RT Journal Article
SR Electronic
T1 A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 067371
DO 10.1101/067371
A1 Giovanni Delussu
A1 Luca Lianas
A1 Francesca Frexia
A1 Gianluigi Zanetti
YR 2016
UL http://biorxiv.org/content/early/2016/08/02/067371.abstract
AB This work presents a scalable data access layer, called PyEHR, intended for building data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts openEHR formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structures indexing to speed up searches. The persistence is guarantee by a driver layer with a common driver interface. Presently, are implemented the interfaces with two NoSQL DBMS: MongoDB and Elasticsearch. The scalability of PyEHR has been evaluated experimentally through two types of tests, namely constant load and constant number of records, with queries of increasing complexity on a two synthetic datasets of ten millions records each, containing very complex openEHR archetype structures, distributed on up to ten working nodes.