Transform XML Data into Harmonised RDF using Precise Mapping 

Semantic Engineers implementing semantic interoperability solutions use Mapping Workbench to accurately map source  data XML schemas to target ontologies

Mapping complex XML data

Large organisations require seamless interoperability across varied data sources and systems. To achieve this, they need to efficiently and accurately map data from evolving source schemas with target ontologies.

This process requires a profound understanding, not only of the mapping technology but also of the domain knowledge, the source XSD schemas and the target ontologies.

The mappings need to be readable by business stakeholders and processable by the automated transformation systems. 

To fully trust the integrity of the data, stringent quality controls of the mapping coverage, validity, accuracy are essential.

Many semantic engineers struggle with evolving XML schemas, nuanced or context-dependent interpretations, making it difficult to manage the mapping process systematically

Mapping Rules and Data Management Errors

Incorrect mapping rules, terms, and incomplete mappings lead to significant data integrity and usability issues.

Multiple XML Schema Versions

Managing mappings across evolving schemas and ontologies proves complex discrepancies between business validation and technical execution.

Mapping Maintenance 


Difficult to empirically evaluate and maintain mappings over time, leading to a slow and reactive mapping process.

Integration Gap Between Semantic and Technical Layers

Disconnection between semantic and technical layers requires systematic mapping and validation to ensure accuracy and completeness.

Mapping Workbench addresses these issues by enabling straightforward, accurate mappings from XML to RDF, facilitating a smooth transition to semantic web technologies:

Precision Mapping Tools

Implement advanced tools that ensure correct mapping rules and terms, enhancing data integrity and usability.

Harmonised Schema Management System

Use holistic schema management to align evolving source schemas with ontologies, ensuring consistent transformation.

Automated Mapping Evaluation

Deploy automation in mapping evaluation and maintenance to accelerate processes and reduce response times.

Unified Conceptual and Technical Mapping Rules

Integrate a framework that bridges the conceptual and technical mapping rules, streamlining validation and enhancing accuracy.

Benefits of using Mapping Workbench:

Guarantees quality by measuring mapping validity, accuracy, and coverage

Significantly speeds up data mapping and reduce maintenance cost

Identifies conceptual mapping issues early by involving domain experts

Handle the mapping complexity of large schemas, contextual mappings, and evolving schema versions

Collaborative mapping environment for semantic engineers and domain experts

Prepares data for advanced ML and AI applications, unlocking new use cases


What is Mapping Workbench?

Mapping Workbench is a collaborative platform to design, implement and validate mapping rules. It aims to maximise the mapping developer productivity and ensuring high-quality mappings by organising all the relevant resources in one environment and facilitating executing the relevant tasks and activities at every step of the development lifecycle from inception to deployment.

Who can use Mapping Workbench?

It is ideal for semantic engineers and IT professionals who are tasked with implementing semantic interoperability or knowledge graph creation within large organisations, such as EU institutions, that require seamless integration of diverse data silos.

How does Mapping Workbench handle evolving XML schemas?

The Mapping Workbench implements a two-layer approach to manage mapping rules: the conceptual and the technical (with RML). Once the conceptual mapping is established, one or multiple XPath variations can be associated with the same source field. Then the multiple RML implementations can realise the same conceptual mapping. 

What makes Mapping Workbench different from other data mapping tools?

Mapping Workbench is a collaborative environment that focuses on following a robust methodology and mapping management approach. It is especially effective for handling complex mapping projects. Moreover, it offers robust quality control mechanisms and ensures mappings are both technically sound and business-relevant.

How does Mapping Workbench ensure the accuracy of data mappings?

The tool is based on a test-driven approach. It includes advanced validation features based on SPARQL queries and XPath coverage measurement that cross-verify the technical implementation of mappings with business-level understanding and requirements. This dual-validation approach ensures high accuracy and relevance.

In addition, the SHACL validation capability ensures that the mappings rules produce output compliant with semantic data standards. 

Is training required to use Mapping Workbench effectively?

While Mapping Workbench is user-friendly, initial training is recommended to help users maximize its capabilities. Training sessions typically cover the basic concepts, the mapping methodology, how to set up and manage mapping projects, and how to use the tool’s advanced features effectively.

What support options are available for Mapping Workbench users?

Users of Mapping Workbench can access a range of support options including an online knowledge base, direct customer support via email or phone, and a community forum where users can share insights and solutions.

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Start using Mapping Workbench to harmonise your data today 

Connect with us


Begin your journey to better data integration by connecting with our team to discuss your specific needs and how Mapping Workbench can address them.

Each integration scenario is unique, and we tailor Mapping Workbench to seamlessly fit into your existing data management framework.

Step 1

Setup and Configuration

Set up the Mapping Workbench and configure it to interact with your existing data systems. This includes setting up connections to your source schemas and target ontologies.

Step 2

Mapping Creation and Validation

Use the Mapping Workbench to develop and validate mappings between your source schemas and target ontologies. The tool provides a visual interface and guided processes to help you map fields accurately.

Step 3

Deploy in Transformation Pipelines

Once validated, implement the mappings in a data transformation environment. The Mapping Workbench supports the deployment process to ensure mappings are correctly applied to ongoing data operations.

Step 4

Ongoing Support and Updates

Benefit from ongoing support and regular updates from our team to ensure that your Mapping Workbench continues to meet your evolving data integration needs.

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