PACIS 2019 Proceedings


Cancer is a deadly complex disease. Poorly aligned institutions, their data sources, and doctor-patient disengagement motivate us, strengthening collaborative cancer research. The research explores informatics solutions, by collating various cancer-linked data attributes and interconnecting them with spatial-temporal dimensions. The study is aimed at developing a methodological framework and investigating the open source empirical cancer data that involve diverse human ecosystems. We propose a Multidimensional Cancer Research Framework (MUCARF), responding to challenges of reporting, documenting and collaborating the data sources that characterize different cancer ailments including their worldwide causalities. Information system artefacts built based on cancer-domain ontologies, with similar and dissimilar attributes are integrated into MUCARF to dig the diagnostic cancer metadata views in new knowledge domains. Metadata model that replicates the design and development of MUCARF is a useful analytic therapy to examine and mitigate high rates of cancers and their types as preventive care and cancer disease management.