The fourth industrial revolution is changing how geoscience is carried out, how information is shared and how society and people engage with the world around them and with scientific discovery and data. Geoscience plays a crucial and central role supporting solutions to societal challenges such as the energy transition, understanding (and mitigating) geohazard risks and ensuring environmental sustainability and resilience. From a geodata management point of view this will only be achieved through an end-to-end data management process, from acquisition to delivery of quality-assured data.
As we strive to understand ever more complex and interdependent earth systems we must have access to trusted and authorative data. This is critical for the development of our geoscience knowledge through the exploitation of emergent technology such as Artificial Intelligence, Machine Learning, Digital Twins, and the further use of autonomous systems. These new technologies will enable us to ‘forecast’ future scenarios, as well as develop ‘hindcasting’ techniques to calibrate and confirm hypotheses. Increasingly, modelling approaches informed by sensor networks and edge computing approaches drawn across the Internet of Things (IoT) and by novel data sources such as that from citizen science can also be used to develop ‘nowcasting’ techniques. This a key component of Digital Twin approaches. All of these new areas of digital geoscience research are reliant on well managed data.
With the increasing access and availability of digital information in all areas of society, there is an expectation of openness and transparency in information used for evidence and decision making, especially from publicly-funded research institutes. Appropriate, ethical and responsible use of geoscience data and models, especially around the use of emerging technology, is essential.
A fundamental requirement is that geoscience data is trusted, secure, authoritative and FAIR (findable, accessible, interoperable and reusable). To preserve data and to make data FAIR requires Trusted Repositories that follow the TRUST principles for digital repositories (transparency, responsibility, user focus, sustainability and appropriate technology).
Open science has led to journals requesting access to both supporting data and models, and to data journals dedicated to data as a primary research output. This requires national data repositories to be certificated as trusted repositories and collaboration across the global geoscience community to enable interoperability and reuse.