Knowledge synthesis – Integration and Implementation Insights

Towards a taxonomy of synthesizing

October 17, 2023September 19, 2023

By Howard Gardner

“Synthesis” seems to be in the atmosphere. The capacity to synthesize, the need for syntheses, and improvement of the quality of syntheses—these are seemingly of interest to many.

A preliminary working definition:

A synthesis is an attempt to bring together various ideas, strands, concepts, and materials. A good synthesis enhances one’s understanding of a question, puzzle, phenomenon (or multiples of these). Familiar examples are school term papers, doctoral dissertations, position papers, landscape analyses, executive summaries, and textbooks. But one can easily extend the list beyond the verbal—to chemical syntheses, equations in physics or mathematics, works of art (poems, paintings, dioramas)—indeed any creation or invention that brings together disparate elements in a satisfying and illuminating way.

Of course, it’s important to avoid the situation where just about everything qualifies as a synthesis.

An analytical framework for knowledge co-production

September 5, 2023May 30, 2023

By Marianne Penker

How can students and academics starting out in transdisciplinary research begin to come to grips with knowledge co-production?

Colleagues and I developed a useful analytical framework comprising the following four elements:

typology of actor roles (who?)
research phases (when?)
objectives and forms of actor integration (why?)
types of knowledge (what?).

These four elements are illustrated in the figure below.

The development of the framework was based on the literature and our experiences in running a doctoral school on transdisciplinary sustainability research (see Enengel et al. 2012).

Seven methods for mapping systems

February 28, 2023

By Pete Barbrook-Johnson and Alexandra S. Penn

authors_pete-barbrook-johnson_alexandra-penn — 1. Pete Barbrook-Johnson (biography)
2. Alexandra S. Penn (biography)

What are some effective approaches for developing causal maps of systems in participatory ways? How do different approaches relate to each other and what are the ways in which systems maps can be useful?

Here we focus on seven system mapping methods, described briefly in alphabetical order.

1. Bayesian Belief Networks: a network of variables representing their conditional dependencies (ie., the likelihood of the variable taking different states depending on the states of the variables that influence them). The networks follow a strict acyclic structure (ie., no feedbacks), and nodes tend to be restricted to maximum two incoming arrows. These maps are analysed using the conditional probabilities to compute the potential impact of changes to certain variables, or the influence of certain variables given an observed outcome.

Addressing societal challenges: From interdisciplinarity to research portfolios analysis

November 1, 2023February 18, 2021

By Ismael Rafols

author_ismael-rafols — Ismael Rafols (biography)

How can knowledge integration for addressing societal challenges be mapped, ‘measured’ and assessed?

In this blog post I argue that measuring averages or aggregates of ‘interdisciplinarity’ is not sufficiently focused for evaluating research aimed at societal contributions. Instead, one should take a portfolio approach to analyze knowledge integration as a systemic process over research landscapes; in particular, focusing on the directions, diversity and synergies of research trajectories.

There are two main reasons:

1. since knowledge integration for societal challenges is a systemic and dynamic process, we need broad and plural perspectives and therefore we should use a battery of analytical tools, as developed for example in research portfolio analysis, rather than a narrow focus on interdisciplinarity.

Agent-based modelling for knowledge synthesis and decision support

April 15, 2022June 25, 2019

By Jen Badham

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).

A checklist for documenting knowledge synthesis

April 28, 2021July 31, 2018

By Gabriele Bammer

How do you write-up the methods section for research synthesizing knowledge from different disciplines and stakeholders to improve understanding about a complex societal or environmental problem?

In research on complex real-world problems, the methods section is often incomplete. An agreed protocol is needed to ensure systematic recording of what was undertaken. Here I use a checklist to provide a first pass at developing such a protocol specifically addressing how knowledge from a range of disciplines and stakeholders is brought together.

KNOWLEDGE SYNTHESIS CHECKLIST

1. What did the synthesis of disciplinary and stakeholder knowledge aim to achieve, which knowledge was included and how were decisions made?

Synthesis of knowledge about participatory modeling: How a group’s perceptions changed over time

August 24, 2022July 3, 2018

By Rebecca Jordan

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.

Two types of interdisciplinary scholarship

October 1, 2020February 6, 2018

By Andi Hess

Would it be helpful to identify two distinct forms of interdisciplinary scholarship ― 1) individual interdisciplinarity and 2) interdisciplinary dialogue and team science ― and to make this distinction explicit in the literature? What are the benefits and challenges of each? Are a different set of resources and methods required to achieve effective interdisciplinary scholarship?

As integration scientists are aware, there are many analyses of appropriate methods for conducting interdisciplinary work. Each has its own benefits and challenges, and each requires a different set of resources and methods for achieving effective interdisciplinary scholarship.

Toolkits for transdisciplinary research

December 1, 2022July 25, 2017

By Gabriele Bammer

If you want to undertake transdisciplinary research, where can you find relevant concepts and methods? Are there compilations or toolkits that are helpful?

I’ve identified eight relevant toolkits, which are described briefly below and in more detail in the journal GAIA’s Toolkits for Transdisciplinarity series.

One toolkit provides concepts and methods relevant to the full range of transdisciplinary research, while the others cover four key aspects: (i) collaboration, (ii) synthesis of knowledge from relevant disciplines and stakeholders, (iii) thinking systemically, and (iv) making change happen.

The ‘methods section’ in research publications on complex problems – Purpose

December 21, 2022October 11, 2016

By Gabriele Bammer

Do we need a protocol for documenting how research tackling complex social and environmental problems was undertaken?

Usually when I read descriptions of research addressing a problem such as poverty reduction or obesity prevention or mitigation of the environmental impact of a particular development, I find myself frustrated by the lack of information about what was actually done. Some processes may be dealt with in detail, but others are glossed over or ignored completely.

For example, often such research brings together insights from a range of disciplines, but details may be scant on why and how those disciplines were selected, whether and how they interacted and how their contributions to understanding the problem were combined. I am often left wondering about whose job it was to do the synthesis and how they did it: did they use specific methods and were these up to the task? And I am curious about how the researchers assessed their efforts at the end of the project: did they miss a key discipline? would a different perspective from one of the disciplines included have been more useful? did they know what to do with all the information generated?

In praise of multidisciplinarity

November 30, 2022August 2, 2016

By Gabriele Bammer

What characterizes multidisciplinary research? When is it most appropriate? What does it take to do it well? Multidisciplinarity often gets a bad rap, being seen as less sophisticated than interdisciplinarity and transdisciplinarity. But does it have its own important role in dealing with complex social and environmental problems?

Multidisciplinary research has two primary characteristics:

different disciplines independently shine their light on a particular problem, and
synthesis happens at the end and can be undertaken by anyone.

Unlike interdisciplinary and transdisciplinary research, there is no attempt to agree upfront on either a problem definition or on how the different perspectives will be brought together.