Why model?

By Steven Lade

Steven Lade
Steven Lade (biography)

What do you think about mathematical modelling of ‘wicked’ or complex problems? Formal modelling, such as mathematical modelling or computational modelling, is sometimes seen as reductionist, prescriptive and misleading. Whether it actually is depends on why and how modelling is used.

Here I explore four main reasons for modelling, drawing on the work of Brugnach et al. (2008):

  • Prediction
  • Understanding
  • Exploration
  • Communication.

Read moreWhy model?

Four patterns of thought for effective group decisions

By George P. Richardson and David F. Andersen

George Richardson
George P. Richardson (biography)

What can you do if you are in a group that is trying to deal with problems that are developing over time, where:

  • root causes of the dynamics aren’t clear;
  • different stakeholders have different perceptions;
  • past solutions haven’t worked;
  • solutions must take into account how the system will respond; and,
  • implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?

Read moreFour patterns of thought for effective group 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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Synthesis of knowledge about participatory modeling: How a group’s perceptions changed over time

By Rebecca Jordan

Rebecca Jordan (biography)

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.

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

What’s in a name? The role of storytelling in participatory modeling

By Alison Singer

singer
Alison Singer (biography)

That which we call a rose,
by any other name would smell as sweet.

That Shakespeare guy really knew what he was talking about. A rose is what it is, no matter what we call it. A word is simply a cultural agreement about what we call something. And because language is a common thread that binds cultures together, participatory modeling – as a pursuit that strives to incorporate knowledge and perspectives from diverse stakeholders – is prime for integrating stories into its practice.

To an extent, that’s what every modeling activity does, whether it’s through translating an individual’s story into a fuzzy cognitive map, or into an agent-based model. But I would argue that the drive to quantify everything can sometimes make us lose the richness that a story can provide.

Read moreWhat’s in a name? The role of storytelling in participatory modeling

Citizen science and participatory modeling

By Rebecca Jordan and Steven Gray

Rebecca Jordan (biography)

As investigators who engage the public in both modeling and research endeavors we address two major questions: Does citizen science have a place within the participatory modeling research community? And does participatory modeling have a place in the citizen science research community?

Let us start with definitions. Citizen science has been defined in many ways, but we will keep the definition simple. Citizen science refers to endeavors where persons who do not consider themselves scientific experts work with those who do consider themselves experts (around a specific issue) to address an authentic research question.

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Dealing with deep uncertainty: Scenarios

schmitt-olabisi
Laura Schmitt Olabisi (biography)

By Laura Schmitt Olabisi

What is deep uncertainty? And how can scenarios help deal with it?

Deep uncertainty refers to ‘unknown unknowns’, which simulation models are fundamentally unsuited to address. Any model is a representation of a system, based on what we know about that system. We can’t model something that nobody knows about—so the capabilities of any model (even a participatory model) are bounded by our collective knowledge.

One of the ways we handle unknown unknowns is by using scenarios. Scenarios are stories about the future, meant to guide our decision-making in the present.

Read moreDealing with deep uncertainty: Scenarios

Uncertainty in participatory modeling – What can we learn from management research?

By Antonie Jetter

antonie-jetter
Antonie Jetter (biography)

I frequently struggle to explain how participatory modeling deals with uncertainty. I found useful guidance in the management literature.

After all, participatory modeling projects and strategic business planning have one commonality – a group of stakeholders and decision-makers aims to understand and ultimately influence a complex system. They do so in the face of great uncertainty that frequently cannot be resolved – at least not within the required time frame. Businesses, for example, have precise data on customer behavior when their accountants report on annual sales. However, by this time, the very precise data is irrelevant because the opportunity to influence the system has passed.

Two key lessons from the management literature deal with the nature of uncertainty and responding to four major types of uncertainty.

Read moreUncertainty in participatory modeling – What can we learn from management research?

ICTAM: Bringing mental models to numerical models

By Sondoss Elsawah

sondoss-elsawah
Sondoss Elsawah (biography)

How can we capture the highly qualitative, subjective and rich nature of people’s thinking – their mental models – and translate it into formal quantitative data to be used in numerical models?

This cannot be addressed by a single method or software tool. We need multi-method approaches that have the capacity to take us through the learning journey of eliciting and representing people’s mental models, analysing them, and generating algorithms that can be incorporated into numerical models.

More importantly, this methodology should allow us to see in a transparent way the progression on this learning journey.

Read moreICTAM: Bringing mental models to numerical models

Participatory processes and participatory modelling: The sustainable procedure framework

By Beatrice Hedelin

beatrice-hedelin
Beatrice Hedelin (biography)

How can we resolve debates about participatory processes between proponents and skeptics? What role can participatory modelling play in improving participatory processes?

Proponents argue for the merits of participatory processes, which include learning; co-production of knowledge; development of shared understanding of a problem and shared goals; creation of trust; and local power and ownership of a problem.

Sceptics point to evidence of inefficient, time-consuming, participatory processes that escalate conflict and mistrust. They also highlight democratic problems; lack of transparency; and powerful actors that benefit in relation to weaker ones such as the unorganized, poor, and uneducated.

Read moreParticipatory processes and participatory modelling: The sustainable procedure framework

Art and participatory modelling

By Hara W. Woltz and Eleanor J. Sterling

authors_mosaic_hara-woltz_eleanor-sterling
1. Hara W. Woltz (biography)
2. Eleanor J. Sterling (biography)

What can art contribute to participatory modelling? Over the past decade, participatory visual and narrative arts have been more frequently and effectively incorporated into scenario planning and visioning workshops.

We use arts-based techniques in three ways:

  1. incorporating arts language into the process of visioning
  2. delineating eco-aesthetic values of the visual and aural landscape in communities
  3. engaging art to articulate challenges and solutions within local communities.

The arts based approaches we use include collage, drawing, visual note taking, map making, storyboarding, photo documentation through shared cameras, mobile story telling, performance in the landscape, drawing as a recording device, and collective mural creation.

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Serious gaming: Helping stakeholders address community problems

By Nagesh Kolagani

kolagani
Nagesh Kolagani (biography)

Citizens are increasingly coming together to solve problems that affect their communities. Participatory modeling is a method that helps them to share their implicit and explicit knowledge of these problems with each other and to plan and implement mutually acceptable and sustainable solutions.

While using this method, stakeholders need to understand large amounts of information relating to these problems. Various interactive visualization tools are being developed for this purpose. One such tool is ‘serious gaming’ which combines technologies from the video game industry – mystery, appealing graphics, etc., – with a purpose other than pure entertainment, a serious, problem driven, educational purpose.

Read moreSerious gaming: Helping stakeholders address community problems