Breaking the Language Barrier in Data Discovery: IntuView’s CLM

As data ecosystems grow, one of the central challenges is no longer simply storing information but ensuring that users can find the data that is relevant to their needs. This becomes considerably more difficult when data providers and users describe the same subjects differently or operate in different languages.

IntuView Ltd.’s Culture and Language Module (CLM) addresses this problem by creating a common semantic language for data discovery. Technology processes text and its accompanying tags in multiple languages and converts their meaning into a language-independent ontological graph. In effect, the ontology becomes a semantic “lingua franca” through which descriptions, data and user requirements can be compared regardless of the terminology or language in which they were originally expressed.

For data providers, CLM analyses the description of a data space and creates an ontological digest representing its principal concepts, entities and relationships. This model can subsequently be enriched with examples of actual data, making the representation increasingly precise. CLM can also provide feedback on the description itself, identifying ways in which it could be improved so that users searching for relevant information are more likely to discover it.

The same process works from the opposite direction. When a user submits a request for information, CLM converts the request into the same language-independent semantic framework. It can then compare what the user is looking for with its representation of the available data spaces. The result is a move from conventional keyword matching toward meaning-based discovery.

This capability is being integrated into several areas of DS2. In the catalogue, CLM can help direct participants toward relevant product sets and data spaces. Applied to the DS2 Chatbot, it can improve the interpretation of questions, make responses more targeted, and identify resources that users might otherwise overlook.

Perhaps more importantly, discovery does not have to end with the user's original search. As new data spaces and data sets enter the environment, CLM can compare them with previously identified interests and requirements and suggest newly available information that may be relevant.

The result is a semantic bridge between data providers and data consumers. Instead of requiring users to know exactly how information has been described, where it resides, or even the language in which it was originally expressed, IntuView’s CLM enables data to be discovered according to what it means.