Malcolm Atkinson
Emeritus Professor
Member of Artificial Intelligence and its Applications Institute
Research Interests
Keywords: Data-intensive computing; scientific workflows; facilitating data-sharing; methodologies to sustain multi-everything collaboration. Developing a methodology for creating and sustaining collaborative behaviour in modern consortia addressing R&D or evidence-based advice remains a key challenge. Recent progress includes progress with agreeing concepts, conceptually framed methods an their mapping to scientific workflows and diverse platforms. Critical outstanding issues include: 1. enabling precise communication with sufficient abstraction for longevity, 2. facilitating harmonised agreements on concepts, methods, data and collections, 3. crossing boundaries and facilitating user-controlled change, and 4. encouraging the co-existence of reliable stability with agile innovation. This requires methods and technical support for: 1. agreeing how to communicate across discipline, organisational, legislative and system boundaries using terms that retain their meaning as details evolve; 2. agreeing and implementing rules on how data should be used and establishing sufficiently complete protected provenance to verify compliance; and 3. providing infrastructure that enables this in co-existence with encouraging innovation. With obvious immediate benefits to encourage adoption and retention of new methods and platform features. It also requires patterns of incremental adoption to minimise disruption. Innovations include: 1. data-streaming workflows mapped unchanged optimally to many distributed systems, 2. equal harmonised treatnent for concepts, methods, data and collections, and 3. support of a hierarchy of work contexts to enable different modes of work and rates of adoption to productively co-exist.
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