The Interoperability Toolkit provides standard means or foundation principles by which data may be described, categorized, and shared, considering its data description, data context, data linking, reusability and sharing. The aim of the Interoperability Toolkit is to provide a collection of tools and resources that support the execution of data discovery and manipulation over different semantically described information.

These tools can be classified into the following classes:

Mapping of Semantic Concepts: This class refers to the tools used to identify relations between semantic concepts defined in different Data Models. This mapping allows to establish relations between different Data Models, describing how datasets conforming to different Data Modes can be related and converted.

Data Indexing and Collection: Refers to the tools that support the discovery and indexing of data sets that satisfy any query specification, regardless of the Data Model used to describe the datasets. It also refers to the tools used to interact with data sources for the purpose of collecting the relevant information.

The following figure represents how the Semantic Interoperability Toolkit interacts with other components of AI4PublicPolicy. The Semantic Interoperability Toolkit integrates into the Catalogue of Datasets and Policies to provide capabilities to handle information described using disparate semantic definitions. With these capabilities, Policy Makers can use the Catalogue to discover and inspect Datasets and Policies regardless of the semantic descriptions associated with each dataset or policy. After the Policy Maker identifies the Policies and/or Datasets of interest, the export process takes place, sending them to the Data Management component under a semantic description and format optimized for the AI Models utilized on the VPME.