Data Integration & Interoperability

Interoperability refers to the ability of systems to communicate with a shared understanding. Smart systems require the integration of data from multiple sources, yet these sources have evolved independently from each other resulting in data silos. Data integration refers to the task of combining this data so that it is interpreted consistently and correctly. This is required in order to use and analyze data from disparate sources.

It is important to distinguish between two types of integration and interoperability: syntactic and semantic. Syntactic integration refers to the task of harmonizing or otherwise aligning the format of data encoding between two or more sources. Similarly, syntactic interoperability is achieved when two or more systems agree on some formalism(s) or communication protocol(s) and thus are capable of exchanging information. For example, JSON, XML, and RDF are syntaxes for syntactic interoperability. In contrast, semantic integration requires an agreement on the meaning of the data in multiple sources and semantic interoperability is the ability of multiple systems to exchange information in a consistent and meaningful way. For example, knowing the difference “plant” being interpreted as an industrial site as opposed to a living organism.