Keywords
transdisciplinary research, participatory modelling, bayesian networks, actor modelling, actor-based modelling, participatory scenario development
Start Date
1-7-2012 12:00 AM
Abstract
Generation and integration of different forms of disciplinary knowledgeand knowledge outside of academia have become increasingly important in theeffort of tackling real-world problems that are related to complex and uncertainhuman-environment systems. In recent years, transdisciplinary research hasemerged as a collaborative and integrative approach for the co-generation ofsystem knowledge, target knowledge, and transformation knowledge amongscientists and stakeholders. In this paper, we present a methodology forparticipatory modelling processes that we apply in a transdisciplinary project forsustainable energy supply based on renewable energies in the county of Groß-Gerau in the German state of Hesse. The core of the transdisciplinary researchproject is a stakeholder dialogue including stakeholder interviews and a series ofworkshops. The participatory processes will be supported by actor-basedmodelling and Bayesian network modelling for joint knowledge generation andintegration among scientific experts and institutional stakeholders. Actor-basedmodelling is a semi-quantitative method used for the analysis of problemperceptions that are depicted in perception graphs (PG). These perception graphsare analyzed with the software DANA (http://dana.actoranalysis.com) in order toidentify sustainable development paths. On the other hand, probabilistic BayesianNetworks (BNs) can be used to model complex problem fields using quantitativedata as well as qualitative expert judgments. In our study of the problem field, weaim at developing implementable management strategies, particularly by thegeneration of qualitative and quantitative scenarios.
Transdisciplinary research for supporting environmental management
Generation and integration of different forms of disciplinary knowledgeand knowledge outside of academia have become increasingly important in theeffort of tackling real-world problems that are related to complex and uncertainhuman-environment systems. In recent years, transdisciplinary research hasemerged as a collaborative and integrative approach for the co-generation ofsystem knowledge, target knowledge, and transformation knowledge amongscientists and stakeholders. In this paper, we present a methodology forparticipatory modelling processes that we apply in a transdisciplinary project forsustainable energy supply based on renewable energies in the county of Groß-Gerau in the German state of Hesse. The core of the transdisciplinary researchproject is a stakeholder dialogue including stakeholder interviews and a series ofworkshops. The participatory processes will be supported by actor-basedmodelling and Bayesian network modelling for joint knowledge generation andintegration among scientific experts and institutional stakeholders. Actor-basedmodelling is a semi-quantitative method used for the analysis of problemperceptions that are depicted in perception graphs (PG). These perception graphsare analyzed with the software DANA (http://dana.actoranalysis.com) in order toidentify sustainable development paths. On the other hand, probabilistic BayesianNetworks (BNs) can be used to model complex problem fields using quantitativedata as well as qualitative expert judgments. In our study of the problem field, weaim at developing implementable management strategies, particularly by thegeneration of qualitative and quantitative scenarios.
