Repositories for scientific and scholarly data are valuable resources to share, search, and reuse data by the community. Such repositories are essential in data-driven research based on experimental data. In this paper we focus on the case of combustion kinetic modeling, where the goal is to design models typically validated by means of comparisons with a large number of experiments. In this paper, we discuss new requirements emerging from the analysis of an existing data collection prototype and its associated services. New requirements, elaborated in the paper, include the acquisition of new experiments, the automatic discovery of new sources, semantic exploration of information and multi-source integration, the selection of data for model validation. These new requirements set the need for a new representation of scientific data and associated metadata. This paper describes the scenario, the requirements and outlines an initial architecture to support them.

Storing Combustion Data Experiments: New Requirements Emerging from a First Prototype: Position Paper

Scalia, Gabriele;Pelucchi, Matteo;Stagni, Alessandro;Faravelli, Tiziano;Pernici, Barbara
2018-01-01

Abstract

Repositories for scientific and scholarly data are valuable resources to share, search, and reuse data by the community. Such repositories are essential in data-driven research based on experimental data. In this paper we focus on the case of combustion kinetic modeling, where the goal is to design models typically validated by means of comparisons with a large number of experiments. In this paper, we discuss new requirements emerging from the analysis of an existing data collection prototype and its associated services. New requirements, elaborated in the paper, include the acquisition of new experiments, the automatic discovery of new sources, semantic exploration of information and multi-source integration, the selection of data for model validation. These new requirements set the need for a new representation of scientific data and associated metadata. This paper describes the scenario, the requirements and outlines an initial architecture to support them.
Semantics, Analytics, Visualization. SAVE-SD 2017, SAVE-SD 2018
9783030013783
Combustion modeling; Experimental data; Explorative approaches; Theoretical Computer Science; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1071500
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