A new scientific paper on Ontology-Driven Data Cleaning Towards Lossless Data Compression has been published, written by PolicyCloud members namely Athanasios Kiourtis, Argyro Mavrogiorgou, George Manias, and Dimosthenis Kyriazis.
With the devices’ increase, there has been a growth of data exchange protocols. Especially in healthcare, due to the broader eHealth strategy , healthcare organizations require interoperable data and efficient exchange. Current approaches pay attention to the exchanged data security, without fully facing Health Information Exchange (HIE) requirements , due to non-efficient transfer rates and low performance data exchange protocols. Data compression algorithms provide efficient rates, which may lead to information loss, driving the implementation of lossless compression algorithms .
In this paper, it is being introduced an Ontology-driven Data Cleaning mechanism, facilitating Lossless Healthcare Data Compression, which parses and splits healthcare data into data chunks, and based on the ingested data type and format, different lossless compression algorithms are provided to function in parallel threads.