Looking for patterns: An approach for tackling tough problems

Community member post by Scott D. Peckham

Scott D. Peckham (biography)

What does the word ‘pattern’ mean to you? And how do you use patterns in addressing complex problems?

Patterns are repetitions. These can be in space, such as patterns in textiles and wallpaper, which include houndstooth, herringbone, paisley, plaid, argyle, checkered, striped and polka-dotted.

The pattern concept can also be applied to repetitions in time, as occur in music. Those who know the temporal patterns can classify a piece of music as a blues, waltz or salsa. For each of these types of music, there are also classic dance steps, that usually go by the same name; these are patterns of movement in space and time.

These examples get to the idea that patterns can be viewed more generally as any type of repetitive structure or recurring theme that we can look for and potentially recognize or discover and then assign a memorable name to, such as “houndstooth” or “waltz”. Recognizing the pattern may then indicate a particular course of action, such as “perform dance moves that go with a waltz”.

The ability to recognize a pattern and then take appropriate action is something that we associate with intelligence. Indeed, “pattern recognition” is one of the big topic areas in artificial intelligence and has led to the development of self-driving cars, Siri and machines that “read”.

We also gain new respect for ancient peoples when we learn of the patterns that they were able to recognize and then use to solve problems. One fascinating example is the way that ancient Polynesians were able to navigate across huge expanses of ocean to tiny islands by reading the patterns of the waves, a skill they taught to their children with the use of stick charts. Archaeoastronomy also provides many examples, where druids, Aztecs and other ancient peoples observed the spatio-temporal patterns of celestial objects, then learned to develop calendars and predict future events.

In thinking about patterns, it is useful to consider the verbs that we associate with patterns, such as recognize, discern, perceive, detect, notice and identify. These all show that we attach value to patterns and tend to actively seek them. The concept of a pattern allows for some fuzziness and is not about exact matches; it is more about grouping things based on structural similarities that are important in a given, possibly abstract, context.

There are a variety of algorithms and mathematical methods for detecting patterns in data sets. These fall under the banner of classification or segmentation schemes. The starting point for this type of analysis is a data set where each record in the data set corresponds to a particular observation (eg., a system state, occurrence or an individual) and each record has several fields that describe the (often numerical) attributes of that observation.

Given such data sets with large numbers of observations, there are methods such as factor analysis, principal component analysis, empirical orthogonal functions and cluster analysis that can be used to find hidden structure. Some attributes are typically correlated with others, and a particular subset of combination of attributes may turn out to provide strong explanatory or discriminating power for classifying observations into groups or classes. Data scientists then attempt to find the minimal set of attributes that lead to reliable classification.

Examples include efforts to better understand human behavior and personality patterns. Two specific instances are the development of OCEAN and the Myers-Briggs Type Indicator. In OCEAN (also known as the Big 5 Personality Traits), each letter in the acronym stands for a personality trait, namely: openness to experience, conscientiousness, extroversion, agreeableness and neuroticism. Many independent studies have shown these 5 traits to be good discriminators. The Myers-Briggs Type Indicator is similar and distinguishes between 16 distinct personality types or patterns.

Patterns are typically given relatively short, memorable names and these names are important and efficient elements of human communication. Sometimes the names refer to well-known stories that epitomize a particular pattern, such as Pandora’s box, Achilles’ heel, Good Samaritan, boy who cried wolf, Solomon and the baby, or David and Goliath. Sometimes they refer to familiar problem-solving strategies, such as “good cop, bad cop”, “top down” and “Devil’s advocate”. Sometimes they refer to a type of scenario, as with all of Aesop’s fables and well-known logical fallacies such as “red herring” and “slippery slope”. Genres like “romantic comedy” and plot lines like “boy meets girl” are also patterns.

In each case, they represent a useful template for recognizing a common situation and often indicate a particular, corresponding action.

As food for thought, here are some specific examples of relatively complex problems and how the identification of a pattern helps to find a solution.

  • Committing a robbery: A criminal “cases a joint” over a period of time, looking for patterns that he can exploit. (eg., the guard takes a break at 11 pm).
  • Catching criminals: A detective uses “offender profiling” to identify possible suspects or future criminals, using the fact that people who commit a particular type of crime often share a certain pattern of physical and psychological attributes. In addition, there is often a pattern associated with the crimes of an individual, known as their modus operandi or MO. Handwriting and speech pattern analysis are also used.
  • Winning poker games: A poker player learns to recognize the involuntary “tells” of other players, in order to predict what type of hand they have, or to bluff.
  • Increasing profits: A corporate data scientist identifies the purchasing patterns of customers through data mining and customer segmentation, so that different types of customers receive different ads and coupons in the mail or during online searching.
  • Avoiding scams: A consumer learns to recognize the patterns of several known types of scams and then avoid them. Each type of scam has a name such as “bait and switch”, “pyramid scheme” and “shell game”.
  • Winning a court case: A lawyer looks for and utilizes legal precedents with names like “X v. Y” that share important similarities to their own case.

Patterns are also important in a research context, as the following examples illustrate.

  • Speeding up software development: A software developer reads a book about software design patterns and best practices in order to determine whether her problem is a variant of a common pattern for which there are known, reusable solutions that can be rapidly implemented. Examples include the “adapter pattern” and the “decorator pattern”.
  • Understanding the Earth system: A geoscientist realizes that there are recurring weather and climate patterns, such as El Nino and the North Atlantic Oscillation that can help us to better understand and then predict the onset of droughts and floods.

This blog post sets the scene for two related blog posts that will be published next week on how patterns can transmit ‘know-how’ knowledge about modelling practices. 

What other examples of patterns do you have to share? More particularly, can you provide examples about where patterns play a role in solving a difficult problem?

Recommended Reading:
Australian Competition and Consumer Commission (ACCC). (2016). The Little Black Book of Scams. Commonwealth of Australia: Canberra, Australia. Online: https://www.accc.gov.au/publications/the-little-black-book-of-scams

Davenport, W. H. (1964). Marshall Islands cartography, Expedition Magazine (The Bulletin of the University Museum of Pennsylvania), 6, 4: 10 -13.

Duhigg, C. (2012). How companies learn your secrets. The New York Times Magazine, February 16, 2012.

Gamma, E., Helm, R., Johnson, R. and Vlissides, J. (1994). Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley: Boston, United States of America.

Kessler, S. (2015). The 5 Personality Patterns: Your Guide to Understanding Yourself and Others and Developing Emotional Maturity. Bodhi Tree Press: Richmond, California, United States of America.

Parry, W. (2011). How to spot psychopaths: Speech patterns give them away. Online: http://www.livescience.com/16585-psychopaths-speech-language.html

Pickett, M., Tar, C. and Strope, B. (2016). On the personalities of dead authors. Online:  https://research.googleblog.com/2016/02/on-personalities-of-dead-authors.html

Van De Oudeweetering, A. (2014). Improve your chess pattern recognition: Key moves and motifs in the middlegame. New in Chess: Alkmaar, The Netherlands.

Winerman, L. (2004). Criminal profiling: The reality behind the myth. Monitor on Psychology, 35, 7: 66.

Biography: Scott D. Peckham PhD is a Senior Research Scientist at the Institute of Arctic and Alpine Research (INSTAAR) at the University of Colorado, Boulder. His science research is mainly in hydrology and fluvial landscape evolution, with expertise in fluid dynamics, digital terrain analysis, mathematical modeling, scaling theory, stochastic processes, software development and cyber-infrastructure. He is author of many open-source computational models, most of which are available in a Python package called TopoFlow 3.5. He is also author of an innovative, automatic model coupling framework called EMELI (Experimental Modeling Environment for Linking and Interoperability). He is a member of the Core Modeling Practices pursuit funded by the National Socio-Environmental Synthesis Center (SESYNC).

This blog post is the first of a series resulting from the third meeting in April 2017 of the Core Modelling Practices pursuit. This pursuit is part of the theme Building Resources for Complex, Action-Oriented Team Science funded by the National Socio-Environmental Synthesis Center (SESYNC).

Impacts of social learning in transformative research

Community member post by Flurina Schneider, Lara M. Lundsgaard-Hansen, Thoumthone Vongvisouk, and Julie G. Zähringer

Flurina Schneider (biography)

How can science truly support sustainability transformations?

In our research projects we often find that the very process of co-producing knowledge with stakeholders has transformative impacts. This requires careful design and implementation. Knowledge co-production in transdisciplinary and other research leads to social learning and can make a difference in the lives of those involved.

Lara M. Lundsgaard-Hansen (biography)

Knowledge co-production is, therefore, not only a cognitive endeavour that will result in new, action-oriented knowledge, but also a broad social learning process that includes relational, normative, and emotional dimensions.

The following three examples from recent research on sustainable land use and poverty alleviation in Laos and Myanmar illustrate how it can work.

Thoumthone Vongvisouk (biography)

Local land users see their environment with new eyes

In both countries, we conducted participatory mapping exercises to investigate land use changes since 2000. Researchers and local land users mapped current and past land uses by bringing together the local land users’ understanding of their surrounding landscapes and the information provided by high-resolution satellite images. Joint field walks were another key part of the method.

Julie G. Zähringer (biography)

During these exercises, several participants expressed their enjoyment as they gained a better understanding of changes in their environment. For example, during a field walk in Laos to a remote forest boundary, two local participants were surprised by the extensive land use changes that had taken place; they had not visited the spot in a long time. In Myanmar, one participant took part in three field walks and learned how to interpret satellite images, which he had never seen before. He was very enthusiastic about this new skill, which led to considerable adjustment in his spatial understanding of the village’s land uses.

Interestingly, Klaus Hubacek and Christina Prell, in their blog post, also noted the value – in a completely different context – of participation by walking the land together.

Women reflect on their well-being and how to achieve it

To examine how land use changes have affected villagers’ well-being, we conducted separate focus groups with men and women. Participants discussed what they consider to be important for their well-being, and how their ability to achieve well-being has changed since 2000.

In both Laos and Myanmar, the women’s groups were particularly active in these discussions. Several women independently expressed their gratitude for the focus groups, as they learned a lot about the requirements for achieving well-being in their village. For example, by reflecting systematically on the well-being situation in their village and what they had already achieved, they began to see more clearly what the priorities for further actions should be.

Emotional relief in post-conflict situations

Our research also involved villages inhabited by ethnic minority groups. In Myanmar, we worked in a village inhabited by Karen people, who, until a few years ago, had been heavily affected by the civil war and military dictatorship. They experienced countless land expropriations and human rights violations, especially between 1995 and 2001.

At the beginning of our research, these villagers were suspicious of getting involved, so we adapted our plans and emphasized trust building. After a few days, the village spokesperson gave a very emotional public speech. He said that he never dreamed it would be possible, after 40 years of isolation and suppression, to sit with foreigners and Myanmar people of other ethnic groups to jointly discuss the problems the Karen had been, and still were, facing in their village. He also said that he trusted our research team because we seemed to believe in human rights, and that our research was being conducted with good intentions, especially that of helping the village to find justice again. He described his emotions as finally feeling much “lighter”.


The three examples illustrate that transdisciplinary research involving knowledge co-production can change the participants’ knowledge, values, relationships, and emotional states. Jane Palmer also describes a way of tapping into these deep issues for stakeholders in her blog post on transdisciplinary research as story-telling ethnography.

From an academic perspective, these transformative impacts might be viewed as minor, or as side-effects of the actual research. However, we believe that these learning processes are immediately tangible for the stakeholders involved and should therefore be regarded as important impacts of transdisciplinary research projects striving for sustainability transformations. To achieve such tangible results, research interactions with stakeholders must be designed as processes that are meaningful not only for the researchers, but also for the stakeholders.

What are your experiences with knowledge co-production and social learning? What methods have you found to be particularly useful? What powerful outcomes have you seen? We look forward to learning about your experiences.

Biography: Flurina Schneider is an integrative geographer and head of the Land Resources Cluster at the Centre for Development and Environment (CDE), University of Bern, Switzerland. Her research focuses on sustainability, justice, and human well-being in relation to land and water resources. She is particularly interested in how science, knowledge co-production and participation can contribute to sustainability transformations.

Biography: Lara Lundsgaard-Hansen is a PhD candidate at the Centre for Development and Environment (CDE) and the Institute of Geography at the University of Bern, Switzerland. She lives and works in Yangon, Myanmar. She is particularly interested in sustainable development in emerging countries, especially how communities can achieve a thriving economy without harming nature and social equity. In her PhD research, she focuses on land governance in rural areas of Southern Myanmar.

Biography: Thoumthone Vongvisouk is a senior researcher at the Faculty of Forest Sciences at the National University of Laos. He has more than ten years of research experience on the interactions between natural resource governance, land use and rural people’s livelihoods in Laos. He is a geographer with a PhD in natural resource management and rural people’s livelihoods from the Faculty of Sciences at the University of Copenhagen, Denmark.

Biography: Julie G. Zähringer is a senior scientist at the Centre for Development and Environment (CDE) at the University of Bern, Switzerland. She is an environmental scientist with a PhD in geography and sustainable development and a strong interest in social-ecological systems in least-developed countries. In her current research, she focuses on the interlinkages between land use changes, ecosystem services, and human well-being in the context of land investments and conservation in East Africa and Southeast Asia.

Methods for integration in transdisciplinary research

Community member post by Matthias Bergmann

Matthias Bergmann (biography)

To make progress in contributing to the solution of complex real-world problems, transdisciplinary research has come to the forefront. By integrating multiple disciplines as well as the expertise of partners from societal practice, transdisciplinary researchers are able to look at a problem from many angles, with the goal of making both societal and scientific advances.

But how can these different types of expertise be integrated into both a better understanding of the problem and more effective ways of addressing it?

Colleagues and I have collected 43 methods from a number of transdisciplinary research projects dealing with a variety of research topics. We have grouped them into seven classes following an epistemological hierarchy. We start with methods in the narrower sense, progressing to integration instruments. Continue reading

A guide to ontology, epistemology, and philosophical perspectives for interdisciplinary researchers

Community member post by Katie Moon and Deborah Blackman

Katie Moon (biography)

How can understanding philosophy improve our research? How can an understanding of what frames our research influence our choices? Do researchers’ personal thoughts and beliefs shape research design, outcomes and interpretation?

These questions are all important for social science research. Here we present a philosophical guide for scientists to assist in the production of effective social science (adapted from Moon and Blackman, 2014). Continue reading

Going beyond ‘context matters’: A lens to bridge knowledge and policy

Community member post by Leandro Echt and Vanesa Weyrauch

Leandro Echt (biography)

The role and importance of context in the interaction between research and policy is widely recognized. It features in general literature on the subject, in case studies on how research has successfully influenced policy (or not), and in practitioners´ reflections on the results of their work. But how does context specifically matter? Can we move beyond generic statements?

Vanesa Weyrauch (biography)

To find some answers to these complex questions, Politics & Ideas and the International Network for the Availability of Scientific Publications (INASP) embarked on a joint knowledge systematization effort, combining a literature review with in-depth interviews with 48 experts and policymakers, mostly in developing countries.

What do we mean by context?

Our first challenge was to define what we concretely mean by context. Continue reading

A primer on policy entrepreneurs

Community member post by Jo Luetjens

Jo Luetjens (biography)

In the world of public policy, it is interesting to consider how and why particular policy ideas catch on. What is it that makes some ideas succeed and others fail? By examining the role of policy entrepreneurs we may come closer to an answer. In making policy change happen, what – and who – are policy entrepreneurs? Why are they important? What strategies do they use to effect change? And finally, what are the attributes of a successful policy entrepreneur?

The what

Policy entrepreneurs are energetic people who work with others in and around policymaking venues to promote significant policy change. Continue reading