Bridging from Concepts to Data and Computation for eScience (BC2DC'19)

A workshop co-located with the eScience 2019 International Conference

Accepted Papers and Presentations

  1. Keynote: Data Driven Collaboration: a Social Construct for Multidisciplinary Scientific Discovery by Carl Kesselman
  2. Active provenance for Data-Intensive workflows: engaging users and developers by Alessandro Spinuso, Malcolm Atkinson and Federica Magnoni
  3. Modeling and Matching Digital Data Marketplace Policies by Sara Shakeri, Valentina Maccatrozzo, Lourens Veen, Rena Bakhshi, Leon Gommans, Cees de Laat and Paola Grossoi
  4. Bridging Concepts and Practice in eScience via Simulation-driven Engineering by Rafael Ferreira da Silva, Henri Casanova, Ryan Tanaka and Frederic Suter
  5. Managing Scientific Literature with Software from the PORTAL-DOORS Project by Shiladitya Dutta, Pooja Kowshik, Adarsh Ambati, Sathvik Nori, S. Koby Taswell and Carl Taswell
  6. Towards a new paradigm for programming scientific workflows by Reginald Cushing, Adam Belloum, Cees De Laat and Onno Valkering
  7. Towards a computer-interpretable actionable formal model to encode data governance rules by Rui Zhao and Malcolm Atkinson
  8. DARE: A Reflective Platform Designed to Enable Agile Data-Driven Research on the Cloud by Iraklis Klampanos, Athanasios Davvetas, Andre Gemuend, Malcolm Atkinson, Antonis Koukourikos, Rosa Filgueira, Amrey Krause, Alessandro Spinuso, Angelos Charalambidis, Federica Magnoni, Emanuele Casarotti, Christian Page, Mike Lindner, Andreas Ikonomopoulos and Vangelis Karkaletsis
  9. Ease access to climate simulations for researchers: IS-ENES climate4impact by Christian Page, Wim Som De Cerff, Maarten Plieger, Alessandro Spinuso and Xavier Pivan

☛ Download the BC2DC programme here!

At a glance

What: Half-day workshop
When: September 24, 2019
Where: San Diego, California, USA

Description

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:

Workshop organizers

Iraklis A. Klampanos, National Centre for Scientific Research "Demokritos", Greece
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Rosa Filgueira, The University of Edinburgh, UK
Malcolm Atkinson, The University of Edinburgh, UK
Rafael Ferreira da Silva, University of Southern California, CA, USA

Important dates

July 15 2019: BC2DC'19 Submissions due (Extended!)
July 24 2019: BC2DC'19 Notification of acceptance
July 24 2019: Preliminary BC2DC'19 Programme w/ keynote speakers
August 9 2019: Camera-ready papers due for accepted papers (Extended!)

Submission information

The submissions page is now closed.

We welcome:

The proceedings of the workshop will be included in the eScience 2019 proceedings to be published by the IEEE Computer Society Press, USA and made available online through the IEEE Digital Library.

All contributions are required to use the IEEE 8.5 × 11 manuscript guidelines: double-column text using single-spaced 10-point font on 8.5 × 11 inch pages. Templates are available from IEEE.

Depending on the number and quality of contributions, we may pursue the publication of a special issue of an international journal. More information will be provided here nearer the submission deadline.

Program Committee

David Abramson, The University of Queensland, Australia
Leonardo Candela, ISTI - CNR, Italy
Emanuele Casarotti, INGV, Italy
Oscar Corcho, Universidad Politécnica de Madrid, Spain
Cees de Laat, University of Amsterdam, The Netherlands
Shaun de Witt, Culham Centre for Fusion Energy, UK
Katerina Doka, National Technical University of Athens, Greece
Daniel Garijo, University of Southern California, USA
Andre Gemuend, Fraunhofer, Germany
Sandra Gesing, University of Notre Dame, USA
Alex Hardisty, University of Cardiff, UK
James Hetherington, The Alan Turing Institute, UK
Andreas Ikonomopoulos, NCSR "Demokritos", Greece
Keith Jeffery, Keith G Jeffery Consultants, UK
Shantenu Jha, Rutgers University, USA
Peter Kacsuk, MTA-SZTAKI, Hungary
Tamas Kiss, University of Westminster, UK
Antonis Koukourikos, NCSR "Demokritos", Greece
Chee Sun Liew, University of Malaya, Malaysia
Paolo Missier, Newcastle University, UK
Christian Page, CERFACS, France
Loic Pottier, University of Southern California, USA
Richard Sinnott, The University of Melbourne, Australia
Alessandro Spinuso, KNMI, The Netherlands
Vlado Stankovski, University of Ljubljana, Slovenia
Ian Taylor, Cardiff University, UK and The Center of Computation and Technology, LSU, USA
Luca Trani, KNMI, The Netherlands
Rongbing Wang, Liaoning University, China
Paul Watson, Newcastle University, UK
San Diego, Nserrano [CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0)]