Annotations of Virus Data for Knowledge Enrichment

Data analytics in healthcare informatics has grown rapidly due to the greater influx of multimodal data. Studying virus related diseases uses analysis and comparison of hetero-geneous data, often related to geographical patient position and hospital services. In this context, cooperation among different data sources as geographical dislocated hospitals, is relevant to prevent diseases diffusion. At the same time, annotation and enriching data may be used to support cooperation, knowledge enrichment and to boost artificial intelligence based systems. We present a data integration and annotation model to integrate virus data sources through a web-based application. We present a prototype able to collect clinical data, diagnoses and therapies from geographic distributed patients, able to include and classify annotations able to guide and classify viruses related information. We focus on a subset and snashot of an HIV (Human Immunodeficiency Virus) infection database proving the efficacy of the system.