What do we mean by co-labouring? What practices does it involve? How can it enhance interactions among researchers and key stakeholders in transdisciplinary research?
Choosing the notion of ‘co-labouring’ in our transdisciplinary project stems from an awareness that creating alternative perspectives, eg., on sustainable futures for mining, is a complex endeavor. Ideas of researchers wanting to give voice to unheard groups at the margin are too often based on simple models of translation. These assumptions underestimate what gets lost in translation, or the gaps in understandings between different groups of stakeholders.
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.
In the right circumstances, a cartoon video can be an effective way to communicate research information. But what’s involved in developing a cartoon video?
This blog post is based on our experience as a Chinese-Australian partnership in developing an educational cartoon video (The Magic Glasses, link at end of post) which aimed to prevent soil-transmitted helminths (parasitic worm) infections in Chinese schoolchildren. We believe that the principles we applied are more broadly applicable and share them here.
What is the groan zone in collaboration? What can you do when you reach that point?
As researchers and practitioners engaged in transdisciplinary problem-solving, we know the value of diverse perspectives. We also know how common it is for groups to run into challenges when trying to learn from diverse ideas and come to consensus on creative solutions.
This challenging, often uncomfortable space, is called the groan zone. The term comes from Sam Kaner’s diamond model of participation shown in the figure below. After an initial period of divergent thinking, where diverse ideas are introduced, groups have to organize that information, focus on what’s most important, and make decisions in order to move forward into the phase of convergent thinking.
How can researchers and policy makers work together to foster more systematic uptake of research in policy making?
In a series of workshops at the European Commission Joint Research Centre’s Evidence and Policy Summer School on migration and demography, participants identified some of the most critical stages where scientists and policymakers interact: problem definition, research process, and communication of results. We then built up a bank of practical ideas and suggestions for each stage.
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.
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?
How do a group’s perceptions change over time, when members across a range of institutions are brought together at regular intervals to synthesize ideas? Synthesis centers have been established to catalyze more effective cross-disciplinary research on complex problems, as described in the blog post ‘Synthesis centers as critical research infrastructure‘, by Andrew Campbell.
I co-led a group synthesizing ideas about participatory modeling as one of the activities at the National Socio-Environmental Synthesis Center (SESYNC). We met in Annapolis, Maryland, USA, four times over three years for 3-4 days per meeting. Our task was to synthesize what is known about participatory modeling tools, processes, and outcomes, especially in environmental and natural resources management contexts.
How can we improve interdisciplinary collaborations? There are many lessons to be learned from the Science of Team Science. The following ten lessons summarize many of the ideas that were shared at the International Science of Team Science Conference in Galveston, Texas, in May 2018.
1. Team up with the right people
On the most basic level, scientists working on teams should be willing to integrate their thoughts with their teammates’ ideas. Participants should also possess a variety of social skills, such as negotiation and social perceptiveness. The most successful teams also encompass a moderate degree of deep-level diversity (values, perspectives, cognitive styles) and include women in leadership roles.
By Katrine Lindvig, Line Hillersdal and David Earle
How can we resolve the stark disparity between theoretical knowledge about interdisciplinary approaches and practical applications? How can we get from written guidelines to actual practices, especially taking into account the contextual nature of knowledge production; not least when the collaborating partners come from different disciplinary fields with diverse expectations and concerns?
For the past few years, we have been developing ways in which academic theory and physical interactions can be combined. The result is CoNavigator – a hands-on, 3-dimensional and gamified tool which can be used:
for learning purposes in educational settings
as a fast-tracking tool for interdisciplinary problem solving.
CoNavigator is a tool which allows groups to collaborate on a 3-dimensional visualisation of the interdisciplinary topography of a given field or theme. It addresses the contextual and local circumstances and the unique combinations of members in collaborative teams. CoNavigator is therefore short for both Context Navigation and Collaboration Navigation. The process of applying the tool takes around 3 hours.
CoNavigator is composed of writable tiles and cubes to enable rapid, collaborative visualisation, as shown in the first figure below. The tactile nature of the tool is designed to encourage collaboration and negotiation over a series of defined steps.
Making the Tacit Visible and Tangible
Each participant makes a personal tool swatch. By explaining their skills to a person with a completely different background, the participant is forced to re-evaluate, re-formulate, and translate skills in a way that increases their own disciplinary awareness. Each competency that is identified is written onto a separate tool swatch.
Can boundary objects be designed to help researchers and decision makers to interact more effectively? How can the socio-political setting – which will affect decisions made – be reflected in the boundary objects?
Here I describe a new context-specific boundary object to promote decision making based on scientific evidence. But first I provide a brief introduction to boundary objects.