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Linked Data 2014

Overview

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 schema.org, 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.