Linked data 2018



Linked Data and other Semantic Web technologies are used in a variety of organisations for projects large and small. They are a key feature in both government open data initiatives and enterprise-wide data integration systems for internal use. In this course, you'll learn about the building blocks of the Semantic Web and how to use them, including how to model your data in RDF, integrate with third-party and OpenData sources, and how to enter and run SPARQL queries. You'll hear about how these technologies are used today, and have a chance to try them out in the hands-on portions of the classes.

This course is chaired by Kal Ahmed and taught by Andy Seaborne, Jen Williams, Kal Ahmed, and Stuart Williams.

Classes for 2018

The Linked Data course runs on and .

An Introduction to Linked Data

Taught by Jen Williams.

Linked Data is a set of best practises that defines how to structure data so that it can be interlinked and published on the Web. By using the Web as the publishing platform, data can distributed across innumerate points, while still allowing navigation and discovery through the use of URIs in the data itself. Data models are embedded into the structure of the Linked Data itself, and follow the same best practises by being defined as Linked Data Vocabularies.

The principles of Linked Data allows developers to publish data without the need to develop custom APIs, and offers the ability for data publishers to adopt data standards to improve interoperability between disparate sources of data.

This "Introduction to Linked Data" course will cover all of the basics around the structure of the data itself, the use of URIs, popular vocabularies and how to use them in sample datasets.

Delivering Linked Data

Taught by Kal Ahmed.

The infrastructure of the world wide web can do more than deliver documents for people to read off of their screens: it can also deliver data for applications to use. The principles of Linked Data have laid a foundation that has made it possible for governments, media, and e-commerce retailers to publish data on the web without depending on custom-built APIs. This class will show you how to take advantage of these principles to consume available data and to publish it yourself.

Among other things, we'll learn about popular sets of linked data that you can use, how to create links between datasets, how to mint good URIs, HTTP issues, and how to take gradual steps toward good linked data publishing.

Introduction to SPARQL

Taught by Andy Seaborne.

SPARQL is the standard W3C query language for semantic web applications. It brings together the features of a number of RDF query languages into one method for extracting information from data represented in RDF, whether small datasets or large.

This session will provide a solid grounding in SPARQL. After demonstrating how powerful some very simple SPARQL queries can be, we will take a practical approach to looking at the key features of SPARQL 1.0 and 1.1, and then explore the principles underpinning the SPARQL query language.

Hands-on SPARQL

Taught by Andy Seaborne, Jen Williams, and Kal Ahmed.

In this session students will get a chance to try their hand at writing some SPARQL queries. This session will help to consolidate the fundamentals of SPARQL query as well as introducing some new tips and tricks for being more effective with the SPARQL that you write.

For this session students will need a laptop with a wi-fi connection and a browser capable of running modern Javascript applications (e.g. Chrome or a recent version of Firefox).

From CSV to RDF

Taught by Kal Ahmed.

CSV (comma-separated values) files are one of the simplest ways we have of sharing data. From databases and spreadsheets to content management systems and CRMs, many applications are capable of producing CSV data.

This session will focus on how we can create and publish Linked Data from this popular data format. Using the free publishing service we will show how easy it is to map simple CSV data to an ontology and publish it. We will then go on to show how to make use of common tools and open-source products such as OpenRefine to get more creative with formatting and structuring data for publication.

RDF Modelling

Taught by Stuart Williams.

Modelling the world in RDF involves identifying the important entity types within some domain of interest, their properties and relationships. In this session we will workshop the development of an RDF data model for a familiar domain.

We’ll look at the open world nature of RDF models and their focus on making statements about things in the world. We’ll build up a data model as we go along, questioning its purpose and considering the questions (possibly in the form of SPARQL queries) we’d like to be able to answer from data expressed using the model. We’ll take a quick look at expressing our evolving model in RDFS and OWL. Finally we’ll contrast the model we develop in the session with one that’s already been developed for the same domain.