European Conference on Ecological Modelling (ECEM 2023)
The 9th European Conference on Ecology Modelling (ECEM 2023) is approaching!
The 9th European Conference on Ecological Modelling, ECEM 2023, extends a warm welcome to contributions directly or indirectly supporting transformation. This encompasses strategies and models enhancing aspects such as response mechanisms representation, multi-criteria model evaluation, model-data fusion, sensitivity and robustness analyses, upscaling, transferability to new regions, links to management scenarios, social-ecological systems, transparency, reproducibility, theory and concept implementation and testing, and multi-modeling synthesis. In essence, any contribution advancing ecological modeling is highly encouraged.
ECEM 2023 continues the legacy of conferences initiated by the European chapter of ISEM, the International Society for Ecological Modelling. ISEM is committed to fostering international knowledge exchange in the domains of systems' analysis and simulations in ecology and the application of ecological modeling in natural resource management.
BioDT at the ECEM 2023
Taimur Khan, from Helmholtz-UFZ and BioDT partner, joins the "Designing Dynamic Data-Driven Digital Twin Systems in Ecology" workshop as part of the ECEM 2023 this year.
His presentation revolves around Dynamic Data Driven Application Systems (DDDA). His abstract is the following:
"Today's ecological modelling and simulation code typically only support static workflows. Users can only interact with the running code to terminate a run when input data and parameter files have been produced in advance and are read by the code at startup. If data re-integration is necessary, it is typically done manually using static, sanitised input files produced from data sources to interact with observation systems, data archives, and experiments. This presents a challenge in using legacy ecological models and simulations in Digital Twins.
Dynamic Data Driven Application Systems (or DDDAS) is a conceptual framework that synergistically combines models and data in order to facilitate the analysis and prediction of physical phenomena. DDDAS is an emerging systems design approach that enables to measure physical processes more effectively and consequently update models and simulations. DDDAS and Digital Twins are a natural pairing that improve the combined capabilities of sensors, data, models, and choices. DDDAS incorporates additional data into an executing Digital Twin, and in reverse, enhance a Digital Twin to dynamically steer the decision on its physical asset.
In this workshop, participants will get the chance to dive into what DDDAS is and what possibilities it allows for designing Digital Twin systems in Ecology. Furthermore, examples of DDDAS in Digital Twin design will be presented."