1. Ontology-driven User Interfaces
Organisation
Person
CSIRO
Activity
CLW
EIS
Jonathan
Tech Session: Ontology-driven User Interfaces
Role
Research Software Engineer
Topic
User interface design
Semantic Web
Ontology
Ontology-driven User Interfaces
Knowledge capture and use is a critical part of our daily activities for interoperability, however, much of this is captured in multiple different formats, schemas, and even semantic representations or is left implicit. Semantic Web technologies allow the integration of resource definitions and terms for users through the capture of semantics using ontologies with machine-readable knowledge representation languages, such as the Web Ontology Language, and standard schemas, such as SKOS. At the same time, web technologies and libraries have provided the ability to render rich, interactive user interfaces efficiently. This talk explores how we can leverage ontologies for driving user interfaces and software systems using modern web technologies and libraries. We also step through some demos of ontology-driven user interfaces.
Jonathan Yu | Research software engineer | 21 June 2013
CSIRO Land and Water | Environmental Information Systems

2. Overview (Semantic view)
Organisation
Person
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CSIRO
Activity
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CLW
EIS
Jonathan
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Tech Session: Ontology-driven User Interfaces
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interest
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Research Software Engineer
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Semantic Web
User interface design
Ontology
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3. Overview
Problem Recap of ontologies and semantic web User interfaces: Rich Internet Applications Ontology-driven user interfaces
Presentation title | Presenter name

4. Problem – NetCDF header example
Try to interpret these NetCDF metadata headers...
float DetR_N(record, k_centre, j_centre, i_centre) ;
DetR_N:tracer = "true" ;
DetR_N:coordinates = "t, x_centre, y_centre, z_centre" ;
DetR_N:units = "mg N m-3" ;
DetR_N:type = 4 ;
float Chl_MIM(time, latitude, longitude) ;
Chl_MIM:_FillValue = -999.f ;
Chl_MIM:long_name = "Chlorophyll concentration, MIM SVDC on Rrs" ;
Chl_MIM:units = "ug/l" ;

5. Problem – WDTF XML example
Try to interpret this...
<wdtf:result>
<wdtf:TimeSeries>
<wdtf:defaultInterpolationType>InstVal</wdtf:defaultInterpolationType> <wdtf:defaultUnitsOfMeasure>ML</wdtf:defaultUnitsOfMeasure> <wdtf:defaultQuality>quality-A</wdtf:defaultQuality>
<wdtf:timeValuePair time=" T01:29:35+10:00“>
</wdtf:timeValuePair>
</wdtf:TimeSeries>
</wdtf:result>
Presentation title | Presenter name

6. Problem
Semantics (meaning) are often kept implicit in syntax or in heads of people and can result in inconsistency, ambiguity, errors in the documentation, data, and software produced
Solution
Formalise semantics explicitly
Build tools to support its use in documentation, annotation of datasets, and software engineering activities

7. Ontologies enable specification of semantics
concepts (classes and instances)
the relationships between concepts
set of logical assertions that apply
Presentation title | Presenter name

8. Formalising ontologies as explicit artifacts
Provides:
context and the ability to precisely reference meaning
shared understanding of the semantics used between stakeholders
ability to leverage logics-based reasoning and querying
bind to / reuse of growing list of public ontologies
Using RDF-based ontology languages and vocabularies allow
Machine readable
Collection of truth statements and propositions
Draw inferences or possible states
“Web enabled”
RDF-based ontology languages are part of the semantic web stack

9. The semantic web
‘Status quo’ web : web of documents The semantic web: web of data
<a href...>
Melbourne
Australia
gn:parentCountry
Victoria
gn:parentFeature
“ ”
“ ”
pos:lat
pos:long
Move away from implicit or adhoc semantics in documents to having semantics or meaning available with documents, with the data.
Performing event detection over real-time sensor data using ontology-driven approaches | Jonathan Yu

10. Uses of RDF-based ontologies/vocabularies: Knowledge representation
Some uses on the producer side...
1. Use ontologies to perform semantic annotation of datasets.
E.g. ML refers to the unit of measure, MegaLitres
2. Representing domain knowledge
e.g. Hydrological concepts - flow, rainfall
3. Promote consistency in your application
E.g. Black Mountain is a geospatial feature located in Canberra, not the class of black coloured mountains
Presentation title | Presenter name

11. Uses of RDF-based ontologies/vocabularies: Driving software applications and services
Some uses on the consumer side
1. Data Discovery and semantic search
2. Driving user interfaces
Have been doing this in some projects in varying degrees: eReefs, WDTS, Tools and Docs, SIRF, Geofabric
Presentation title | Presenter name

12. XML / JSON / RDF NetCDF / SHP / etc.
The “www” today
HTML, AJAX, RIA
Web Apps
Humans
Web
Server
Web
------
Application Server
XML / JSON / RDF NetCDF / SHP / etc.
Computers / Machines
Presentation title | Presenter name

13. Web Applications: Modern UI Development
Modern web UI development for Rich Internet Applications (RIA)
HTML, XHTML, XML, CSS
PHP, JSP, Javascript
AJAX components
Frameworks for developing modern web applications
Javascript: jQuery, Dojo
Python: Django, web2py
Microsoft : Visual C# / ASP.NET
Java - JavaServer Faces based (JSF): RichFaces, ICEfaces MyFaces, ADF Faces
Frameworks for generating RIA
Google Web Toolkit
Vaadin
Pyjamas
Presentation title | Presenter name

14. Ontology-driven UI Some powerful ontology libraries available:
Ontology APIs, e.g. OWL-API, Jena
Semantic inference engines, e.g. Pellet
Rules engine, e.g. SPIN
SPARQL querying, e.g. Jena ARQ
Not immediately usable by common web application frameworks
Developed some wrappers using GWT to provide access to these libraries
Demonstrate what is possible with ontology-driven UIs
Presentation title | Presenter name

15. Ontology-driven UI using GWT Ontology Lib
HTML, AJAX, RIA
Web application server
Web UI Framework: GWT (List boxes, portlets, trees, layouts, etc.)
Humans
OWL / RDF Interfaces
Inferences
Queries
Rules
GWT wrapper to ontology libraries and toolkits
OWL-api: Native Java interface to OWL ontologies
Jena: Native Java interface to OWL ontologies and querying using SPARQL
Pellet: Inferencing using ontology reasoners
RDF documents and triple stores
Pellet
SPARQL
SPIN
OWL-api
Apache Jena
Presentation title | Presenter name

16. Examples using GWT Ontology Library
Presentation title | Presenter name

17. Thank you Land and Water Jonathan Yu Research Software Engineere w
Land and Water