Overcoming the Barriers of Using Linked Open Data in Smart City Applications

TL;DR

The paper addresses barriers to using Linked Open Data in smart city applications by analyzing provider and consumer challenges across publication, standardization, discovery, and data quality. It proposes an integrated, open-source toolchain leveraging NGSI-LD, Smart Data Models, DCAT-AP, CKAN, and FIWARE GEs (including Orion-LD, Draco, IoT Agents, and Cosmos) to harmonize, publish, and consume data. The approach is validated with a Santander, Spain smart mobility use case, demonstrating end-to-end data flow from multiple providers to aggregated portals and ML-based predictions, with scalability to city-wide data. The study concludes that the proposed stack enables interoperable, scalable LOD-enabled smart city applications and offers a reference architecture for cross-domain adoption, complemented by a quality-assessment and metadata management workflow.

Abstract

We study the benefits and challenges of using Linked Open Data in smart city applications and propose a set of open source, highly scalable tools within the case of a public-rental bicycle system, which can act as a reference guide for other smart city applications.

Figures (2)

• Figure 1: Usage of open data in smart city applications
• Figure 2: Provider and consumer bicycles rental service architecture