A Year Since the FRIDAS Whitepaper: Let’s Get Reacquainted!
In January 2025, I published the FRIDAS Whitepaper at a moment when Biodiversity Net Gain (BNG) was shifting from future policy into everyday planning reality. Since then, BNG has moved fast. The legislation is live, the statutory metric is embedded, and GIS data has quietly become one of the most important pieces of evidence behind planning decisions.
As we start a new year, it feels like the right time to get reacquainted. What is FRIDAS? How was it created? and why do we need it? Let's start at the beginning...
BNG is a planning policy in England that requires development to result in an overall improvement in biodiversity. It is assessed using the statutory biodiversity metric published by Natural England, which draws on mapped habitat information to compare baseline and post‑development outcomes. The spatial data produced as part of this process forms a long‑term ecological and legal record that supports planning decisions and future monitoring. Despite this reliance on spatial measurement, there is currently no standardised practice governing how GIS data is prepared, structured, or quality‑checked for BNG submissions. So what happens when spatial data is unregulated?
The result is a system where assessments may be technically compliant with the metric while being built on spatial data of highly variable quality. In practice, this leads to a range of compounding issues, including inconsistent data formats that hinder interoperability, inaccurately drawn or misaligned red line boundaries that distort what is counted, poorly digitised habitat polygons that introduce gaps or overlaps into area calculations, and the omission of terrain considerations such as slope that can materially affect surface area on complex sites. These issues are often exacerbated by limited or absent metadata, making it difficult to verify data lineage, audit calculations, or understand how habitats were classified. Without consistent standards, biodiversity unit totals cannot be meaningfully compared or trusted at face value, increasing the risk of planning delays, misinformed decisions, financial exposure, and reputational damage. More broadly, it undermines confidence in the evidence base that Biodiversity Net Gain relies upon, not because the principle is flawed, but because the spatial data underpinning it is uneven and difficult to validate.
Newsletter Why Good GIS Data is Critical for Credible BNG link: https://www.linkedin.com/pulse/why-good-gis-data-critical-credible-biodiversity-dpzje/?trackingId=UsemFwEbTjiaw3CP39XauA%3D%3D
This is why we wanted to create a GIS data standard, however, we didn't want to re-create the wheel. Well established data quality principles exist across both academic and professional GIS practice, and FRIDAS is built directly on these foundations: how data is structured within GIS systems, how it is collected in the field, and how it is documented through metadata. In a BNG context, this means paying attention to consistency across datasets and over time so that information can be compared and trusted, ensuring linkage between mapped habitats and the wider ecological evidence that supports classification decisions, and recording clear lineage so that who collected the data, when, and how remains transparent long after submission. It also means considering positional accuracy, particularly where boundary placement or terrain can materially affect area calculations, validating attribute accuracy so habitat types and condition scores genuinely reflect ecological reality, enforcing logical consistency so datasets contain no overlaps, gaps or broken geometry, and ensuring completeness so that no habitats, attributes or supporting information are missing. When reviewed together, these issues are not isolated mistakes but recurring patterns that stem from the absence of a shared, practical structure for managing BNG spatial data. The challenge is not a lack of competence among ecologists or GIS practitioners, but a lack of a common framework that reflects how people actually work. FRIDAS was developed in response to this gap, bringing these core data quality principles together into a set of practical checks that support defensible, traceable, and usable GIS data across the full lifecycle of a BNG project. (Read the FRIDAS Whitepaper to see more detail).
Which leads us to FRIDAS... a synthesis of those core pain points we see in real data, turned into a set of practical checks and standards. It’s not about adding more admin. It’s about giving GIS consultants, ecologists, and developers a common foundation to work from, so that everyone is using data that’s defensible, traceable, and genuinely useful across the project lifecycle.
So why is it called FRIDAS?
FRIDAS is an acronym for the 6 major categories in our data standard. Each letter represents a category to simplify the data management process. There are as follows:
1. Format (F)
2. Red line boundary (R)
3. Identification (I)
4. Data - Supplementary and Metadata (D)
5. Attributes (A)
6. Slope (S)
Each category has between 1-5 question items for the user to answer along with a requirement for supplementary information. The specific requirements around FRIDAS are designed as best practices, but are dynamic, allowing for adjustments to reflect planning laws, the latest versions of the Biodiversity Metric technical guidance, but along with practical feedback. Let's break down the elements...
Format
BNG calculations rely on area, length, and spatial relationships. Those calculations can only be trusted if the underlying data is supplied in recognised GIS formats with a consistent coordinate reference system. Submitting shapefiles, GeoPackages or equivalent formats allows spatial integrity to be checked and preserved. Static maps alone cannot do that. Standardised format is the foundation that everything else depends on.
Newsletter BNG Should Start with Format Link: https://www.linkedin.com/pulse/bng-should-start-format-ecospatial-solutions-r8uoe/?trackingId=WdzNwzd5SC6rQRNu9Nl1Ag%3D%3D
Red Line Boundary
The red line boundary defines what is legally included in the application and therefore what is counted in the metric. If the baseline boundary does not exactly match the post development boundary, biodiversity units can be duplicated, lost, or accidentally counted outside land ownership. FRIDAS treats the red line boundary as a single authoritative spatial layer that must be reused consistently across all datasets and figures.
Newsletter The Boundary Problem in Biodiversity Net Gain Link: https://www.linkedin.com/pulse/boundary-problem-biodiversity-net-gain-ecospatial-solutions-3fyte/?trackingId=%2B4ci4X%2BjRS%2B%2F02YWHEIEPQ%3D%3D
Identification
Habitat identification under BNG is tied directly to UKHab classifications and condition assessments. Whether surveys are field based or desk based, polygons must be digitised cleanly, snapped correctly, and aligned with their real-world extents. Gaps, overlaps, slivers and inconsistent geometry introduce uncertainty that propagates straight into the metric. FRIDAS focuses on checking that habitats are both ecologically credible and spatially sound.
Newsletter Habitat Mapping: Do It Properly Link: https://www.linkedin.com/pulse/habitat-mapping-do-properly-ecospatial-solutions-ohnbe/?trackingId=YBEFskb7RSKpi%2BqaW7P9dg%3D%3D
Data and Metadata
BNG data must stand up over time. That means being able to understand who created it, when, how, and based on what evidence. Metadata is not an administrative extra. It is what allows planners to verify submissions, future officers to interpret legacy sites, and monitoring to make sense years later. FRIDAS aligns with recognised metadata standards to strengthen transparency and traceability.
Newsletter The Role of Supplementary Data in Strengthening BNG Submissions Link: https://www.linkedin.com/pulse/role-supplementary-data-strengthening-bng-submissions-efl4e/?trackingId=afOF4oMQTUu%2FSxEGhYNkvA%3D%3D
Newsletter Creating Audit Trails: Why Metadata Is Essential for BNG Link: https://www.linkedin.com/pulse/creating-audit-trails-why-metadata-essential-bng-0srse/?trackingId=E8xMHgZNSbykT2YutGwaaw%3D%3D
Attributes
The biodiversity metric only works if attributes are complete and correctly populated. Missing condition fields, inconsistent naming, or ad hoc table structures introduce avoidable errors. Using Natural England’s templates or equivalent structured schemas ensures that GIS datasets can plug into BNG workflows without reworking or reinterpretation.
Slope
Slope is not currently a direct input into the statutory metric, but it influences habitat extent, suitability, and sometimes area calculations in non trivial ways. Ignoring topography can underestimate true habitat area on steeper sites. FRIDAS encourages practitioners to acknowledge slope where it materially affects interpretation, even if it sits outside the calculator itself.
Newsletter The Case for Including Slope in BNG Link: https://www.linkedin.com/pulse/case-including-slope-bng-ecospatial-solutions-wrr6e/?trackingId=EXmdmBHAQESX1lwHpJtf3Q%3D%3D
The introduction of the FRIDAS checklist marks an important step forward in addressing the persistent challenges surrounding GIS data quality in Biodiversity Net Gain assessments. It offers a structured, practical way to improve the consistency, accuracy, and defensibility of the spatial data submitted as part of planning applications, grounding biodiversity outcomes in evidence that can be checked and trusted over time. FRIDAS is not a purely technical exercise but a response to real issues that practitioners encounter every day, from misaligned red line boundaries and incomplete metadata to inconsistent habitat classification and digitising practices. At the same time, this work recognises that BNG is still evolving. As Natural England guidance continues to develop and local planning authorities refine their approaches, additional expectations around GIS data will inevitably emerge. FRIDAS is designed with that reality in mind, remaining adaptable to policy change, practitioner feedback, and new technologies, so that spatial data can continue to support credible, transparent, and durable biodiversity outcomes.
