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Organization of Virtual Experiments in Data-Intensive Domains: Hypotheses and Workflow Specification
| Author(s): | D. Kovalev, L. Kalinichenko, S. Stupnikov |
| Created: | 2017/12/05 |
| Published: | Data Analytics and Management in Data Intensive Domains. Selected Papers of the XIX International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2017). CEUR Workshop Proceedings, ISSN 1613-0073, Vol. 2022. P. 293-300. |
| Abstract: | |
| Organization and management of virtual experiments in data-intensive research has been
widely studied in the several past years. Authors survey existing approaches to deal with virtual experiments
and hypotheses, and analyze virtual experiment management in a real astronomy use-case. Requirements for
a system to organize virtual experiments in data intensive domain have been gathered and overall structure
and functionality for system running virtual experiments are presented. The relationships between hypotheses
and models in virtual experiment are discussed. Authors also illustrate how to conceptually model virtual
experiments and respective hypotheses and models in provided astronomy use-case. Potential benefits and
drawbacks of such approach are discussed, including maintenance of experiment consistency and shrinkage
of experiment space. Overall, infrastructure for managing virtual experiments is presented. |
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