According to a PriceWaterhouseCoopers report, “Semantic Web technologies could revolutionize enterprise decision making and information sharing”. By connecting more flexible, standardized ways to model and share data with best practices for identifying the meaning (or, at the very least, the source) of descriptive terms, Semantic Web technologies open up new possibilities for developing applications that work across the web or behind your firewall.
In this course, we’ll learn about the building blocks of the Semantic Web such as the RDF data model, the RDFa version that lets you embed machine-readable facts (or “triples”) into web pages, the SPARQL query language, and the Web Ontology Language (OWL) for defining vocabularies and term relationships. We’ll also learn about some of the open source and commercial software that lets you assemble these building blocks into applications that help you get more out of both your own data and the increasing amount of publicly available linked data, and see some examples of these technologies put into practise.
Classes for 2013
The Semantic Technologies 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 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?
- RDF and XML
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.
- Research Data Management: Dealing with Diversity
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.
- What's holding people back?
This panel session with all speakers will concentrate on the practical aspects of what is stopping more people from implementing and using Semantic Technologies