PT  - JOURNAL ARTICLE
AU  - Giovanni Delussu
AU  - Luca Lianas
AU  - Francesca Frexia
AU  - Gianluigi Zanetti
TI  - A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data
AID  - 10.1101/067371
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 067371
4099  - http://biorxiv.org/content/early/2016/08/04/067371.short
4100  - http://biorxiv.org/content/early/2016/08/04/067371.full
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.