1Spatial : Creating a sustainable SDI using Open Standards

Previously, we discussed why Modern Spatial Data Infrastructures (SDIs) are crucial for creating a spatially enabled society.

So how do you go about creating one, and making sure it is sustainable?

Getting the right data to the right party at the right time

How do we ensure that we supply data to the right people? And that they are able to consume it in the way they need? This comes down to Open Standards. In fact, it also invokes a classic architectural principle - that of high cohesion. High Cohesion means that content (information, in this case) supports a central and related purpose. So getting data to the right party means that we are able to encapsulate data needs in a service to them. GDS (Government Data Service) specifically advocates this: structured public sector generated data is specific to a particular subject matter, and is supplied via APIs.

The ideal mechanism is to provide data as part of a SDI, supplying all the data that a party needs, but no more. Hence it becomes incumbent on the data provider within an SDI to appreciate the needs of the consumer.

Providing access to data through a wide variety of channels

Where data is to be provided for general consumption, it should be provisioned under the assumption that it will be used and visualised over a wide variety of channels and devices.

For instance, data may be viewed over a mobile device with limited network bandwidth, whilst simultaneously being consumed into a huge, enterprise-class system. This may mean that the same data is exposed through lightweight protocols whilst also being provided in large batches.

Standards such as those created by OGC, styles such as REST, and patterns like publish-subscribe enable different methods of provisioning that will engender a wider variety of consumption - and therefore generate more benefit from data exposure.

Describing purpose using metadata

Data is often captured for a single purpose, but wider benefits can be imagined through exposure. All the same, there may be limitations of the data based on its original capture method and purpose. Declaring the original intent of capture and any constraints allows consumers to determine its fitness-for-purpose.

Within an SDI, this may mean that it is selected or rejected for inclusion. Moreover, it generates a discussion on what would need to be performed on the data to bring it into an SDI. This may mean incremental improvements, resulting in its scope of use being substantially extended, generating benefits for what is a small uplift in cost. If metadata itself adheres to open standards, the process of decision making is even easier as consumers can compare data sets like-for-like.

Providing assured quality of data

Being able to describe data quality in a way that is measurable assures consumers of its trustworthiness.

If data is being supplied as part of an SDI, the total value of data within the SDI is raised when it has assured and demonstrable quality. Supplying accuracy parameters as part of metadata that has been generated by tools, as opposed to by eye, substantially raises the value of that data and provides credibility to data within the SDI as a whole.

Open Standards

Open Standards facilitate the exchange, sharing and quality of data and in particular, geospatial information. They enable more data management operations to be automated. Emerging standards such as the OGC's Geosynchronisation Service identifies an open standards interface that enables data consumers to propose changes to data providers' interface content, which may include requests for new content or to modify data that is currently being provisioned.

As Open Standards improve and mature, they in turn become incorporated into more software solutions, and more opportunities arise. This becomes a positive feedback loop as the value of services (and the underlying data they provide) grows.

The use of open standards is a fundamental element to data foundations (infrastructures) as per the National Data Strategy.

Poor data quality and, relatedly, a lack of agreed standards are clear barriers to the effective use of data, from basic record-keeping to cutting-edge applications of data-driven technology.

Responses to our call for evidence and stakeholder engagements highlighted common issues around:

• a lack of ownership of data standards/metadata/APIs
• a lack of skills in managing and using data
• the pace of change leading to a fragmentation in the systems used to manage data, with ongoing resourcing issues linked to set up and maintenance costs

Facilitating the Future

The rate of data generation is already immense, and will only increase exponentially. Similarly to how the internet sits on a set of principles, standards and protocols, continuous benefits for data usage can only progress if standards and protocols are agreed and maintained.

Building physical services in line with expectations will only happen if access to underlying digital and data services are in place, easy to access, and trustworthy. Modelling physical entities as Digital Twins enables a rapid path to creation, but Digital Twins within the context of modern physical infrastructure require a representation of real-world entities in an agreed and open way. We'll only be able to do this with SDIs that sit atop open standards, that facilitate access via the Q-FAIR principles, and enable end users to decide on fitness-for-purpose based on representation and quality.

1Spatial's platform both facilitates and embraces the use of open standards to ensure quality and exchangeability - and to make sure both producers and end users have confidence in data; its fitness-for-purpose, and the ability to add value to whatever projects are going to make use of it. Our pedigree is in providing data to organisations that contribute to SDIs that are considered trustworthy, shareable, form the backbone of future decision-making and the creation of new digital technologies that are part of strategies that stretch out over the next twenty years.