Data, and research for applications and models (DREAM) : scoping study report

Giles, J.R.A.; Hughes, A.; Kessler, H.; Watson, C.; Peach, D.. 2010 Data, and research for applications and models (DREAM) : scoping study report. Nottingham, UK, British Geological Survey, 75pp. (OR/10/020) (Unpublished)

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Many scientific disciplines have been modelling during the past 5 to 10 years in order to best understand and analyse the processes and conditions within their areas of interest. This has led to a multitude of discipline specific models, modelling system software and workflows with greater or lesser success depending upon the quantity and sources of data and complexity within the scientific discipline concerned. There is now a growing realisation that to answer the most pertinent questions of the age such as climate change, sustainable and natural resources we need to model whole Earth system science, bringing together climate, ecological, hydrological, hydrogeological, geological and socio-economic models to name but a few in order to provide the necessary framework in which decisions upon prediction and planning can be most appropriately undertaken. This has become most apparent within the British Geological Survey (BGS) from the wide variety of differing geoscience models generated in the past few years that need to be interlinked to fully understand the subsurface. To this end the ‘Data and Environmental Modelling’ (DAEM) Scoping Study project was commissioned to assess the current situation and make some preliminary recommendations in order to make steps towards a more joined up and semantically harmonized future in environmental modelling. Vision: Our vision is to provide scientists with the data, tools, techniques and support to address trans-disciplinary environmental questions impacting on human society. We hope to achieve this by being a leading member of an open community that will share data, applications and environmental models thus enabling collaboration and achieving sustainable solutions. The investment and knowledge captured within the many existing scientific models is a significant resource and not one that could be easily replicated in any new centralised environmental modelling software. The intrusion upon existing legacy modelling workflows and knowledge held for many collaborative partners would be too much to bear. Considering these acute disadvantages of centralisation, the alternative approach of ‘linked models’ passing parameters at runtime is seen as more pragmatic, achievable and cost-effective solution. This solution brings together the best and most appropriate scientific models and allows the various scientific disciplines to continue development of their current models as their knowledge is enhanced. Linkage of models has been discussed and considered by many to be the most appropriate answer and the most mature solution currently developed is the European Union (EU) supported Open Model Interchange (OPENMI). With critical underpinning activities such as data management, semantics, vocabularies and ontology’s, understanding of linked model uncertainty and visualisation, OPENMI presents an opportunity to address the present disparate nature of scientific models and move forward in understanding the whole Earth.

Item Type: Publication - Report
Programmes: BGS Programmes 2010 > Information and Knowledge Exchange (Information Management)
Funders/Sponsors: NERC
Additional Information. Not used in RCUK Gateway to Research.: This item has been internally reviewed but not externally peer-reviewed
NORA Subject Terms: Earth Sciences
Data and Information
Date made live: 24 Aug 2010 09:28 +0 (UTC)

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