Chapter 6: Data opportunities - Measuring Progress: Water-related Ecosystems and the SDGs

Dou, Changyong ; Wang, Futao ; Liu, Jie ; Zuo, Lijun ; Wang, Meng ; Guo, Huadong ; Lu, Shanlong ; Li, Xiaosong ; Chen, Yaxi ; Chen, Yu (2023-03)

Big data sources are increasingly being recognized as new and innovative information sources for SDGs (MacFeely 2019; IAEGSDGS 2019; Tam and Van Halderen 2020). Many NSOs are already experimenting with big data in the production of official statistics, with initiatives catalogued by the United Nations Global Working Group on Big Data and the United Nations Global Pulse. Currently, the dominant big data types include Earth Observation (EO) data, citizen science, other sensor network data, commercial data, tracking data, administrative data, and opinion and behavioural data. Combined with advanced analytical techniques (e.g. machine learning, geospatial modelling and geostatistical modelling), they could contribute to the monitoring of 15 goals, 51 targets and 69 indicators (Allen et al. 2021), particularly those related to health and biodiversity.

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