基于元数据集成的协同科研实验管理

Fusheng Wang, Peiya Liu, John Pearson, F. Azar, G. Madlmayr
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引用次数: 13

摘要

许多领域的科学研究越来越需要多个机构和学科的合作。科研人员不仅需要一个有效的系统来管理他们的数据、结果和产生结果的实验,还需要一个平台来跨多个机构整合、共享和搜索这些数据。因此,研究人员能够重用实验,汇集专业知识和验证方法。本文提出了一个协作科研实验管理与集成系统Sci- Port。SciPort的架构使用i)一个通用的基于转换的数据模型来表示和链接实验过程;Ii)根据研究项目目标和组织在多个机构之间进行分层数据分类;Iii)元数据中心表示,简洁地捕捉实验背景;iv)通过集中元数据集成实现虚拟数据集成。系统面向开源,基于元数据的表示和集成为科研团体提供了统一的实验管理和共享框架和工具集。
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Experiment Management with Metadata-based Integration for Collaborative Scientific Research
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.
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