Integrated Environmental Modeling: A Vision and Roadmap for the Future. Laniak, G. F., Olchin, G., Goodall, J., Voinov, A., Hill, M., Glynn, P., Whelan, G., Geller, G., Quinn, N., Blind, M., Peckham, S., Reaney, S., Gaber, N., Kennedy, R., & Hughes, A. 39:3–23. ![Integrated Environmental Modeling: A Vision and Roadmap for the Future [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops). [Highlights] [::] A roadmap for the future of integrated environmental modeling (IEM) is presented. [::] IEM landscape consists of applications, science, technology, and community elements. [::] IEM current practices, issues, and challenges are described. [::] A call for science and technology standards established by the global IEM community.
@article{laniakIntegratedEnvironmentalModeling2013,
title = {Integrated Environmental Modeling: A Vision and Roadmap for the Future},
author = {Laniak, Gerard F. and Olchin, Gabriel and Goodall, Jonathan and Voinov, Alexey and Hill, Mary and Glynn, Pierre and Whelan, Gene and Geller, Gary and Quinn, Nigel and Blind, Michiel and Peckham, Scott and Reaney, Sim and Gaber, Noha and Kennedy, Robert and Hughes, Andrew},
date = {2013-01},
journaltitle = {Environmental Modelling \& Software},
volume = {39},
pages = {3--23},
issn = {1364-8152},
doi = {10.1016/j.envsoft.2012.09.006},
url = {http://mfkp.org/INRMM/article/11759258},
abstract = {Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops).
[Highlights]
[::] A roadmap for the future of integrated environmental modeling (IEM) is presented. [::] IEM landscape consists of applications, science, technology, and community elements. [::] IEM current practices, issues, and challenges are described. [::] A call for science and technology standards established by the global IEM community.},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-11759258,~to-add-doi-URL,decision-making,decision-support-system,environment-society-economy,environmental-modelling,integrated-modelling,integration-techniques,knowledge-integration,modelling,multi-criteria-decision-analysis,multi-stakeholder-decision-making,science-based-decision-making,science-policy-interface,science-society-interface,transdisciplinary-research}
}
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