Lung cancer remains one of the leading causes of cancer-related mortality worldwide and represents a major public health concern. Although extensive research has identified numerous risk factors associated with this disease, further investigation is still required, particularly with respect to its underlying biological mechanisms. In prior work, a biological ontology was introduced to organize and harmonize heterogeneous biological data related to lung cancer and its subtypes. Nevertheless, lung cancer is inherently multifactorial, as biological processes interact with environmental and contextual factors that are commonly represented across disparate and unconnected data sources. To address this limitation, the present work extends the existing ontology to include both biological and environmental factors within a unified platform, which is embedded in a visual analytics tool. This approach enables the visualization and exploration of lung cancer–related risk factors and associated information across multiple heterogeneous data sources. By supporting cross-domain queries that integrate biological, environmental, and additional previously unconnected data, the proposed solution provides more functional and comprehensive access to knowledge relevant to lung cancer research.