4 Predictions for Geospatial Data in 2022
We spoke to Seb Lessware, 1Spatial's Chief Technology Officer, about the top trends in geospatial data for 2022.
1. Cloud APIs enable ‘system of systems’
An ongoing trend that shows no sign of slowing is the growth in organisations providing software and services via cloud APIs which make it faster and easier to build solutions by connecting these services as a system of systems. This enables the development of powerful and valuable automated processes which access data remotely and create added value from these resources.
These services and the systems which use them will really grow and accelerate this year. There are many data services being set up in this way; some are pay-for-use and some are no-cost but in both cases, providing secure and controlled access to them is vital.
2. Security concerns put pressure on the spatial industry
As demonstrated by the fallout from 2021's dramatic log4j vulnerability issue, privacy and security of cloud services is a hot topic and a global IT problem for which there are many existing standards and best practices. The spatial industry will continue to be forced to 'grow up' fast by ensuring the services they deliver are following these security best practices.
Spatial data has additional security implications though: It often represents physical assets which are sensitive from a national security perspective, and it can also represent the location of people which brings privacy concerns if not carefully managed.
In addition, the benefit of spatial data is that it doesn't need to be explicitly linked together in order to gain new insights because the linkage can be inferred from spatial proximity and so the security of spatial data - who can access it, when and for what purpose - is even more important than many other types of data.
3. The demand for clean and usable 3D data will increase
A big news item going into 2022 is Facebook declaring their intent to create a metaverse of 3D virtual worlds for online interaction and their rebrand as Meta. If this gets off the ground, then it will drive big demand for clean and usable 3D data. While this could be no different to the large amounts of gaming data out there, there is likely to be demand for the metaverse to include representations of the real world in 3D and for more than just visualisation.
Geospatial data providers may see this as another reason to accelerate their creation of 3D content because they are a natural source for this real-world data. This is also likely to increase interest in creating more processes for integrating indoor and outdoor data in 3D and for automating data capture and use of machine learning.
4. Data governance, provenance, quality and trust will continue to grow
GIS Data governance remains undoubtedly one of the most important requirements in a GIS project. All of the GIS data-driven needs we are now seeing will add to the volume and update frequency of spatial data, highlighting the importance of mastering data quality and provenance and, ultimately, trust of the data.
As the role of machine learning in data governance increases, it will be interesting to see which machine learning approaches are delivering actual value for managing and analysing this data. Machine learning for data analysis is now common practice, and we see machine learning starting to be used more for generating new data, but the question remains whether the resulting data is of a high enough quality to be used and trusted.
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