Experiment Management with Metadata-based Integration for Collaborative Scientific Research

  • Authors:
  • Fusheng Wang;Peiya Liu;John Pearson;Fred Azar;Gerald Madlmayr

  • Affiliations:
  • Siemens Corporate Research;Siemens Corporate Research;Siemens Corporate Research;Siemens Corporate Research;Johannes Kepler University Linz

  • Venue:
  • ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
  • Year:
  • 2006

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Abstract

Scientific research in many fields is increasingly a collaborative effort across multiple institutions and disciplines. Scientific researchers need not only an effective system to manage their data, results, and the experiments that generate the results, but also a platform to integrate, share and search these across multiple institutions. Therefore, researchers are able to reuse experiments, pool expertise and validate approaches. In this paper, we present Sci- Port, a system of experiment management and integration for collaborative scientific research. SciPort's architecture uses i) a general transformation-based data model to represent and link experiment processes; ii) hierarchical data classification across multiple institutions according to research programs' goals and organization; iii) metadatacentric representation that concisely captures the context of experiments; and iv) virtual data integration through centralized metadata integration. The system is built for open source, and the metadata-based representation and integration provides a unified framework and tool set to manage and share experiments for scientific research communities.