Information Advantage in Space - Capitalising on the Data Revolution
Not since the space race in the last century has the space domain experienced such an exciting and dramatic change. As late as the 1990s, space launches were considered a national event, but with the advent of technological innovation, cost reductions and relaxing of the rules governing space access, commercial satellite constellations are now being launched with little fanfare or mainstream coverage. This is taking the total number of space platforms in Low Earth Orbit (LEO) to nearly 2000, including a host of commercial providers offering a range of valuable services.
Many different sectors are benefiting from this significant market development. In the earth observation market alone, environmental monitoring, smart agriculture, meteorological survey and the energy sector are areas that have been revolutionised by the advent of commercial space-based data collection. From a defence and security perspective, nations and their relevant intelligence organisations are also developing how commercial space-based ‘Intelligence, Surveillance and Reconnaissance’ (ISR) can support them, including how the collection of vast data sets – including imagery and geospatial information – can be consumed and used effectively.
This is where we see a significant challenge. How do we convert this deluge of data from multiple satellite and sensor providers into something useable? The question of handing the ‘volume, velocity, variety and ubiquity’ of data is starting to have profound effects on the role of humans tasked with engaging with this data. In the defence and security domain, this includes the intelligence analysis community. These skilled people are tasked with taking data and converting it into usable information and insightful intelligence – but they can only deal with so much data effectively. The former head of the United States’ National Geospatial Intelligence Agency (NGA), Robert Cardillo said that without technical tools and support, an extra 8 million analysts would be required to analyse all of the data coming from new data sources – including commercial space-based collection. Given how unlikely hiring 8 million extra analysts is likely to be, and the monumental challenge of processing and organising this data – another solution is needed.
This is where space technology meets Information Advantage back on earth – what the UK MOD describes as ‘the advantage gained through the continuous, adaptive, decisive and resilient employment of information’ - this means that there is not an end game to be won – but a continuous, ever faster cycle of exploiting data effectively and supporting decision-making. In order to deal with the data and to move quickly enough – this is going to take a significant shift in the way humans interact with their technology. Concepts such as Human-Machine teaming and the insertion of machine intelligence into day-to-day operations is well documented but it is now, with the quantity of data that is available, will these technological innovations be so essential – especially when combined with the vast amounts of Publically Available Information (PAI) collected via the internet every day. This represents another challenge - if this data is available to us, then it is available to everyone. Regardless if you are the United States government or a teenager in their bedroom, we all potentially have access to everything. Only by moving at the pace of relevance – machine speed – can we hope to keep our edge with understanding the data that is out there.
So how do we move faster? There is no doubt that technology holds the key to managing the flood of data, but technology cannot be integrated in isolation. Over the next 10-15 years, there will be transformational change in the way we engage with data, including large, complex data sets from space sensors – how it is collected, processed, fused, stored, organised, assured, trusted, analysed and visualised are all likely to see major developments. Our interaction with systems and processes will mean that Agile Software Development and IT Operations (DevOps) approaches will be commonplace, with system changes made daily and algorithmic updates hourly depending on mission requirements. We will be in a world where the boundaries between operations, experimentation and training become blurred. Data Scientists will train machines – analysts will be supported by machines – machines will help develop analysts – and all in a constant cycle of improvement, integration and action. In turn, this will improve how we manage, task and ultimately collect further data whilst refining the next generation of space collectors and look to fuse the data they provide with the widest possible sources that are available.
The data revolution is here. Our people, our wider organisations and our ambition need to be ready to realise the challenges and the limitless benefits that this revolution will provide.
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