An ETL Extension to DHIS2

Our team has already developed a geospatial data management decision support platform (DDMS, Geoprism) that has been used in vector-borne disease elimination, water, hygiene, and local farm business support across multiple countries in Africa and Asia. One of the applications is an entomology module that is being extended to all African Indoor Residual Spraying project (AIRS) countries for malaria elimination efforts. Commercially, the platform has been used in oil and gas and media analytics. The platform has an extract, transform, and load (ETL) engine that utilizes ontologies and machine learning to reconcile disparate datasets. Our proposal is to port this proven functionality into a plugin for DHIS2 to make it as easy as possible to import and harmonize existing disparate and dirty data without the need to engage software professionals. Under-resourced disease elimination programs will have the ability to utilize data already available that they otherwise could not integrate for decision support.