Modelareltable

Modelareltable is a theoretical framework and software concept that enables the declarative construction of tabular models used in simulation, data analysis, and decision support. It emphasizes modularity, reusability, and interoperability, allowing users to define tables that encode variables, constraints, and relationships in a structured form. The approach supports both static specifications and dynamic updates as data changes.

The name combines "modelare," a term related to modeling in some languages, with "table," signaling its focus on tabular representations of model components. The concept emerged in academic and open-source communities focused on modeling workflows in the early 2020s and has been applied to disciplines ranging from systems engineering to social science.

Core features include a declarative schema for columns and rows, support for derived columns through expressions, constraint validation, versioning, and import/export in common formats such as CSV and JSON. It often integrates with statistical and simulation engines, enabling execution from table specifications or translation into executable models.

Typical use cases involve designing experiment plans, parameter sweeps, and scenario analysis where the relationship among variables is best captured in tabular form. It is used in teaching to illustrate data-driven modeling and in research to prototype complex modeling workflows quickly.

See also related concepts such as tabular modeling, declarative modeling, and model-driven engineering.