Breaking through disciplinary barriers with practical mapping

By Steven E. Wallis and Bernadette Wright

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1. Steven E. Wallis (biography)
2. Bernadette Wright (biography)

How can practical mapping help develop interdisciplinary knowledge for tackling real-world problems — such as poverty, justice and health — that have many causes? How can it help take into account political, economic, technological and other factors that can worsen or improve the issues?

Maps are useful because they show your surroundings – where things are in relation to each other (and to you). They show the goals we want to achieve and what it takes to get there.

‘Practical mapping’ is a straight-forward approach for using concepts and connections to integrate knowledge across and between disciplines, to support effective action.

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Providing a richer assessment of research influence and impact

By Gabriele Bammer

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Gabriele Bammer (biography)

How can we affirm, value and capitalise on the unique strengths that each individual brings to interdisciplinary and transdisciplinary research? In particular, how can we capture diversity across individuals, as well as the richness and distinctness of each individual’s influence and impact?

In the course of writing ten reflective narratives (nine single-authored and one co-authored), eleven of us stumbled on a technique that we think could have broader utility in assessing influence and impact, especially in research but also in education (Bammer et al., 2019).

Read moreProviding a richer assessment of research influence and impact

Theory U: A promising journey to embracing unknown unknowns

By Vanesa Weyrauch

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Vanesa Weyrauch (biography)

How can we best live in a VUCA (volatile, uncertain, complex and ambiguous) world? How can we shift from a worldview that looks to predict and control what is to be done through plans and strategies to being present and flexible in order to respond effectively as unexpected changes take place? How can we be open to not knowing what will emerge and embrace uncertainty as the opportunity to co-create and learn?

One powerful and promising way forward is Theory U, a change methodology developed by Otto Scharmer and illustrated below. Scharmer introduced the concept of “presencing”—learning from the emerging future. The concept of “presencing” blends “sensing” (feeling the future possibility) and “presence” (the state of being in the present moment). It acknowledges that we don’t know the answers. Staying at the bottom of the U until the best potential future starts emerging requires embracing uncertainty as fertile soil.

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Blackboxing unknown unknowns through vulnerability analysis

By Joseph Guillaume

Author - Joseph Guillaume
Joseph Guillaume (biography)

What’s a productive way to think about undesirable outcomes and how to avoid them, especially in an unpredictable future full of unknown unknowns? Here I describe the technique of vulnerability analysis, which essentially has three steps:

  • Step 1: Identify undesirable outcomes, to be avoided
  • Step 2: Look for conditions that can lead to such outcomes, ie. vulnerabilities
  • Step 3: Manage the system to mitigate or adapt to vulnerable conditions.

The power of vulnerability analysis is that, by starting from outcomes, it avoids making assumptions about what led to the vulnerabilities.

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Designing scenarios to guide robust decisions

By Bonnie McBain

Bonnie McBain (biography)

What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:

  • goals;
  • design; and,
  • use and defensibility.

Goals of scenarios

Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures.

Read moreDesigning scenarios to guide robust decisions

Agent-based modelling for knowledge synthesis and decision support

By Jen Badham

Jen Badham (biography)

The most familiar models are predictive, such as those used to forecast the weather or plan the economy. However, models have many different uses and different modelling techniques are more or less suitable for specific purposes.

Here I present an example of how a game and a computerised agent-based model have been used for knowledge synthesis and decision support.

The game and model were developed by a team from the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), a French agricultural research organisation with an international development focus. The issue of interest was land use conflict between crop and cattle farming in the Gnith community in Senegal (D’Aquino et al. 2003).

Agent-based modelling is particularly effective where understanding is more important than prediction. This is because agent-based models can represent the real world in a very natural way, making them more accessible than some other types of models.

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Managing uncertainty in decision making: What can we learn from economics?

By Siobhan Bourke and Emily Lancsar

Siobhan Bourke (biography)

How can researchers interested in complex societal and environmental problems best understand and deal with uncertainty, which is an inherent part of the world in which we live? Accidents happen, governments change, technological innovation occurs making some products and services obsolete, markets boom and inevitably go bust. How can uncertainty be managed when all possible outcomes of an action or decision cannot be known? In particular, are there lessons from the discipline of economics which have broader applicability?

Read moreManaging uncertainty in decision making: What can we learn from economics?

Idea tree: A tool for brainstorming ideas in cross-disciplinary teams

By Dan Stokols, Maritza Salazar, Gary M. Olson, and Judith S. Olson

Dan Stokols (biography)

How can cross-disciplinary research teams increase their capacity for generating and integrating novel research ideas and conceptual frameworks?

A key challenge faced by research teams is harnessing the intellectual synergy that can occur when individuals from different disciplines join together to create novel ideas and conceptual frameworks. Studies of creativity suggest that atypical (and often serendipitous) combinations of dissimilar perspectives can spur novel insights and advances in knowledge. Yet, many cross-disciplinary teams fail to achieve intellectual synergy because they allot insufficient effort to generating new ideas. Here we describe a brainstorming tool that can be used to generate new ideas in cross-disciplinary teams.

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Toolboxes as learning aids for dealing with complex problems

By Stefan Hilser

Stefan Hilser (biography)

How can toolboxes more effectively support those learning to deal with complex societal and environmental problems, especially novices such as PhD students and early career researchers?

In this blog post, I briefly describe four toolboxes and assess them for their potential to assist learning processes. My main aim is to open a discussion about the value of the four toolboxes and how they could better help novices.

Before describing the toolboxes, I outline the learning processes I have in mind, especially the perspective of legitimate peripheral participation.

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Conceptual modelling of complex topics: ConML as an example / Modelado conceptual de temas complejos: ConML como ejemplo

By Cesar Gonzalez-Perez

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Cesar Gonzalez-Perez (biography)

A Spanish version of this post is available

What are conceptual models? How can conceptual modelling effectively represent complex topics and assist communication among people from different backgrounds and disciplines?

This blog post describes ConML, which stands for “Conceptual Modelling Language”. ConML is a specific modelling language that was designed to allow researchers who are not expert in information technologies to create and develop their own conceptual models. It is useful for the humanities, social sciences and experimental sciences.

Read moreConceptual modelling of complex topics: ConML as an example / Modelado conceptual de temas complejos: ConML como ejemplo

Scatterplots as an interdisciplinary communication tool

By Erin Walsh

erin-walsh
Erin Walsh (biography)

Scatterplots are used in many disciplines, which makes them useful for communicating across disciplines. They are also common in newspapers, online media and elsewhere as a tool to communicate research results to stakeholders, ranging from policy makers to the general public. What makes a good scatterplot? Why do scatterplots work? What do you need to watch out for in using scatterplots to communicate across disciplines and to stakeholders?

What makes a good scatterplot?

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Skilful conversations for integration

By Rebecca Freeth and Liz Clarke

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1. Rebecca Freeth (biography)
2. Liz Clarke (biography)

Interdisciplinary collaboration to tackle complex problems is challenging! In particular, interdisciplinary communication can be very difficult – how do we bridge the gulf of mutual incomprehension when we are working with people who think and talk so very differently from us? What skills are required when mutual incomprehension escalates into conflict, or thwarts decision making on important issues?

It is often at this point that collaborations lose momentum. In the absence of constructive or productive exchange, working relationships stagnate and people retreat to the places where they feel safest: their own disciplines, their offices, or the colleagues who are on their ‘side’. As a consequence, prospects for meaningful collaboration and integration dwindle.

One of the difficulties of interdisciplinary collaboration is being able to express the brilliant ideas swimming around in our own heads so that they can (a) be understood by others and (b) contribute to mutual insights and integration.

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