Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1016/j.ecoinf.2025.103407 |
Licence  |
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| Title (Primary) | TwinEco: A unified framework for dynamic data-driven digital twins in ecology |
| Author | Khan, T.; de Koning, K.; Endresen, D.; Chala, D.; Kusch, E. |
| Source Titel | Ecological Informatics |
| Year | 2025 |
| Department | BZF |
| Page From | art. 103407 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Keywords | Digital twin; Ecological modelling; Research infrastructure; Framework; Data; DDDAS |
| Abstract | A Digital Twin (DT) is a virtual replica of a physical object or process
that is continuously updated at a certain frequency and can steer
change on the physical system, enabling a seamless integration of
observation, understanding, and action. Although initially applied
primarily in industry, DT is emerging as a powerful tool in ecology,
offering new possibilities for dynamic simulations of change in the
biosphere. However, since DTs are relatively new in this field, there is
currently no standard framework to guide their conceptualisation and
development. Thus, DTs in ecological applications are already
experiencing fragmentation in software concepts and design philosophies,
leading to incompatibilities across DT implementations. This
fragmentation risks undermining the progress and potential of the DT
concept in ecology. A unifying framework, such as TwinEco, can address
these discrepancies and establish a cohesive foundation for the
effective adoption and integration of DTs across ecological domains.
TwinEco is a modular framework designed to aid and harmonise ecologists'
efforts to build DTs. In doing so, TwinEco focuses on three major
design goals: 1. Modularity, flexibility, and interoperability of DTs facilitated through distinct “components” nested within DT “layers”. 2. Dynamic modelling of ecological processes and states that evolve over time. 3. Linking ecological modelling to downstream actions or decisions made on the ecological object or process of study. TwinEco's architecture builds upon the feedback loops and state management strategies introduced in the Dynamic Data-Driven Application Systems (DDDAS) paradigm, which has already inspired many DTs across scientific domains. We also discuss the usefulness and ease-of-use of TwinEco by demonstrating its applicability to computational case studies and suggesting future recommendations to the community of data infrastructure builders and modellers in regards to open considerations. By introducing a shared terminology and emphasising model-data fusion, TwinEco highlights the importance of a unified framework to avoid fragmentation in the burgeoning field of ecological digital twinning. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29571 |
| Khan, T., de Koning, K., Endresen, D., Chala, D., Kusch, E. (2025): TwinEco: A unified framework for dynamic data-driven digital twins in ecology Ecol. Inform. , art. 103407 10.1016/j.ecoinf.2025.103407 |
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