We all know how locked down and controlled 2020 has been. Paradoxically perhaps, this very act of containment has driven an increased use of world mapping data and geospatially-aware software, as we seek to find out what’s happening around the planet. Right now, we really don’t want to be lost on the map, more than ever.
A large number of Covid-19 (Coronavirus) news reports have featured local, national and global statistics graphically depicted across mapped-out regions of the planet. Behind these color-coded charts, graphs and diagrams are software programs designed to ingest, process, analyze and deliver accurate location-based data to provide us with a geospatially-aware representation of what’s happening.
In many cases, the data these applications use draws upon the same information source as is used by public sector organisations, governments, emergency services and businesses. In the United Kingdom, that source is very often the Ordnance Survey, the national mapping agency for Great Britain.
As a public body working for the public good, the Ordnance Survey’s software and data team suggest that barriers to accessing geospatial data have been lowered; not least by Ordnance Survey itself, which launched the OS Data Hub – a repository of its own trusted geospatial data – in July of this year. What this leads to is the suggestion that software developers inside commercial organisations could and perhaps should also be embracing the chance to put more location-aware information into the applications that we all use every day.
With some obvious caveats related to security and compliance, geospatial data is everywhere and it’s (mostly) for everybody.
Senior technology labs engineer at Ordnance Survey Tim Manners, alongside John Hoopes, developer advocate at Ordnance Survey say that they understand the ‘commercial opportunities’ that can be unlocked by this data, as well as its potential to help us address some of the most pressing issues of our time.
A brief history of geospatial data
But first, Manners and Hoopes insist a brief layperson’s history lesson in geospatial science is needed. This is because, when it comes to the world of geospatial data, there are two core communities of users.
The first geospatial data user group has been around since the first Global Information Systems (GIS) systems were developed in Canada in the 1960s. These users lived (and still live) and work in desktop GIS applications like QGIS, CadCorp and Environmental Systems Research Institute (ESRI) products such as ArcGIS, ArcMaps, ArcGIS Pro etc.
“This [first, original] community has always been mainly focused on geospatial data analysis and – usually – the production of static maps, which are still very much relevant for many communities and industry use cases including applications in geography, topography, real estate, urban planning and so on. These users are geographically-minded and comfortable with complicated technical data formats, such as ‘shapefiles’, that are difficult to use without a good grasp of GIS principles,” explain the pair.
They note that the second community arose with the advent and maturation of web 2.0 and they came in the form of application developers, who started on the web and then added Apple iOS-native and Android-native mobile apps to their repertoire. This community has very different ways of working with geospatial data and its requirements vary too.
From purist propellerheads to programmers… to people
Manners and Hoopes note that the first location-based apps were always more logically likely to be built by developers who had some interest or background in GIS, as geospatial data formats were difficult to work with.
But today, data formats are far easier to work with because of the advent of platform-level software tools that can provide technology abstraction layers, built-in AI intelligence, Application Programming Interface (API) connectivity channels and various autonomous functions. All of which mean that many more forms of geospatial data can be used by all manner of software professionals… and not just geospatial data purists, who do still exist.
“A decade ago, large datasets (which geospatial datasets often typically are) were hard to get hold of and difficult to consume right away. It might have been hours before the data could be broken down and sorted into a format that was fit for purpose. Now, thanks to hosted services, open source tools, APIs and increased bandwidth and computational power, developers can readily access the data they need and create an application, or install a geospatial or mapping visualization in an existing app, in a matter of minutes,” explain the pair, who both clearly played with a lot of maps as children.
As with other areas of software application development and data management, a significant factor driving adoption of any technology is the presence of standardization. Some software tools in this space are proprietary but still heavily standardized according to defined industry protocols, but this is not a given. So there is another avenue here. By adopting open standards, developers can independently create tools that interoperate with data and tools provided by others.
As an open software geospatial tool (or indeed any kind) gains more adoption, the tool’s ‘gravity’ is said to increase and a virtuous circle and cycle develops. As adoption increases, further development of the tool increases and it makes more sense to build according to the standard of the tool itself. Geospatial standards of this kind include GeoJSON, Mapbox Vector Tiles (and on the OS Data Hub) the Maps API, with ZXY and WMTS endpoints and the Features API, which is a web feature service.
“Firms understand that usability is a key factor for developers when they embark on a creative journey. Data formats that ‘play’ better with others will likely be favored over those that require laborious integration and weak support. Increased accessibility and usability also have the effect of widening the geospatial developer community and the potential for innovation, which is already paying dividends in a number of ways,” insist and enthuse Manners and Hoopes.
Real-world use cases for geospatial data
For a working example in the real world, the ‘insurtech’ (insurance technology) industry makes use of geospatial data to help manage building insurance. An insurer can take relevant local data points into consideration when creating policies that could include everything from local crime rates, to flood risk and onwards to proximity to fire and police stations.
Manners and Hoopes are all for the greater good of humanity and the pair explain that applications in this area could help with environmental management, town and transport planning, emergency services and more. Even more advanced use cases, such as augmented reality applications for gaming or proptech (you guessed it, property technology) applications made possible by vector tile APIs, are emerging.
“Many of the mobile devices we carry with us, as well as the individual applications installed on them, use location data in some form. Geospatial data can provide better experiences for users in a variety of ways, and not just through obvious use cases like mapping, routing and navigation. Mobility apps help users get from A to B efficiently. House-sharing apps help users explore the world from a comfortable home base. Dating apps connect singles to people nearby. Location data helps developers create experiences that are more valuable to their users,” conclude the Ordnance Survey men.
These are still early days and this is (very arguably) an important growth area. With global pandemic data being fed into Covid-19 viral infection ‘track-and-trace’ apps (which have been notoriously troublesome with spurious alerts being sent to individuals), these geospatial data streams also have to work with the WiFi, Bluetooth and mobile network connectivity on our mobile devices.
There’s a lot we could get less than perfect (let’s stop short of saying wrong) if we engineer geospatial capabilities into our apps without prudently planned architecture, adherence to standardized protocols and accessibility to the right trusted datasets.
Today we can work with geospatial data in three dimensions, perhaps even four dimensions if we add time. As we enter the fifth and sixth dimension and start to see the ‘plane’ where other possible worlds will exist, geospatial data’s wider limits could be coming with us.
Note to the team: we’re going to need a bigger server guys.