Towards normalizing good practice across the whole modeling cycle: its instrumentation and future research topics

Choices made in modeling matter and demand more explication since they determine how much we can trust modeling insights and predictions within their social, political and ethical contexts. Good Modeling Practice (GMP) is a key research area for strengthening and maturing the modeling field and community, through identifying, formulating and sharing knowledge about the craft of modeling. This craft represents the knowledge that modelers learn in practice about how they get things done, and how they adapt their practices to new situations. This Joint Special Issue is motivated by the importance of sharing good modeling practices from a whole modeling lifecycle viewpoint. We attempt to add conceptual clarity to this research area by defining the plethora of concepts and decision points used to characterize the choices to be made throughout the modeling process, and by synthesizing some of the existing efforts on GMP. We characterize a broad list of articles in the literature on GMP and identify a list of essential topics demanding more attention. This list is only a preliminary one as we anticipate that a more comprehensive list of knowledge gaps will be unearthed from the submissions to the Joint Special Issue collection on GMP, of which this is an introduction. We also propose a vision for GMP and suggest instrumental ways that good practice can become not just well-known but normal practice. This instrumentation focuses on journal standards, collective commitment and culture especially by research community societies, early career awards for advancing GMP, and legal requirements or accreditation. A vital instrument in all this is the design and development of a modeling curriculum that distills core requisite knowledge about modeling, as well as proven-to-work routines and practices that can be scaled up in different contexts.

Bibliographic Details

Main Authors:	Jakeman, Anthony J., Elsawah, Sondoss, Wang, Hsiao-Hsuan, Hamilton, Serena H., Melsen, Lieke, Grimm, Volker
Format:	Article/Letter to editor biblioteca
Language:	English
Subjects:	Life Science,
Online Access:	https://research.wur.nl/en/publications/towards-normalizing-good-practice-across-the-whole-modeling-cycle
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