1. Linked Services for the
Web of Data
John Domingue, Knowledge Media Institute,
The Open University, UK
STI International, Austria
2. Overview
• Linked data introduction
– Linked data successes
• Linked Services
– Approaches and principles
– Technologies supporting Linked Services
• Models: MicroWSMO, WSMO-Lite and the Minimal Service Model
• Tools: iServe, SWEET and OmniVoke
• Sample applications
– House hunting
– Integrating advertising and video in Watch‟n‟Buy
• Current and future work
• Summary
7. Linked Data Principles
Set of best practices for publishing structured
data on the Web in accordance with the general
architecture of the Web.
1. Use URIs as names for things.
2. Use HTTP URIs so that people can look up those
names.
3. When someone looks up a URI, provide useful
RDF information.
4. Include RDF statements that link to other URIs so
that they can discover related things.
Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2006
26. Linked Data and Services
• Provide a platform for building applications on top of
Linked Data
• Connect services and semantic formats within the Web
context
• Ease the tasks associated with building applications
from online service components
31. Linked Services Principles
• Services described as Linked Data
– Inputs, outputs, functionality, etc is described using RDF(S) and
using existing vocabularies
• Consume and produce RDF
– Applications may contain „standard services‟ too
• Process layer on top of the Web of Data
37. iServe Key Features
• Support for several SWS formalisms
– WSMO-Lite, MicroWSMO, SAWSDL, OWL-S
• Supports access via
– Web Application - iServe Browser
– Read and Write RESTful API
– Linked Data principles
– SPARQL endpoint
– Content negotiation (RDF, HTML)
• Support for hybrid discovery
• Integration of social features (tags, comments,
ratings)
44. SWEET: Initial State
Current status of the
annotation in the form Input: HTML description of the Web API Addition of
of a tree structure (local representation of the HTML, which is the HTML tags
used as a basis for the annotation process)
Dynamics, APIs and Services / Hands-on SWEET/iServe and WSMT - 44
77. A New Era of Socio-Inspired
Technology
New socially interactive Better understanding,
ICT enabled by monitoring,
complexity theory and and management of global
novel social science society enabled by new ICT
influences
computer complexity social
science science science
influences
78. Planetary
Nervous
Participatory
System
Platform
Global
high-level semantically
meaningful information
Living
Earth
Simulator
complex predictions (e.g “financial crisis likely”)
79. Summary
• Linked data now a mainstream mechanism for sharing
data on the Web
• Now a requirement for application development support
– Especially within emerging Linked Data portals
• Linked services
– Services which consume and produce linked data
– Described as Linked Data
– Approaches and principles
• Technologies supporting Linked Services
• Models: MicroWSMO, WSMO-Lite and the Minimal Service Model
• Tools: iServe, SWEET, OmniVoke….
• Validation of approach through diverse application
scenarios
• Linked-USDL for services at the business level
80. Acknowledgements
• BBC slides adapted from Jem Rayfield
http://www.slideshare.net/JemRayfield/mark-logic-
usergroup2012
• Internet of Services adapted from SAP including Axel
Fasse http://www.slideshare.net/drleidig/linked-usdl-at-
the-fiware-architects-weeks-in-madrid
• Chris Bizer, Jacek Kopecky, Ning Li, Dong Liu, Maria
Maleshkova, Carlos Pedrinaci
• Funded by the SOA4All, NoTube, PlanetData and VPH
Share projects
81. Thanks
• More details at: iserve.kmi.open.ac.uk
• Interested in a PhD Studentship or internship?
– John.domingue@open.ac.uk
Notas del editor
27 Live Video Steams for Olympics Live Stats overlaysStats -> Ontology driven aggregations
Open Graph Protocol Inspired by Dublin Core, link-rel canonical, Microformats, and RDFa.3,000,000 likes per day! ‘Like’ buttons now appearing across all websites. These now generate With associated data
700 billion minutes per month on Facebook900 million content pages30 billion pieces of contentGenerating a graph of people, photos, friends and online resources
Supports RDFa Lite a lightweight version of RDFa which can be used to embed RDF into web pages
Google knowledge graphBased on Metaweb’s Freebase
8665 datasets
31billion statements, 450M links
So how do we link to this wealth of data?We have our own repository of service descriptions within the cloud. We are the first and still only service repository in this space. The are created using a variety of tools. Note that when creating our descriptions we can rely on existing descriptions in the cloud. In the same way as one web page can point to another to expand a description.
Which can produce data for this large semantic cloud
Now I come to a first of 3 examples. This one from a recent project. Imagine that you are moving to a new area and you are looking for a house. You would be concerned with
Depending on your circumstances
Within one of my projects (soa4all) we have developed an iPhone App to support this. Its available in the store and called the soa4all real estate finder
Mulberry school and others
Services over public data (to the singers in the virtual choir)Service broker is like the conductor. Services are published in our broker. An engine translates between user actions and details of invoking services (each service may have its own idiosyncratic way of being invoked)User interacts with the iPhone Appdiscovery based on user preferences and location -> services are available Services are not fixed (like singers for each performance). adding more for crime statistics also based on public data.
elasticity of heart muscles, another modelling blood flow, another for different dysfucntionsPatient avatar: a digital personalised representation of a patient for diagnosis and treatmentIn the media domainWe have a new project which started in Spring which will look at sharing processes related to the human body across Europe to support research and patient care. One of the processes to be modelled will be the human heart. The idea is that across varies labs in Europe there will be a bits and pieces of data and software – e.g. Our broker will be used to put these pieces together into a coherent whole and also to integrate into patient specific data leading to personalised patient avatars – a digital represention of your relevant processes supporting diagnosis and treatment.