Research on Software Development Data Modeling Based on Meta Model

Software R&D process documentation encompasses heterogeneous data types, including structured and unstructured formats. Traditional file system based storage models for R&D data exhibit critical limitations: coarse grained version control, fragmented process data continuity, and redundant data entries. To address these challenges, this paper conducts a systematic analysis of software R&D data characteristics and proposes a meta model based architecture for R&D data modeling and a configurable MongoDB based storage mechanism. The meta model enables unified semantic representation of diverse document types, while the schema flexible NoSQL implementation supports dynamic data relationships and version aware persistence. This integrated approach achieves granular process control through coherent data traceability, eliminating redundant data operations while ensuring full lifecycle management of R&D artifacts.