A Graph Based Knowledge and Reasoning Representation Approach for Modeling MongoDB Data Structure and Query
MongoDB document store is the most popular of NoSQL systems. For managing and retrieving data, having a representation of its inherent knowledge structures proves to be significant for modeling purposes. In this paper, we present a modeling method for MongoDB data structure and query based on a graph based knowledge and reasoning (GBKR) model, due to Chein and Mugnier. The expressive power of the GBKR model makes it particularly suitable for conceptual modeling of semi structured data. We propose a common interface for data structure modeling and queries in MongoDB by using knowledge graphs. For a proof of concept we have developed a software tool implementing these functions.
2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)