By Steven E. Wallis and Bernadette Wright
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.
Practical mapping is based on research showing that we are better at understanding situations and reaching desired goals when our knowledge is more ‘structured.’ We can see the structure of our knowledge by diagramming it to create a map. Below is a simple hypothetical example of a map showing concepts (in boxes) connected by causal arrows. (This simple example is not intended to be a complete or accurate map.)
Each box represents something that can be described and measured in the real world (a variable). Each arrow represents the cause-and-effect relationship between the boxes (to the best of our collective understanding).
We can ‘read’ each arrow on the map as “more of this causes more of that.” Starting at the bottom and moving up to the right, you can see that, according to this map, the more taxes that are paid to the state, the more funds there will be for educational programs, which in turn leads to more educational programs, and that leads to more people with work skills – and so on.
In the above (hypothetical) example, the light-shaded boxes come from research related to the business community while the darker-shaded boxes are from researchers in education. The darkest boxes are where their research overlaps – the concepts are of direct relevance to researchers from both fields – where their research results overlap and so where their perspective maps may be synthesized.
Creating your own map
To create a map for your research topic, use information from a variety of sources, such as academic research, trade publications, interviews with experts, and stakeholders. Maps can show knowledge from qualitative, quantitative or mixed methods. As in any knowledge pursuit, more data sources are better.
Start by reading the text found in the research results from your sources. Find the concepts (whatever was measured); then identify the causal relationships. For example, a report from the business side might say something like, “When our businesses grow from collaborative marketing, we will need to hire more workers.” That might ‘translate’ into the language of boxes and arrows as shown in the above figure’s upper-right hand corner (Correction January 2023, this should read upper-left hand corner).
Once you get used to the mapping process, you can more easily create maps incorporating research results from other disciplines. And, you can more easily collaborate with scholars and practitioners from other disciplines to help them create maps and merge them with yours to create a more complete picture.
A particular benefit of practical mapping in supporting interdisciplinary collaboration is that it provides a ‘common language’ of measurement and causality. By looking at how the concept in each box is measured, and if research has inferred any causal relationships between the concepts, it overcomes a common problem where researchers miss valuable studies from other fields when they use different terms to describe the same thing.
Do you already use some (or all) aspects of the practical mapping approach? What kinds of mapping have you used for interdisciplinary collaborations? What has worked well, and what might be done better?
To find out more and for step-by-step instructions, with additional free handouts and guides, see:
Wright, B. and Wallis, S. E. (2019). Practical Mapping for Applied Research and Program Evaluation. Sage, Thousand Oaks, California, United States of America (Online handouts): https://practicalmapping.com/
Biography: Steven E. Wallis PhD is the director of the Foundation for the Advancement of Social Theory. His research is focused on structural perspectives of knowledge to accelerate the development of more useful theory, within and between disciplines, to help individuals and organizations more easily reach their highest goals.
Biography: Bernadette Wright PhD founded Meaningful Evidence to help nonprofits leverage social research to make a bigger impact. She works with nonprofits that are advancing social justice and public well-being in the areas of health, human services, and education.
When I give advice to interdisciplinary research teams I always encourage them to draw a map of their problem. It helps them reflect on the complexity of their research problem, the expertise they need, and the theories and methods they want to apply. One challenge is deciding where to limit a particular inquiry, since all of the boxes in any diagram are also connected to lots of boxes that are not on the diagram.
(I liked your book!)
Rick, glad you liked our book! I’ll list your statement as a very short book review 😉 Great idea to have teams start by mapping the problem! The challenge you mention (deciding where to limit a particular inquiry) is common among creative big-thinkers! We go by the rule that while everything in the universe is connected… some things are more connected than others. So, after the team has been working on the map for a while, they may see a pattern start to emerge. A “core” of highly connected concepts and a “belt” of loosely connected concepts (a very messy example here in this map of economic concepts: https://kumu.io/Steve/core-of-potus ). Depending on the relevance of the concepts, the team may want to focus on finding more connections within the core and set aside (at least temporarily) the concepts in the belt. This helps the team move toward “conceptual closure” where all concepts of the map are highly causally interconnected. More on closure in this academic article: https://onlinelibrary.wiley.com/doi/abs/10.1002/sres.2680
Related post with robust comment discussion here: https://i2insights.org/2017/03/30/knowledge-mapping-technologies/
Bethany – good resource for comparing different approaches to mapping! My research suggests a very similar arrangement with “fuzzy” (or no connections) on the bottom (easy to create, not so useful in practical application) and causal mapping at the top (more difficult and also more useful) and concept mapping somewhere in the middle. I would say that more robust maps are better no matter what kind of map we are using. In addition to evaluating the robustness of causal maps with IPA, concept maps can be evaluated using a “systemicity” approach (from developmental psychology and education fields). We have yet to determine if a highly robust concept map might be better (more useful) than a low-robust causal map.
More insights buried in this academic article: https://onlinelibrary.wiley.com/doi/abs/10.1002/sres.2680
Bruce, Excellent point. I agree that small simple example maps are often misleading and not very useful for developing successful solutions to complex issues!
I acknowledge your caveat – “This simple example is not intended to be a complete or accurate map”, but would offer the opinion that such linear cause-effect diagrams do not advance the understanding of knowledge flow in practice for complex issues of social justice, poverty and unemployment. To leave out the interdependencies between each of the boxes, (emphasising flow in only one direction) highlights why so many programs fail. Each of the nodes needs something for each of the other nodes within the boundaries of the mapping exercise to behave in an optimal way. Maps, presented in the form outlined here, often mislead because of the absence of that critical systems’ property ‘coherence’.
Bruce – Absolutely! As more perspectives are added to the map (from various disciplines and/or fields of practice) the concepts become more causally interconnected and so more useful for understanding situations and action planning. I’m not sure if you’ve heard but, we can now measure that coherence in our maps. This measure provides a kind of compass pointing the way to improving our maps. Because most maps have little coherence (they seem to be made at around the 20% level) there is a great opportunity to advance every field of scholarship and practice (imagine a world where our plans and policies for resolving social problems were twice as effective). The basics for evaluating the structure/robustness of maps may be found here: [Moderator note – as at October 2021, this link was broken: projectfast[dot]org … basics-of-ipa/]. And, for use with tabletop mapping among stakeholders, you might be interested in our award winning paper here: https://absel-ojs-ttu.tdl.org/absel/index.php/absel/article/view/2899
Thanks for engaging with this point. In my mapping work I find the simple question – what does A need from B to optimise its outcomes? and what does B need from A to optimise its outcomes? and so on for all the related nodes. The negotiations between the nodes enables the whole system to optimise rather than one node over another. Obviously this form of mapping works best where the conversation is focussed on functions of a system rather than structures and where the actors within a function are speaking on behalf of the function. I find that these conversations to better understand coherence contribute significantly to cross disciplinary understanding and collaboration.
Bruce, I completely agree. In our work with stakeholders, we help them to create a complex map of many interconnected elements/concepts/functions. That map serves to focus the conversation – makes action planning very easy. It also helps to promote transparency and accountability. In contrast, using a simple map with few causal connections is likely to lead to confusion, competition, and blaming – even among groups that are striving for the same goal. This is seen in a “daisy petal” diagram – an example in this recent piece on defunding police: [Moderator note – as at October 2021, this link was broken: projectfast[dot]org … Defunding-police.docx]. Instead, we encourage people to look for interdependent goals where, as you say, each is optimized by the other.