Designing a NoSQL Database for Efficient Storage and Retrieval of Health Data

The role of Cloud to store and retrieve health data is felt more than ever before in this pandemic. In remote places, and in emergency situations, there is scarcity of medical personnel and proper medical infrastructure. Hand held devices like smart phones and other devices having sensing capabilities can be used to store health data in cloud. This health data containing audio, video, images, sensor data as well as text data can be easily stored in a cloud. A static data model does not have the capability to cope with changes in the requirements of a health care application. Ontology comes as a solution to incorporate the dynamic requirements of such an application. Also, there are multiple complicated health data standards to follow or to be interoperable with. Ontology has the capacity to bring different health data standards and relate these standards. Health data being Big data by its nature is stored in MongoDB cloud in this work. Designing a data model that stores health data so that queries can run in less time- is a challenge. An algorithm is used to generate the data model design for a set of queries. This data model design is used to store data in this work. The experience of storing and running some queries is discussed here.