Dec 10, 2016

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data

PloS One
Giovanni DelussuGianluigi Zanetti

Abstract

This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR's formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called "Constant Load" and "Constant Number of Records", with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes.

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Mentioned in this Paper

Description
Structure
Disease Management
Information Extraction
Circulating Neoplastic Cells
Biomedicine
High Mobility Group Proteins
Anatomic Node
Computational Molecular Biology

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