Submission 51_SWAT4HCLS18_DEMO_Final_MSAl_Manir.pdf (212.67 kB)
journal contributionposted on 2018-12-01, 20:59 authored by Jon Haël Brenas, Mohammad Sadnan Al Manir, Kate Zinszer, Christopher J. O. Baker, Arash Shaban-Nejad
The Semantics, Interoperability, and Evolution for Malaria Analytics (SIEMA) platform a provides solution to integration and interoperability challenges associated with distributed malaria data. SIEMA leverages (i) community developed ontologies for facilitating standardization, (ii) SADI Semantic Web services for discovering and accessing distributed data, (iii) an analytics dashboard for detecting mission-critical changes interrupting the system interoperability, (iv) Valet SADI tool for building SADI services and re-actively rebuilding services to accommodate the changes in terminologies, and (v) the HYDRA query engine that provides the functionality to create SPARQL queries graphically and perform the automatic discovery, invocation, orchestration, and execution of services. Whereas the open-source surveillance software District Health Information Software 2 (DHIS2) provides improved malaria surveillance in many countries, SIEMA goes beyond the capabilities of such systems by addressing the needs for semantics, greater interoperability and evolution or change management needs of dynamic surveillance systems.