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Toward Mapping an NGSI-LD Context Model on RDF Graph Approaches: A Comparison Study.

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Summary
This summary is machine-generated.

Next Generation Service Interfaces-Linked Data (NGSI-LD) enables interoperability for isolated IoT systems. This study proposes semantic mapping to RDF graphs, simplifying NGSI-LD data processing without complex reification.

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Area of Science:

  • Computer Science
  • Internet of Things
  • Semantic Web Technologies

Background:

  • Internet of Things (IoT) deployments often lack interoperability due to isolated solutions.
  • Standardized data models like Next Generation Service Interfaces-Linked Data (NGSI-LD) aim to bridge this gap.
  • NGSI-LD utilizes JSON for Linked Data (JSON-LD) for context information, leveraging semantics and linked open data.

Purpose of the Study:

  • To address the theoretical limitations of NGSI-LD graph APIs and query languages.
  • To propose standardized mapping mechanisms for NGSI-LD data to RDF graphs.
  • To demonstrate the feasibility of semantically exploiting RDF stores for NGSI-LD data processing.

Main Methods:

  • Developing standardized mapping mechanisms from JSON-LD payloads to RDF graphs.
  • Ensuring compliance with the NGSI-LD context model and API specifications.
  • Avoiding the use of reification for relationship annotation in JSON-LD payloads.

Main Results:

  • Proposed mapping mechanisms enable semantic exploitation of NGSI-LD data in RDF stores.
  • Demonstrated that processing NGSI-LD data semantically using RDF stores is feasible and uncomplicated.
  • Illustrated the mapping approaches with real-world use-case examples.

Conclusions:

  • Semantically processing NGSI-LD data via RDF stores is achievable and straightforward.
  • The proposed mapping mechanisms facilitate enhanced interoperability and data utilization in IoT.
  • Further exploitation of semantic approaches can unlock the full potential of NGSI-LD.