Models in the Cloud: Generative Software Frameworks to Support the Execution of Environmental Models in the Cloud

Cloud computing is one of the most important technological developments of the last few years, with the technology having a major and transformative impact on many areas of society and the economy. For example, cloud computing underpins developments in smart cities, ecommerce and eGovernment and also provides the storage and computational capabilities that underpin data science (cf. big data).
The software support offered by cloud computing is however in its infancy and is tailored towards particular styles of application. This is particularly true with respect to computation in the cloud, where the programming approach offered by the computational framework MapReduce dominates and yet MapReduce assumes a particular style of programming where potentially massive data sets are analysed by a map() operation before results are collated through an associated reduce() operation. This is powerful but very limited.
In parallel, researchers are also interested in realising the benefits of cloud computing in many other areas of application. This project focuses on the support offered by cloud computing to Environmental Science and, in particular, to the execution of potentially complex environmental models in the cloud. This is an area of huge significance, with environmental modelling being the key tool to evaluate uncertainty, risk assessment, and mitigation strategies around flood/ drought, food security and the impact of climate change (with major consequences for the economy and for society). We particularly focus on the principles and techniques in the key areas of Platform as a Service (or PaaS), effectively the middleware for cloud computing. The central insight is that services at the PaaS level need to be more carefully tailored to the needs of key application domains, including but not limited to support for the execution of complex environmental models. We advocate a novel approach based on a combination of model-driven engineering coupled with software frameworks and argue that this enables a paradigm shift in terms of the flexible and tailored support offered by cloud computing for given application domains.
Key beneficiaries of this work include the computer science communities working on model-driven engineering and cloud computing, researchers from environmental modelling in areas ranging from climate change modellers to flood prediction, and also key stakeholders related to environmental management and we include an exciting range of partner institutions from this area to maximise the impact of this work.

The proposed research is well balanced between cutting edge research and impact on society and the economy. In terms of the latter, we seek a transformational impact on the target scientific community and also on users of environmental models who deal with uncertainty, risk assessment, and mitigation strategies around flood/ drought, food security and climate change. We adopt a multi-faceted impact strategy around the following strands (discussed in more detail below):

1. The establishment of an Experts Group as our key vehicle for end user engagement and dissemination and exploitation (new insights and approaches);
2. Working with appropriate bodies to seek a transformative impact on how Environmental Science more generally is carried out (new paradigms);
3. Working with those involved in big data initiatives in the UK to enhance infrastructure capabilities for environmental modelling (new tools);
4. Working with another research institute (EBTIC) to generalise the results beyond Environmental Science (new avenues).

This is supported by a series of strategic partners, and their their roles are summarised below.

Centre for Ecology and Hydrology (CEH): bringing domain knowledge around environmental modelling and access to NERC cloud infrastructure; supporting strands 1, 2, 3.
Community Earth System Model (CESM) via NCAR: bringing domain knowledge around environmental modelling (climate change); supporting strands 1, 2.
JBA Trust: bringing domain knowledge and application of environmental modelling to a range of real world problem domains; supporting strands 1, 2.
UK Earth System Model (UKESM) via Met Office/ NERC: bringing domain knowledge around environmental modelling (climate change); supporting strands 1, 2.
EBTIC: bringing domain knowledge around next generation networks, MDE expertise, generalisation of results; supporting strand 4.

As well as these impact strands, we also plan public engagement activities which we believe are important in scientific research (will include public lectures and Café Scientifique events).