Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1016/j.tree.2023.04.010
Lizenz creative commons licence
Titel (primär) Digital twins: dynamic model-data fusion for ecology
Autor de Koning, K.; Broekhuijsen, J.; Kühn, I. ORCID logo ; Ovaskainen, O.; Taubert, F.; Endresen, D.; Schigel, D.; Grimm, V.
Quelle Trends in Ecology & Evolution
Erscheinungsjahr 2023
Department BZF; OESA; iDiv
Band/Volume 38
Heft 10
Seite von 916
Seite bis 926
Sprache englisch
Topic T5 Future Landscapes
Keywords highlight; digital twins; biodiversity conservation; evidence-based conservation; model-data integration; real-time monitoring; digital conservation
Abstract Digital twins (DTs) are an emerging phenomenon in the public and private sectors as a new tool to monitor and understand systems and processes. DTs have the potential to change the status quo in ecology as part of its digital transformation. However, it is important to avoid misguided developments by managing expectations about DTs. We stress that DTs are not just big models of everything, containing big data and machine learning. Rather, the strength of DTs is in combining data, models, and domain knowledge, and their continuous alignment with the real world. We suggest that researchers and stakeholders exercise caution in DT development, keeping in mind that many of the strengths and challenges of computational modelling in ecology also apply to DTs.
dauerhafte UFZ-Verlinkung
de Koning, K., Broekhuijsen, J., Kühn, I., Ovaskainen, O., Taubert, F., Endresen, D., Schigel, D., Grimm, V. (2023):
Digital twins: dynamic model-data fusion for ecology
Trends Ecol. Evol. 38 (10), 916 - 926 10.1016/j.tree.2023.04.010