Learn about the development towards our vision for universal data interoperability.
In this paper we show how to compute left-Kan extensions of set-valued functors with the venerable chase algorithm from relational data base theory.
We take a popular position that AI systems are limited more by the integrity of the data they are learning from than by the sophistication of their algorithms.
Using a simplified financial reporting example, we examine how traditional data warehouses are put together. We then propose an improved method for creating data warehouses: using the categorical query language CQL.
We consider the issue of multiple overlapping data models in the context of modern power grids.
In this paper we consider how to integrate a simple and developer-friendly data model such as the property graph with more complex and less user-friendly data models such as relational database tables.
CQL is an open-source query and data integration scripting language that can be applied to common challenges in the field of computational science.
We describe a new model management approach based on algebraic specification following a survey of the field of model management.
Our approach to data integration is based on combining techniques from functional programming, category theory and database theory.
We approach the integration of manufacturing service capability databases using a different set of tools, specifically category theory (CT) and FQL, a functorial query language based on categorical mathematics.
We generalize the set-valued functor model by using multi-sorted algebraic theories.