Information Systems Development with the Help of Petri Nets

What is it about?

NoSQL databases (DB) support the ability to handle large volumes of data in the absence of an explicit data schema. On the other hand, schema information is sometimes essential for applications during data retrieval. Consequently, there are approaches to schema construction, e.g., in the JSON DB and graph DB communi-ties. The difference between a conceptual and database schema is often vague in this case. We use functional constructs – typed attributes for a conceptual view of DB that provide a sufficiently structured approach for expressing semantics of document and graph data. Attribute names are natural language expressions. Such typed func-tional data objects can be manipulated by terms of a typed λ-calculus, providing pow-erful nonprocedural query features for considered data structures. The calculus is extendible. Logical, arithmetic operations, and aggregation functions can be included there. Really, conceptual and database modelling merge in this case. The paper fo-cuses on conceptual/database schemas for JSON and graph NoSQL data models.

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