Linked, Open Data
About this course
Page last updated 13 February 2017
The creation of structured, semantically rich datasets is an important step towards better reuse and recombination of data from diverse sources. In addition to best practice in the creation of linked data, this module will introduce you to the tools and methods for querying linked data and for representing rich ontologies that help define data-rich domains. The module will look particularly at consumption and processing of data produced by networked sensors making up the Internet of Things.
Participants are expected to have a first degree at 2.2 level or above (or equivalent,) or alternatively have industrial experience. We strongly recommend that you speak to the course tutor prior to the course if you are unsure about your suitability to complete the assessment.
Careers / Further study
This module can be taken as a stand alone module, or used to build up credit towards a named postgraduate qualification (PG Certificate, PG Diploma or Masters) within our Information Management and Information Technology Awards.
This module will cover the following topic areas:
- 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.
- 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.
Learning and Teaching
Scheduled learning includes lectures, tutorials, demonstration, practical classes (24 hours)
Independent learningincludes hours engaged with essential and further reading, assignment preparation and completion. (130 hours.)
Assessment will be through a coursework/practical project and a written exam.
For more details, see our full glossary of assessment terms.
The University has excellent facilities, accessible to all students, as required; however, it is expected that much of the work will be carried within the work environment.
Find out more about the facilities and resources UWE has to offer.
Supplementary fee information
Bookings for the 2016/17 run of this module are now closed. Please complete an enquiry form to receive information once the 2017/18 academic year run of this module becomes available.
UWE Bristol, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY
How to apply
For all enquiries, please complete our online enquiry form or contact us on the number below.
For further information
- Email: For all queries, please complete the on-line enquiry form above.
- Telephone: +44 (0)117 32 87265