The WWF and World Bank as well as UNEP have called for decision-grade data about nature, but what does that mean? It has to reference back to the decision in question that is being made, but there are likely to be common characteristics across all types of decision. The Taskforce for Nature-related Disclosures‘ Proposed Technical Scope (published 04.06.21) recommends data quality would be able to show:
Relevance: Formal recognition as appropriate to the decision context – for example, as part of the monitoring frameworks of multilateral environmental agreements or national policies – including the mechanism of recognition and the role of third parties in formal recognition of specific datasets.
Resolution (spatial and non-spatial) and scalability: Fit for use at the right scale for the decision. A balance may be struck between the resolution and the complexity of processing the data. For example, sourcing may not be better informed by <1km resolution geospatial data, where sub-regional data may be easier and more straightforward to process.
Temporality: Time series data can support trend analyses or real-time decision-making but must reflect the appropriate time scales for the indicator of interest (including forward-looking analysis where relevant), but also the feasibility of collecting data using current or emerging technologies and collection techniques (e.g. species abundance).
Frequency of update: Regularly updated or updated at appropriate timescales for the subject matter.
Geographic coverage: including globally consistent and comprehensive. Data should be collected in a fashion and using metrics that permit aggregation and dis-aggregation to allow for attribution across portfolios, corporate footprints etc.
Accessibility: Decision-grade data must be easily accessible online in different formats (e.g. direct downloads, web services, APIs), including considerations of costs where not open and freely accessible, as well as available in multiple languages.
Comparability: Decision-grade data must facilitate comparison through interoperable formats and consistent methods that enable integration of financial, socio-economic and ecological data across sectors to inform outcomes. Data should be comparable across and within industries.
Thematic coverage: Addressing specific components of nature (encompassing species, ecosystems and contributions to people), pressures on nature (point and non-point source, direct and indirect) and responses (private, government, societal).
Authoritativeness including traceability: If data have been through a peer-review process, whether published in the scientific literature, reviewed by peers, or a mandated process (e.g. CBD), and are recognised as accurate and authoritative. In order to assess authoritativeness, the data must also be traceable. Data is traceable if the original data source is clear as well as the “data trail” which lays out how the data has been translated by different users to arrive in its final format.