UFCFLJ 15 M

UFCFLJ-15-M Linked Open Data and the Internet of Things

Overview

Best practice in publishing, structuring and managing linked open data. Configuring and using data from IOT sensors.

Objectives

1. Implement and evaluate Ontology Web Language (OWL) based ontologies using industry standard tools and create Resource Description Framework (RDF) models conforming to these
2. Contrast and critique the uses of linked, open data in industry and be fully conversant with best practices in enabling Linked Open Data
3. Create semantic models in an appropriate language and using appropriate tools
4. Create optimised semantic web queries to extract data from the semantic web and subsequently visualise results in novel situations
5. Synthesise evidence on technical challenges, developments and enabling technologies surrounding the development of the Internet of Things (IoT)

Curriculum

Introduction: The open data movement, the role of linked data, origins.

Ontology: Ontology as a shared model of objects, their properties and relationships in a domain, OWL (Web Ontology Language), description logic, meta-models, re-use, relationship to vocabulary, taxonomy.

Semantic models: Metadata, URIs and URLs as the foundation of the semantic web, RDF (Resource Description Framework), creating a dataset based on the domain ontology, RDF serializations including Turtle, named graphs.

Querying Semantic Data: The SPARQL query language (SPARQL Protocol and RDF Query Language, pronounced "sparkle"), SPARQL endpoints.

Publishing Linked Data: Publishing models on the web, Open Linked Data, Enterprise Linked Data.

Consuming and Visualizing linked data: Web-based Javascript clients, JSON-LD, D3 visualization.

Internet of Things: Consuming and visualizing IoT sensor node data.

Open or Closed? Understanding the challenges of open versus closed data on the Internet of Things.

Assessment

Project (50%)

Examination (50%)