Semantic Technologies 2013

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.

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.

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 new standard 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.

Taught by Philip Fennell.

This class will focus on the use of RDF that is embedded in XML, and especially
in HTML web pages, with the W3C’s RDFa standard. We’ll look at how to create
RDFa, how to add it to documents manually, and some strategies for automating
the process. We’ll also see how to extract RDF triples from these documents, and
we’ll tour some of the large-scale websites that are currently making RDF data
available on the public Linked Data web using RDFa. Along the way, we’ll address
these common questions about RDFa: how is it similar to Microformats and
Microdata, and how is it different? What kind of data is suitable for exposing
to other applications as RDFa? Is it only good for public web pages, or can it
be useful behind a firewall? Can RDFS and OWL ontologies play a role in the use
of RDFa? What are the business cases for using RDFa?

Taught by John Snelson.

As data formats, XML and RDF have sometimes been positioned as competing –
however a knowledge of both can lead to stronger data modelling solutions. This
class will look at these complimentary formats, discussing the technologies in
terms of their similarities and their differences, their strengths and their
weaknesses. Integral to this discussion is a comparison of the capabilities
given to the two formats by their respective query languages, XQuery and SPARQL.
Use cases will be described where RDF is more appropriate than XML and vice
versa, as well as cases where there is significant grey area.

Taught by Graham Klyne.

In common with others, applications that use semantic technologies must deal with
an interplay between information modelling, data access and user interactions.
But the representation flexibility and breadth of graph-based semantic
technologies bring some different opportunities and challenges compared with
approaches based on more traditional formats such as XML and/or tabular data
models. In this session, we will survey projects that used semantic technologies
to work with three different kinds of research data and related information:
fruit-fly genomics, classical art object descriptions and scientific workflows.
The context and goals for each of these will be introduced, together with a
summary of the technical approach adopted and consequent experiences. Finally,
taking a view of experiences gained across all the projects, some common themes
and broad lessons will be drawn out and discussed.

Taught by Andy Seaborne,
Graham Klyne,
John Snelson,
Kal Ahmed,
and Philip Fennell.

This panel session with all speakers will concentrate on the practical aspects of
what is stopping more people from implementing and using Semantic
Technologies