The concept of semantic operability, an extension of traditional interoperability, focuses on not just exchanging data through standardized interfaces but also ensuring that the meaning or significance of the data is preserved and understood consistently across different systems or platforms. In traditional interoperability, the emphasis is on the technical aspects of data exchange. This involves using standardized formats and protocols to ensure that different systems can communicate with each other. 

For example, two systems might use XML or JSON formats to exchange data. However, this approach does not guarantee that the receiving system interprets the data in the way the sending system intended. This is where semantic operability comes in.

There is a need for an additional layer of understanding to this data exchange. It ensures that the data, when transferred from one system to another, retains its intended meaning. This is particularly important in complex fields like healthcare, finance, or integrated supply chains, where the same data might be used in different contexts and must be understood accurately to make informed decisions.

To achieve semantic operability, systems often use shared vocabularies, ontologies, or data models. These tools define not just the format of the data but also its context and meaning. 

For instance, in healthcare, a term like "BP" could be standardized to always mean "blood pressure," and associated with certain measurement units and criteria. This standardization ensures that when one system sends data about a patient's BP to another, there's no confusion about what "BP" refers to and how it should be interpreted.