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Published on: November 24, 2021
Reconfiguring practice: the interdependence of experimental procedure and computing infrastructure in distributed
Grace De La Flor1, Mobin Ojaghi, Ignacio Lamata Martínez
1Computing Laboratory, University of Oxford, Oxford OX1 3QD, UK. grace.de.la.flor@comlab.ox.ac.uk
Summary
Distributed earthquake engineering simulations require adapting local lab practices to new computing infrastructure. Researchers modified experimental procedures to coordinate shared experiments across geographically dispersed sites.
Area of Science:
- Earthquake Engineering
- Distributed Systems
- Laboratory Automation
Background:
- Transitioning local laboratory practices to distributed environments highlights the interplay between experimental procedures and technology.
- New computing infrastructure is being embedded in laboratories to facilitate shared experiments across geographically distributed sites.
Purpose of the Study:
- To analyze how the relationship between experimental procedure and technology reconfigures laboratory practices in earthquake engineering.
- To examine the adaptation of local practices for coordinating distributed earthquake experiments.
Main Methods:
- Analysis of laboratory practices during the integration of new computing infrastructure.
- Case study of the UK Network for Earthquake Engineering Simulation (UK-NEES) e-Research project.
- Examination of modifications in experimental procedures to support distributed experimentation.
Main Results:
- The integration of computing infrastructure made the interdependence of experimental procedure and technology explicit.
- Researchers successfully adapted local laboratory practices by modifying experimental procedures.
- Coordination of geographically distributed earthquake engineering experiments was facilitated.
Conclusions:
- Adapting experimental procedures is key to successfully implementing distributed laboratory practices.
- The reconfiguration of practices enables efficient coordination of complex, multi-site experiments.
- This work provides insights into the challenges and solutions for distributed experimental science.
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