Keywords
web-cloud-based, climate service, hydropower, machine learning, seasonal forecast
Start Date
17-9-2020 11:20 AM
End Date
17-9-2020 11:40 AM
Abstract
In many cases the goal of modeling is to predict the future and enable informed intervention to change or optimize the future. That is, modeling seeks to be a decision support tool. However, modeling alone is insufficient to support decision making. As expressed by Lee Roy Beach, people do not make decisions as rational humans using available data and facts but rather construct narratives to understand the outcomes of a particular decision. Within community-based decision making, this narrative construction often proceeds in an ad hoc fashion which may or may not incorporate modeling outcomes and data. This occurs in part because the community lacks the ability to directly explore, challenge, and learn from the model while simultaneously updating the shared narrative. To overcome this, we are exploring a decision making model in which narrative and modeling are explicitly linked, the need for quantitative and qualitative in support of the narrative drives the system modeling effort, and the model evolves as the narrative is explored. There are three elements to this approach: (1) a shared definition of the narrative, (2) an open and transparent modeling process, and (3) explicit links between the narrative and the systems model. This paper focuses on the development of explicit links between the narrative and the model in support of a shared narrative and how the model and narrative can grow together. This approach is demonstrated using the interactions and outcomes of a village energy system model describing the interactions between energy, people, and the environment within the developing world. In this scenario there are multiple stakeholders with differing goals. We will show how exit points from this network of models representing this complex system can provide data into a developing narrative that supports the concerns of a community.
Coupling Models and Narrative in Support of Decision Making
In many cases the goal of modeling is to predict the future and enable informed intervention to change or optimize the future. That is, modeling seeks to be a decision support tool. However, modeling alone is insufficient to support decision making. As expressed by Lee Roy Beach, people do not make decisions as rational humans using available data and facts but rather construct narratives to understand the outcomes of a particular decision. Within community-based decision making, this narrative construction often proceeds in an ad hoc fashion which may or may not incorporate modeling outcomes and data. This occurs in part because the community lacks the ability to directly explore, challenge, and learn from the model while simultaneously updating the shared narrative. To overcome this, we are exploring a decision making model in which narrative and modeling are explicitly linked, the need for quantitative and qualitative in support of the narrative drives the system modeling effort, and the model evolves as the narrative is explored. There are three elements to this approach: (1) a shared definition of the narrative, (2) an open and transparent modeling process, and (3) explicit links between the narrative and the systems model. This paper focuses on the development of explicit links between the narrative and the model in support of a shared narrative and how the model and narrative can grow together. This approach is demonstrated using the interactions and outcomes of a village energy system model describing the interactions between energy, people, and the environment within the developing world. In this scenario there are multiple stakeholders with differing goals. We will show how exit points from this network of models representing this complex system can provide data into a developing narrative that supports the concerns of a community.
Stream and Session
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