98 research outputs found
29th Annual Computational Neuroscience Meeting: CNS*2020
Meeting abstracts
This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests.
Virtual | 18-22 July 202
Methodology to sustain common information spaces for research collaborations
Information and knowledge sharing collaborations are essential for scientific research
and innovation. They provide opportunities to pool expertise and resources. They are
required to draw on today’s wealth of data to address pressing societal challenges.
Establishing effective collaborations depends on the alignment of intellectual and
technical capital.
In this thesis we investigate implications and influences of socio-technical aspects
of research collaborations to identify methods of facilitating their formation and
sustained success. We draw on our experience acquired in an international federated
seismological context, and in a large research infrastructure for solid-Earth sciences.
We recognise the centrality of the users and propose a strategy to sustain their
engagement as actors participating in the collaboration. Our approach promotes and
enables their active contribution in the construction and maintenance of Common
Information Spaces (CISs). These are shaped by conceptual agreements that are
captured and maintained to facilitate mutual understanding and to underpin their
collaborative work.
A user-driven approach shapes the evolution of a CIS based on the requirements of
the communities involved in the collaboration. Active users’ engagement is pursued by
partitioning concerns and by targeting their interests. For instance, application domain
experts focus on scientific and conceptual aspects; data and information experts address
knowledge representation issues; and architects and engineers build the infrastructure
that populates the common space.
We introduce a methodology to sustain CIS and a conceptual framework that has
its foundations on a set of agreed Core Concepts forming a Canonical Core (CC). A
representation of such a CC is also introduced that leverages and promotes reuse of
existing standards: EPOS-DCAT-AP.
The application of our methodology shows promising results with a good uptake
and adoption by the targeted communities. This encourages us to continue applying
and evaluating such a strategy in the future
25th Annual Computational Neuroscience Meeting: CNS-2016
Abstracts of the 25th Annual Computational Neuroscience
Meeting: CNS-2016
Seogwipo City, Jeju-do, South Korea. 2–7 July 201
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