Heterogeneous biological data integration with declarative query language
Heterogeneous biological data integration with declarative query language
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DOI：
10.1147/jrd.2014.2309032
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发表时间：
2014-03
期刊：
影响因子：
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通讯作者：
Hoan Nguyen;L. Michel;J. Thompson;O. Poch
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文献类型：
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作者：
Hoan Nguyen;L. Michel;J. Thompson;O. Poch
现代生物学对可扩展数据集成系统的需求是无可争议的，因为公共数据库中存在非常大的、异构的和复杂的数据集。这种“大数据”与当地数据库的管理和融合是一个重大挑战，因为它是随后将产生和实验验证的计算推理和模型的基础。在本文中，我们提出了一个替代的概念，本地数据集成，称为鸟（生物集成和检索数据），基于四个概念：（i）混合平面文件和关系数据库架构允许快速管理大量的异构数据集;（ii）通用数据模型允许根据现实世界的要求同时组织和分类本地数据库;（iii）配置规则用于将每个数据资源划分和映射到若干数据模型实体;以及（iv）简单的声明性查询语言（BIRD-QL）促进从异构数据集提取信息。这种灵活的通用设计允许将不同的数据格式整合到一个可搜索的数据库中，并根据具体的科学背景提供高级功能。它已经在真实的世界项目中得到验证，特别是SM 2 PH（人类病理学表型的结构突变）项目。
The requirements for scalable data integration systems for modern biology are indisputable, due to the very large, heterogeneous, and complex datasets available in public databases. The management and fusion of this "big data" with local databases represents a major challenge, since it underlies the computational inferences and models that will be subsequently generated and validated experimentally. In this paper, we present an alternative conception for local data integration, called BIRD (Biological Integration and Retrieval Data), based on four concepts: (i) a hybrid flat file and relational database architecture permits the rapid management of large volumes of heterogeneous datasets; (ii) a generic data model allows the simultaneous organization and classification of local databases according to real-world requirements; (iii) configuration rules are used to divide and map each data resource into several data model entities; and (iv) a simple, declarative query language (BIRD-QL) facilitates information extraction from heterogeneous datasets. This flexible, generic design allows the integration of diverse data formats in a searchable database with high-level functionalities depending on the specific scientific context. It has been validated in the context of real world projects, notably the SM2PH (Structural Mutation to the Phenotypes of Human Pathologies) project.