Community member post by Sondoss Elsawah and Joseph Guillaume
In part 1 of our blog posts on why use patterns, we argued for making unstated, tacit knowledge about integrated modelling practices explicit by identifying patterns, which link solutions to specific problems and their context. We emphasised the importance of differentiating the underlying concept of a pattern and a pattern artefact – the specific form in which the pattern is explicitly described.
In order to actually use patterns to communicate about practices, the artefact takes on greater importance: what form could artefacts describing the patterns take, and what mechanisms and platforms are needed to first create, and then share, maintain, and update these artefacts?
While the concepts of ‘problem, solution and context’ should be discussed in some way, there is no single best way of representing patterns as artefacts. The form of artefacts will differ depending on many factors, including how the users perceive the ease of:
- absorbing the pattern
- understanding relationships among patterns
- discovering or being made aware of patterns
- eliciting contributions and building group understanding.
Absorbing the pattern
Patterns are intended to be easily absorbed. The most common ways for representing patterns are structured templates and graphical description (mostly Unified Modelling Language (UML)). In part 1 of our blog posts, we documented the ‘Use a concrete example’ pattern using a structured template artefact consisting of the elements: Pattern name, Context, Description, Consequences, Related patterns.
Understanding relationships among patterns
In order to capture relationships among patterns, patterns are commonly organised into collections in one of two ways. First, patterns may link to each other in their descriptions, such that they organically form an interlinked collection, referred to as a “pattern language.” For example, a modelling pattern describing parameter estimation might link to patterns involving optimisation, selection of objective function, and addressing parameter uncertainty. If relationships are defined by users, the structure of the collection emerges from their needs. This can be an efficient and effective way of progressing patterns, especially in initial design cycles when building understanding and consensus about integrated modelling patterns is only starting.
Alternatively, patterns might be classified more formally to give the community an accessible and easy-to-navigate intellectual repository of existing patterns. The classification gives a big picture overview, as well as giving newcomers a jump-start. For example, modelling patterns might be divided by the stage of the modelling process in which they are used, eg., stakeholder feedback on a conceptual model might belong to a “planning” stage, and parameter estimation to a “model construction” stage. Such a pre-defined structure requires a well-developed shared understanding of relationships among patterns, and may result in substantial changes to the structure if new patterns are added.
Discovering or being made aware of patterns
To assist users in discovering or being made aware of patterns, they can be collected in handbooks, textbooks, journal articles, pattern repository websites, blogs and collaborative wiki.
Eliciting contributions and building group understanding
Eliciting and conceptualizing tacit knowledge is intrinsically challenging, both in obtaining knowledge from individuals and building a group understanding. The philosopher Polanyi (1967) described tacit knowledge as “knowing more than we can tell”, or “knowing to do something without thinking”. The more experienced the person is, the more this knowledge becomes ingrained into their hard-to-access mental schema and becomes taken for granted or regarded as common-sense.
Our anecdotal experience suggests that pattern thinking can be promoted by looking for distinct solutions within a narrative, targeting questions regarding what problem the solution was intended to solve, as well as trying to identify changes to context that would have resulted in switching to different practices.
Building a group understanding involves obtaining agreement. Participants may differ in their perspectives on:
- what worked or did not work in a project, in other words conceptualisations of the solution being discussed,
- factors affecting success,
- how best to capture and represent the lessons learned, and
- how the relationship between different solutions should be presented for effective communication.
Developing and using patterns is an ongoing process of building a shared vision of problems, solutions, and context. The pattern approach is a bottom-up process, initiated and sustained by members of a community, with similar objectives, addressing similar problems. Greater experience within the community will improve the ability of community members to reach shared understanding, and lead to greater benefits from a pattern-based approach.
The integrated environmental modelling community lags behind other domains, such as engineering and computer science, in capturing modelling experience from tacit knowledge. We believe it is worth pursuing a pattern-based approach for learning about modelling practices, and we need to develop sustainable mechanisms (including funding) to identify, share and maintain the pattern artefacts.
We welcome your thoughts regarding how we can move forward with patterns in eliciting tacit knowledge about modelling practices.
Polanyi, M. (1967). The Tacit Dimension. Doubleday: New York, United States of America.
Biography: Sondoss Elsawah is a senior lecturer at the University of New South Wales, Canberra, Australia. She comes from an operations research background. Her research focuses on the development and use of multi-method approaches to support learning and decision making in complex socio-ecological and socio-technical decision problems. Application areas include natural resource management and defence capability management. Her recent work focuses on how to integrate and transfer knowledge across projects and application domains to improve the practice and teaching of systems modelling methodologies. She is member of the Core Modeling Practices pursuit funded by the National Socio-Environmental Synthesis Center (SESYNC).
Biography: Joseph Guillaume is a Postdoctoral Researcher with the Water and Development Research Group at Aalto University, Finland. He is a transdisciplinary modeller with a particular interest in uncertainty and decision support. Application areas have focussed primarily on water resources, including rainfall-runoff modelling, hydro-economic modelling, ecosystem health, global water scarcity and global food security. Ongoing work involves providing a synthesis of the many ways we communicate about uncertainty, and their implications for modelling and decision support. He is member of the Core Modeling Practices pursuit funded by the National Socio-Environmental Synthesis Center (SESYNC).
This blog post is one 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).