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Computational Management Of Data is a Python-based toolkit that helps with modeling, storing, querying, and processing data from .csv and .json sources. It integrates relational and graph database paradigms via tools like SQLite, rdflib, Blazegraph, and SPARQL.
Features
Load and manage tabular data (CSV / JSON) in Python (via pandas)
Model data using relational and graph-based approaches
Store data using SQLite (for relational) or RDF stores (for graph)
Execute complex queries via SQL and SPARQL
Bridge between relational and graph representations
Test suites and example workflows included
Repository Structure
Data/ — contains .csv / .json files used for demonstrations or as raw inputs
Main/ — scripts or modules that orchestrate data loading, modeling, execution
Models/ — implementation of different data models and mappings (relational, RDF, etc.)
Tests/ — automated test suite to ensure correctness and regression checks
About
Facilitates the modeling, storage, querying, and processing of data from .csv and .json files. Utilizes Python, Pandas, SPARQL, SQLite, and relational and graph databases with rdflib and Blazegraph.