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IPS175 Jillian C. et al.
In order for the SDGs to be an effective tool for galvanizing action, there
is a need to urgently uplevel monitoring and build a digital ecosystem for the
planet (Jensen and Campbell, 2019). This would provide a foundation to fill
data gaps for targets lacking data disaggregated by crucial specificities and
disparities (including by gender, income quintile, education, disability and
other vulnerable groups) and even lacking data at all. Such an ecosystem
would also help build the tools and capacity to conduct integrated analysis
that can be used to generate actionable insights (UN Environment, 2019a;
Data Revolution Group, 2014). Global data products and global modelling can
form a basis for filling data gaps and ensuring that there is some data for all
countries. These products also can demonstrate environmental concerns that
should be further monitored through high-frequency or high-resolution
remote sensing or through in situ collection or other means. Existing global
data products like those for SDG target 6.6 (https://www.sdg661.app/) and
SDG targets 8.4 and 12.2 (material flows) can provide an example of how such
products can and have already been accepted for official SDG monitoring (UN,
2018).
Complementing global products and global modelling is citizen science,
which can also help fill data gaps in some countries. Citizen science is already
contributing to SDG indicators, e.g. 15.5.1, but further efforts are needed to
investigate the potential of citizen science for other environmental SDG
indicators, particularly Tier III. Citizen science projects and representatives
from the citizen science community need to be brought into the high-level
discussions on methodology development and data collection to explore the
best way forward. Making progress on one indicator, e.g., 14.1.1. on marine
plastic debris, may be provide a blueprint for integrating citizen science in
other places.
In economic policy, a single headline indicator – Gross Domestic Policy –
is used as a flag for economic progress. There has been some discussion on
developing an equivalent indicator, with corresponding sub-indicators, for
measuring sustainable development (Ekins, et al. 1999). Building out the
portfolio of country-level data on globally-agreed environmental indicators
could support consensus on a headline indicator on the environmental
dimension of development. However, building the capacity of countries to
collect the underlying basic data and better utilizing existing data – including
from non-traditional data sources such as satellites, drones and citizen science
– are at the crux of being able to monitor the SDGs and develop integrated
analyses or indices (Holloway et al., 2018).
The current limitations on understanding environmental indicator
progress illustrate a “catch-22 situation” when it comes to achieving the SDGs
for the sustainability of the planet and for humanity: We use existing data to
identify priorities, but priorities for data collection are identified on the basis

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