A Brief Analysis of Palantir Gotham: A Collaborative and Interactive Big Data Visualization Analysis Software Based on Dynamic Ontology

Palantir Gotham is a big data analysis and management software based on dynamic ontology technology, catering to the domains of military decision-making, national defense security, government administration, etc. This paper selects an frontend analytics software targeted at business analysts from Gotham, delves into its primary capabilities and core functionalities, examines and organizes the underlying core technologies, primarily consisting of big data integration and business mapping techniques based on dynamic ontologies, an integrated security-enhanced collaborative big data system technical architecture, and human-centered collaborative interactive visualization analysis techniques for big data. The paper analyzes and summarizes the primary mapping principles of structured data within the Palantir ontology, the key application principles of Palantir's dynamic ontology technology, along with its comprehension of the three-layer structure and three characteristics of the dynamic ontology. The paper outlines and summarizes the understanding diagram of Palantir's big data system technical architecture, identifying and elucidating its crucial technological components, and identifies and summarizes three typical frontend styles employed in Gotham's interactive visualization analysis. Ultimately, the paper shares three insights: human-computer collaborative analysis, the philosophy of dynamic ontology, and collaborative interactive analysis.