Data Infrastructure for National Infrastructure

Description of the proposed project and the benefits being sought 

Proposal: A pilot study on the requirements and impact of supporting sharing and analysis of data across National Infrastructure systems, with a focus on energy, water and transport, and the related natural, built and social and economic environment. The study will pilot a data brokering service to underpin a data cloud in support of research into infrastructure systems operation and evolution across scales, building on the Data Analytics Facility for National Infrastructure (DAFNI). 

View DINI in detail  

Background: Our national infrastructures, such as energy, water, and transport systems, are critical to the functioning of society. Exploring the potential, impact and evolution of Infrastructure systems is an active area of research within Engineering and related disciplines with high impact on the social, economic and environmental well-being of the UK. Computational modelling and machine learning are an increasingly important part of this research, allowing researchers and policy makers to explore different options and predict the impacts on society. 

However, a barrier to the effective exploitation of this research is the availability of quality data. Data is an essential pre-requisite for good analysis and good decision making, but there are many barriers to the effective use of data, which are prevalent in the infrastructure systems engineering domain, including: 

• Discoverability: A wide variety of data sources exist in government, academia and industry; it can be difficult to understand where to look for data; 

• Licensing: Unclear access conditions on data, whether openly available or via a paid database licence, and under different and unclear Data Sharing Agreements; 

• Sensitivity: Legal restrictions on access to personally, commercially, or security sensitive data, requiring trusted environments; 

• Metadata: Poor documentation and annotation (metadata) on format (logic), semantics (meaning) and context of data, with different standards across domains, which inhibits interoperability and reuse. 

• Reliability: A lack of transparency and traceability on the data scope, quality, currency, and provenance, as well as the methods used to transform, simplify and validate the data. 

• Ethics: data centres are accumulating vast amounts of data without concern for energy use and telecommunications networks which is driving the need for smart storage and removal of data. 

To realise the potential for the exploitation of the huge amount of data within the community to drive research and the subsequent delivery of the impact of that research on policy making, a systematic approach needs to be taken when designing and building a research data cloud environment to coordinate and sustain the management of data is needed to make data in this domain more coherent and sharable. 

Objectives: DINI will have the following specific objectives: 

1. Situation analysis: Identify the benefits and barriers to data sharing, exchange and reuse for infrastructure systems data and related domains – for example by enabling communities to connect across data platforms for multi-disciplinary research, to deliver impact across themes. 

1. Data publication support: Recommend best practises to enable the FAIR publication of and access to infrastructure systems data, including data policy and data sharing agreement templates, and data annotation and terminology including ontologies and the use of Digital Object Identifiers. 

1. Enabling services: Pilot data brokering services to catalogue and provide access to infrastructure data and make it available for interoperation and reuse in traceable analysis processes. 

1. Benefits realisation: Demonstrate potential benefits via case studies on the use of interoperable data in cross-domain scenarios.

Contributes to the objectives of this initiative.

DINI will address the issue of cross-discipline data sharing to support infrastructure systems research, including into related natural and human environmental domains, and thus aid data discoverability. It will address the culture of data sharing via the provision of policies and guidance on Data Sharing Agreements and support data sharing within secure neutral research spaces, backed up by pilot brokering services and pilot demonstrators. It will enhance the provision of FAIR data via the use of common annotation standards implemented in the brokering tool and via using traceable provenance in the DAFNI platform. It will consider the role of Trusted Research Environments (TRE), especially for commercially and national security sensitive data.  

Delivery Plan

DINI will be delivered by the DAFNI team at STFC, in collaboration with teams in the Energy Data Centre (EDC) and the Centre for Environmental Data Analysis (CEDA) within STFC that are already supported by UKRI.  

Preparatory Phase (M1-M4)

The project plan will be refined, and the team extended with leading members of the research community drawn from the UKCRIC DAFNI Consortium of 12 Universities, invited to participate as “project champions” via a targeted research call to draw upon their expertise in domain science e.g., energy, transport and water. Champions will lead consultations with their communities, provide thought leadership and specialist expertise in research data sharing, and further use case demonstrators.   

How the proposed project is complementary to existing activities.

DINI is closely aligned to the DAFNI partnership of STFC and 12 leading research universities. DAFNI focusses on supporting sharing computational models and does not currently provide a data brokering service to access and publish FAIR Data, thus DINI would be highly complementary to the DAFNI platform, providing a mutually enhanced capability. Further, DAFNI is developing a Centre of Excellence under the Building a Secure and Resilient World (BSRW) programme of UKRI, and DINI will enhance the resilience scenarios being explored in that programme. More widely, DINI will complement and extend the existing activities of the EDC (funded by EPRSC) and CEDA (funded by NERC) providing a route to the further exploitation of their data holdings in cross-disciplinary applications. Further the Dis aligned with EPSRC Digital Twin activities, including the recently funded Digital Twin Network+, led by the Alan Turing Institute. DINI is complementary to the DRI DARE programme and will work with DARE in extending the use of TREs to support commercial and security sensitive data. The initiative is also complementary to private sector approaches to data sharing in particular domain sectors, by considering multi-disciplinary integration and making the data accessible to research and other public bodies.