Linked Data 2014



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, how to use the schemas at, and 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 Peter Flynn and taught by Andy Seaborne, Elie Abi-Lahoud, Kal Ahmed, Kevin Page, and Philip Fennell.

Classes for 2014

The Linked Data course runs on and .

The Semantic Web: an Overview

Taught by Kal Ahmed.

The Semantic Web is a set of standards and best practices for sharing data and the semantics of that data over the web for use by applications. What are the standards? What are the best practices? What does it mean to share semantics along with data, and how can that make the data more useful? How do applications use data from across the web?

In this class, we'll look at the high-level answers to these questions, take a tour of the technology and the acronyms, and see how they all fit together before the day's remaining speakers dig deeper into the practical use of these technologies.

Introduction to 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 and SPARQL Update

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.

The next wave of SPARQL standardization is currently underway to add features that are useful for publishing data and also to add mechanisms to update and manage RDF data over the web.

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.

Following this, we will introduce the features of SPARQL for update and management of data using web protocols. SPARQL Update is a language for modifying RDF data and SPARQL HTTP Update provides for RESTful update of a collection of RDF graphs.

RDF principles and modelling

Taught by Philip Fennell.

This session will look at the practical means by which you can generate and acquire RDF datasets from relational data sources, XML, content enrichment and the Linked Open Data Cloud. We will discover best practice in RDF data modelling by utilising established design patterns and how they can be applied to real-world modelling problems. We will also look at publishing metadata in RDFa and how the worlds of XML and RDF can meet to help build more compelling data-driven applications.

Linked Data in disciplines - Experiences across the sciences and humanities

Taught by Kevin Page.

The Web was proposed as a mechanism for sharing knowledge amongst scientists at CERN. How can Linked Data and associated technologies further this aim? Is scholarship in a world of big data even possible without it? Is there a perfect balance between detailed, precise, encoding of semantics and the broad linking of data so successfully pioneered by the Web? Should we expect scientists to SPARQL? We will reflect upon all these issues and the strengths and weaknesses of semantic web technologies through examples drawn from a decade of applying linked data to academic studies in the sciences and humanities. Outlining projects ranging from Martian space exploration, through environmental sensor data, to the computational analysis of music structure, we will discuss how linked data was appropriately and successfully (and sometimes less successfully!) deployed, building up a picture of common patterns and more widely applicable lessons.

Linked Data in Governance, Risk and Compliance

Taught by Elie Abi-Lahoud.

Governance, Risk and Compliance (GRC) Information Systems provide key functionalities - ranging from risk program management to regulatory monitoring and reporting - to different stakeholders within an enterprise. Traditional approaches to Governance, Risk and Compliance (GRC) have proven to be ineffective in addressing key challenges facing the financial industry. These approaches are complex and siloed, they lack automation, and they rarely contain audit trails. GRC is moving toward “a more integrated approach to ensure effective governance, manage risks and optimize performance while addressing compliance obligations throughout the enterprise” (OCEG GRC technology solution guide v2.1).

Data integration is key in enabling enterprise wide GRC: data needs to be integrated in a model overarching the enterprise data repositories. This model should be accessible to the business and easy to maintain. This talk will discuss current and future ways of applying linked data and semantic technologies to address data challenges the financial services industry.