The past decade has witnessed an unprecedented surge in the volume and variety of biomedical data, propelling us into an era of big data. While this surge in data holds immense potential for expanding our knowledge, it has also ushered in significant challenges pertaining to the management and analysis of this continously burgeoning data stream. As immunological and other biomedical research becomes incresaingly data driven, the bottleneck in productivity is shifiting from data generation to its management, integration and analysis. The collection, aggregation, and integration of biomedical reserach data has been found to occupy as much as 70% of the time used for analytic purposes. In this project we propose to develop Inetegrated Knowledge Spaces for Infectious and Immune-mediated Disease Research, a platform that leverages biomedical ontologies to provide rich semantic models of existing immunology data sets, making it easier to represent data relevant for infectious and immune-mediated diseases into knowledge graphs, enabling users to integrate and aggregate data from multiple sources, and to deploy this data into scientific workflows. Phase 1 focuses on developing and validating key technologies and is organized under four general objectives: User-Centered Design, Knowledge Modeling, Semantic Enrichment, and Knowledge Graph Materialization.