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RetechFor-LD

WEB PLATFORM FOR TRANSFORMING HETEROGENEOUS DATA INTO STANDARDIZED INFORMATION


Miranda de Ebro Technology Center

Department of the Environment (Regional Government of Castile and León)

Web platform for transforming heterogeneous data into standardized information

What is it and what is it used for?

A web platform for transforming heterogeneous data into standardized, interoperable, and ready-to-use information. It allows users to create reusable templates that validate, transform, and map data (JSON, CSV, XML, or YAML) against ontologies, automatically generating JSON-LD (Linked Data) models compatible with semantic standards. The platform includes a visual editor, real-time validation, version control, token-based authentication, a REST API, and a monitoring dashboard for tracking executions, ensuring traceability, and detecting errors.

TECHNICAL SPECIFICATIONS
Leading organization
Miranda de Ebro Technology Center
Administration
Department of the Environment, Housing, and Land Use Planning (Regional Government of Castile and León)
Coordinator
David Ayala (Head of the Software Engineering Department at CTME)
Technologies
Modeling. Others.
Target audience
Companies
Project framework
RetechFOR · Next Generation EU
CTME RetechFOR LD

The problem it solves


The forestry sector manages information from inventories, sensors, government agencies, and companies in diverse formats and without a common model, which makes it difficult to integrate, share, and reuse this data. The solution automatically converts this data into a standardized and interoperable format, facilitating its use, collaboration among organizations, and decision-making.

"Acommon language for forest data: transforming scattered information into interoperable knowledge."

What makes it innovative?

A visual platform that democratizes the use of the Semantic Web


It democratizes the use of the Semantic Web in the forestry sector through a visual platform that allows users to transform data from multiple formats into interoperable ontology-based models without the need for programming. It combines validation, transformation, semantic enrichment, and publication via a REST API, accelerating the integration and reuse of information.

Expected impact

It reduces data integration and maintenance costs by eliminating system-specific development. It improves the quality, interoperability, and reusability of information, fostering collaboration among government agencies, businesses, and research centers, and accelerating the digitization of the forestry sector.