The Bridging from Concepts to Data and Computation for eScience (BC2DC’19) Workshop will be held in conjunction with eScience’19 on Tuesday September 24, 2019 in San Diego, CA.
- Papers due:
July 10, 2019July 15, 2019
- Paper Acceptance Notification: July 24, 2019
- Camera-ready deadline: July 29, 2019
- Workshop: September 24, 2019
How can we enable e-Science developers to conceptualize research and translate it to system requirements?
How should we make such processes understandable, reliable, stable and sustainable?
How should advances in engineering deliver the expanding power of distributed computation, heterogeneous (cloud and data) platforms and the massive – still rapidly growing – wealth of data?
How can we make it easier for organizations and researchers to engage in multiple research collaborations and to adapt rapidly to changing requirements and new opportunities?
Research addressing global challenges federates a growing diversity of disciplines, requires sustained contributions from many autonomous organizations and builds on heterogeneous evolving computational platforms. Scientific knowledge is scattered across cloud-based services, local storage, and in source code targeting specific architectures and computational contexts. Concepts reflected in disparate sources are hardly computer-communicable and computer-actionable across or even within disciplines. This makes traceability, communication of methods, provenance gathering and reusing data and methods harder and more time-consuming. Agile response to new needs and opportunities may be accelerated when the available methods and required components have mutually comprehensible descriptions. Commercial clouds play an increasingly important role in large-scale scientific experimentation. Examples of diversity in technology and jurisdiction, as well as in the large-scale exploitation of clouds can be found on both sides of the Atlantic: in the European Open Science Cloud (EOSC) as well as in the ongoing massive migration of data and other resources onto Amazon’s AWS by NASA.
It follows that while potential for large-scale data-driven experimentation increases, so does complexity as well as the risk of getting locked into vendor-specific solutions. To deal with these challenges and to help researchers make better and transparent use of diverse infrastructures many systems propose higher-level abstraction to hide and orchestrate infrastructural and implementation details. Domain experts need to directly control sophisticated and dynamic concepts pertaining to data, execution contexts and diverse e-infrastructures. Furthermore, they need mechanisms that allow them to take responsibility for the quality of results, without distracting technological artefacts.
These often take the form of service-based platforms, containerised solutions, APIs, ontological descriptions of underlying resources, provenance repositories, etc. This workshop focuses on platform-driven and domain-specific developments that contribute towards unifying underlying platforms, clouds, data, computational resources and concepts in order to empower research developers to deliver, maintain and communicate larger, increasingly complex eScience systems.
In particular we welcome contributions in the following areas, not excluding other topics of interest:
- Semantic concept description and implementation
- Specification and execution of conceptually formulated methods
- Component descriptions facilitating reliable composition
- Architectures, frameworks and design patterns delivering flexible use and incremental composition
- Cloud, fog, edge and specialized platforms
- Pervasive and persistent provenance
- Platforms of platforms, containers, orchestration and microservices
- HPC computing over Cloud