or flawed comparisons between studies. This consistency strengthens the reliability of research findings.

Consider this analogy: just as a collapsed bridge is disastrous, inconsistent terminology in behavioural science leads to flawed studies that can’t be replicated or compared. The impact? Wasted resources, missed insights, and potentially flawed interventions.

A real-world example of this issue can be seen in behaviour change interventions. Researchers using inconsistent definitions of behaviour change techniques (BCTs) often produce mixed or contradictory findings. For instance, if 'goal setting' is defined differently across studies, it becomes difficult to determine whether the technique is truly effective. Ontologies solve this by standardising terms, ensuring that studies are comparable and insights more reliable.

Can ontologies improve collaboration across disciplines?

Behaviour doesn’t happen in a vacuum—it’s influenced by everything from social norms to economic factors, cultural contexts, and even genetics. As a result, behavioural science is inherently interdisciplinary, often requiring collaboration between psychologists, economists, sociologists, and even biologists. But each of these fields brings its own language and methods, making effective collaboration a challenge.

Ontologies act as a translator between disciplines, providing a shared framework that different fields can use to describe and study behaviour. For example, cognitive scientists studying decision-making might collaborate with geneticists examining behavioural predispositions, using a common ontology to link their findings. By having a unified framework, researchers can share data more easily, cross-reference their findings, and ultimately develop a more holistic understanding of behaviour.

This kind of interdisciplinary collaboration is increasingly important as we tackle complex behavioural challenges, from improving public health outcomes to understanding the psychological impacts of climate change. The more fields can integrate their knowledge, the more impactful their interventions can become.

What are some real-world applications of ontologies?

While ontologies may seem abstract, their applications in the real world are anything but. Here are just a few examples of how ontologies are already helping advance behavioural science:

Public health: The Human Behaviour-Change Project is a prime example of how ontologies are used to structure and categorise behaviour change techniques (BCTs) in health interventions. The project maps and compares interventions—like smoking cessation programmes—ensuring that practitioners can design more effective, evidence-based strategies. By organising successful interventions through an ontology, it’s possible to build better, more targeted strategies for improving health outcomes.
Consumer behaviour: Companies like Amazon and Zalando use ontologies to better understand and predict consumer behaviour. By mapping customer decisions, they can tailor marketing strategies or customer engagement initiatives. For example, ontologies help track online shopping behaviours, identifying which factors are most likely to drive a customer from browsing to purchasing. This allows companies to create personalised recommendations that increase customer satisfaction and sales.
Cognitive science: Researchers studying cognitive processes such as attention, decision-making, or memory use ontologies to connect different theoretical models. This helps create more integrated models of behaviour, combining insights from psychology, neuroscience, and artificial intelligence.

In each of these fields, ontologies provide the backbone for organising knowledge and making sense of complex, dynamic behaviours. As behavioural science continues to grow, the need for clear, structured ontologies will only increase.

Why ontologies are essential—but also just the beginning

Ontologies are more than abstract frameworks—they’re the foundation that helps researchers make sense of behavioural science, enabling collaboration and real-world impact. Whether you're designing a public health intervention, studying consumer behaviour, or working across disciplines, ontologies provide the shared language and structure needed to manage complex data and insights.

In the next post, we’ll explore the challenges that come with using ontologies, especially when it comes to capturing the messy reality of human behaviour. Can they oversimplify what makes us human, or do they help us see patterns we’d otherwise miss? Stay tuned as we dig deeper into the limits and possibilities of ontologies in behavioural science.

What are ontologies, and why do they matter in behavioural science?

What exactly is an ontology, and why should behavioural scientists care?

How do ontologies make behavioural science research more reliable?

Can ontologies improve collaboration across disciplines?

What are some real-world applications of ontologies?

Why ontologies are essential—but also just the beginning

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