1Spatial : Why Modern SDIs are essential for a sustainable spatially-enabled society

As we move deeper into the 21st Century, more and more prominence is given to data. Automation is starting to become key, driven by industries such as EVs, the levelling-up agenda, and the race to Net Zero Carbon.

Data collection has often been done to suit the needs of the organisation capturing it. Understandably, utilities, highways authorities, telcos, and government departments, have raced ahead with using their own data for their own purposes, with the secondary notion of sharing it with others if needed. However, what we are now targeting is the idea of a spatially enabled society.

As much as infrastructure assets themselves have an intrinsic value, organisations are realising that the data associated with those infrastructure assets have their own worth. This value is naturally increased as data follows the principles of the Geospatial Commission's Q-FAIR Framework: Quality, Findable, Accessible, Interoperable, and Reusable. So, the value of data is not just about its original intention: it is about how it can be made fit for wider purposes. By applying the Q-FAIR Framework, we can extend the value of our data with proportionally less effort than it took to capture it in the first place.

The Open Data Institute (ODI) highlight these key areas of a data infrastructure:

• Data Assets such as identifiers, registers and datasets
• Standards used to enable the sharing or exchanging of data assets between multiple parties
• Technologies used to curate and provide access to data assets
• Guidance and policies that inform the use and management of data assets and the data infrastructure itself
• Organisations that govern the data infrastructure
• Communities or Suppliers involved in contributing to or maintaining data assets, and those who are impacted by decisions that are made using data assets

These all apply to modern and sustainable spatial data infrastructures (SDIs), as we implement them to create sustainable methods of sharing our data and extending its value.

An SDI is essentially a co-ordinated set of policies, technical and data standards, and interfaces that enable the discovery, use and re-use of geospatial information to provide additional uses. It is a formal way of increasing the value of data beyond its original purpose, with the aim of facilitating greater use, enabling new ways of working and - ultimately increasing the size of the economy.

As such, SDIs are an essential aspect of the "DNA" of any organisation or country. In the UK, an SDI can create value out of data to assist with:

• Revitalising networks such as improving our roads, railways and broadband coverage
• Levelling-up communities and regions that have previously been left behind by society and investment
• Moving to net-zero greenhouse emissions by 2050, by transitioning towards cleaner and more sustainable energy
• Building a million new homes to provide affordable housing to the people who need it, where they need it
• Preparing the UK for electric vehicles and autonomous transport
• Leading the world in agricultural technology and land management

A great example of an SDI in action is Ordnance Survey Ireland's PRIME2 initiative. PRIME2 provides data and APIs for a fully digital, object-based representation of real-world features with persistent identifiers and a defined feature lifecycle- not just a cartographic snapshot of the data. This initiative completely fulfils the definition of an SDI, as it spans politics, data models, and the method of accessing them. PRIME2 creates the underlying framework on which to base governmental, business, and individual data structures with a spatial aspect, and integrates these with each other. This isn't just about creating spatial or cartographic relationships as we traditionally would in GIS, but the actual connectivity - the real relationships between real-world features to enable interoperability, modelling and the creation of planning and what-if scenarios.

The key principles for the creation of an SDI are:

• Ownership - so that the responsibilities of the provision of data are identified and shared
• Declaration - so the original use of the data (the use for which it was originally captured) is identified, as well as its future potential fitness for purpose elsewhere
• Consistency - using automated workflows, the enablement of data stability and consistency over time is taken away from being a manual effort, making it even more trustworthy
• Transformation - ensuring that data, from whatever source, adheres to the policies, standards and descriptors being applied (which may include a level of remodelling)
• Validation - ensuring data quality is maintained, which is particularly important when data is used outside of its original purpose
• Access - that data can be discovered and accessed easily; its metadata description is consumable (by humans or other systems)
• Visualisation - that data can be visualised in a variety of ways, especially blended with other geospatial data according to use case
• Usability - outside of GIS, data should be enabled for use in other systems in a non-traditional way (often not rendered as a map, but as part of a completely different application)

Data sets exposed and kept as part of an SDI should anticipate a future level of integration, so it's vital that the Q-FAIR principles are maintained - whilst also preserving data quality.

For deeper insight, 1Spatial have published a little book on SDIs. The book identifies a number of SDI examples already underway, including OSi.

1Spatial are exhibiting at the prestigious Cambridge Conference 12-14^th April, where the leaders of the worlds national mapping organisations come together, typically every 4 years with a focus on exploring common challenges the global geospatial community faces. This years theme is how location data is at the forefront of tackling the climate crisis and SDIs are fundamentalto this. At 1Spatial we believe that when Governments have access to coherent and current data, the likelihood is they can make better and faster decisionsin the fight against climate change, while delivering a smarter, safer, more sustainable world.

Next time we'll look in more detail how we go about creating a modern and sustainable SDI, and how Open Data standards are essential to this process.