NC Data Service

Lead Research Organisation: University of Leeds
Department Name: National Centre for Atmospheric Science


The collection, management and exploitation of data is an integral part of modern environmental science. NERC's policies associated with data span all aspects of NERC's funding routes and branches of environmental science. A key part of the implementation of these policies requires NERC to fund and manage five environmental data centres: the British Oceanographic Data Centre (BODC), the Centre for Environmental Data Analysis (CEDA), the Environmental Information Data Centre (EIDC), the National Geoscience Data Centre (NDGC) and the Polar Data Centre (PDC).

This proposal is presented by a consortium of BODC, CEDA, EIDC, PDC and NGDC and presents a plan for operation and management of the data centres over the period 2018-2023. The proposal explains how each data centre will to deliver core data management. These core functions enable NERC to fulfil its data policy with the primary aim of ensuring the continuing availability of environmental data of long-term value for research, teaching, and for wider exploitation for the public good, by individuals, government, business and other organisations. The specialised knowledge and domain expertise within each data centre ensures there is a trusted repository/access point for all of NERC's environmental data. The close relationship that each data centre has with its relevant research community has a number of benefits. For example, it helps maximises the acquisition of relevant data and also allows data centre staff to easily engage with the environmental science community and promulgate good data management planning and practices.

The proposal also explains, for the first time, how coordination and management will be arranged across all five data centres. Whilst each data centre will remain responsible for the services to its particular sub-discipline of environmental science, the delivery and management of the programme will be harmonised so that the data centres will be able to report collectively to NERC.

In addition to the core functions, a second major strand of the proposal is to increase the integration/harmonisation between data centres and to support and provide services to Dodona (NERC's new initiative in spreading the exploitation of environmental data to new users and communities). Increased harmonization between the data centres will enable more sharing of best practise and use of common tools to improve both data quality and accessibility.

There is also a plan set out for capital investment in the data centres. This will predominantly be used to provide the underpinning systems, standards and vocabularies needed to increase the potential for combining NERC's diverse data sets to order to address end users' problems.

Planned Impact

NERC's environmental data is used by a very wide range of users, spanning academic, research, business and government and voluntary sectors. Where possible, the data is made freely available without charge apart from special cases that involve third party data. Users of NERC data are spread across a very wide range of countries. All of this data is made available by NERC's five environmental data centres, the British Oceanographic Data Centre (BODC), the Centre for Environmental Data Analysis (CEDA), the Environmental Information Data Centre (EIDC), the National Geoscience Data Centre (NDGC) and the Polar Data Centre (PDC). This proposal for the management and delivery of NERC's data centres is therefore at the root of a large fraction of the impact of NERC-funded research. NERC also recognises that there are additional potential users of its environmental data who for a variety of reasons have not yet been able to make use of the assets. NERC has therefore launched an initiative, Dodona, to reach out to these new users. This initiative will be supported by the data centres both through direct provision of data but also through an Integration Programme to develop services to supply diverse data sets in a seamless manner not requiring the users to have prior knowledge of the individual data sources.


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