Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Review article › peer-review
Research output: Contribution to Journal/Magazine › Review article › peer-review
}
TY - JOUR
T1 - ‘Small Data’ for big insights in ecology
AU - Todman, Lindsay C.
AU - Bush, Alex
AU - Hood, Amelia S.C.
PY - 2023/7/31
Y1 - 2023/7/31
N2 - Big Data science has significantly furthered our understanding of complex systems by harnessing large volumes of data, generated at high velocity and in great variety. However, there is a risk that Big Data collection is prioritised to the detriment of ‘Small Data’ (data with few observations). This poses a particular risk to ecology where Small Data abounds. Machine learning experts are increasingly looking to Small Data to drive the next generation of innovation, leading to development in methods for Small Data such as transfer learning, knowledge graphs, and synthetic data. Meanwhile, meta-analysis and causal reasoning approaches are evolving to provide new insights from Small Data. These advances should add value to high-quality Small Data catalysing future insights for ecology.
AB - Big Data science has significantly furthered our understanding of complex systems by harnessing large volumes of data, generated at high velocity and in great variety. However, there is a risk that Big Data collection is prioritised to the detriment of ‘Small Data’ (data with few observations). This poses a particular risk to ecology where Small Data abounds. Machine learning experts are increasingly looking to Small Data to drive the next generation of innovation, leading to development in methods for Small Data such as transfer learning, knowledge graphs, and synthetic data. Meanwhile, meta-analysis and causal reasoning approaches are evolving to provide new insights from Small Data. These advances should add value to high-quality Small Data catalysing future insights for ecology.
KW - Ecology
KW - Evolution
KW - Behavior and Systematics
U2 - 10.1016/j.tree.2023.01.015
DO - 10.1016/j.tree.2023.01.015
M3 - Review article
VL - 38
SP - 615
EP - 622
JO - Trends in Ecology and Evolution
JF - Trends in Ecology and Evolution
SN - 0169-5347
IS - 7
ER -