OntoViews

1
OntoViews A Tool for Creating Semantic Web
Portals

• Eetu Mäkelä, Eero Hyvönen, Samppa Saarela and Kim
  Viljanen (firstname.lastname_at_helsinki.fi)
• Semantic Computing Research Group Helsinki
  Institute for Information Technology (HIIT)
  University of Helsinki, Dept. of Computer
  Science
• http//www.cs.helsinki.fi/group/seco/

2
The Semantic Web research project group
(2002-2004)

• prof. Eero Hyvönen
• Miikka Junnila
• Suvi Kettula
• Eetu Mäkelä
• Samppa Saarela
• Mirva Salminen
• Ahti Syreeni
• Arttu Valo
• Kim Viljanen

3
Research Consortium
Helsinki University Museum
Co-operation withFinnish National Gallery
4
Topics

• The motivation behind OntoViews
• OntoViews from an end-user's perspective
• Implementation
• Summary

5
The Motivation Behind OntoViews

• Much of the semantic web content will be
  published using semantic portals. Such portals
  usually provide the end-user with two basic
  services
• A search engine based on the semantics of the
  content
• Browsing functionality based on the semantic
  relations in the underlying knowledge base
• In order to realize the promises of the Semantic
  Web, such a portal should be
• Usable for an end-user
• Easily integrated and extended with additional
  functionality
• Usable with a variety of different devices
• Adaptable to a wide variety of semantic data
• Scalable to accommodate large amounts of data
• Able to provide its functionality also to other
  programs as Semantic Web Services
• We wanted to create a tool to create such portals

6
Topics

• The motivation behind OntoViews
• OntoViews from an end-user's perspective
• Implementation
• Summary

7
OntoViews from an End-User's Perspective

• Search
• A search engine based on the semantics of the
  content
• Usable for an end-user
• Easily integrated and extended with additional
  functionality
• Browsing
• Browsing functionality based on the semantic
  relations in the underlying knowledge base
• Layout adaptability
• Usable with a variety of different devices

8
OntoViews from an End-User's Perspective

• Search
• A search engine based on the semantics of the
  content Concept-based Multi-Facet and keyword
  search
• Usable for an end-user Based on the tested and
  true Flamenco interface
• Easily integrated and extended with additional
  functionality Seamless integration in the user
  interface of keyword and other searches
• Browsing
• Browsing functionality based on the semantic
  relations in the underlying knowledge base
  Classification tree view, explicit semantic links
  in item view
• Layout adaptability
• Usable with a variety of different devices

9
OntoViews from an End-User's Perspective

• Search
• A search engine based on the semantics of the
  content Concept-based Multi-Facet and keyword
  search
• Usable for an end-user Based on the tested and
  true Flamenco interface
• Easily integrated and extended with additional
  functionality Seamless integration in the user
  interface of keyword and other searches
• Browsing
• Browsing functionality based on the semantic
  relations in the underlying knowledge base
  Classification tree view, explicit semantic links
  in item view
• Layout adaptability
• Usable with a variety of different devices

10
OntoViews from an End-User's Perspective Layout

• Layout
• Usable with a variety of different devices
  Different user interfaces and functionality for
  different devices

11
Topics

• The motivation behind OntoViews
• OntoViews from an end-user's perspective
• Implementation
• Summary

12
The Architecture of OntoViews

• Comprised of three main components
• Ontodella, a prolog-based logic server
• Ontogator, a java-based multi-facet search engine
• OntoViews-C, the main Apache Cocoon -based
  interaction and control component

The User
java text/RDF
http text/RDF
file text/RDF
13
Implementation

• The Logic Server Ontodella
• Adaptable to a wide variety of semantic data
• The Multi-Facet Search Engine Ontogator
• Scalable to accommodate large amounts of data
• Easily integrated and extended with additional
  functionality
• OntoViews-C, the Interaction and Control
  Component
• Easily integrated and extended with additional
  functionality
• Able to provide its functionality also to other
  programs as Semantic Web Services

14
The Logic Server Ontodella

• Projects view-facets from the data to be used in
  search utilizing defined logic rules, for
  example
• ontodella_view( Place of use
• 'http//www.cs.helsinki.fi/seco/ns/2004/03/place
  searth', Root URI
• place_sub_category, Subcategory Rule
• place_of_use_item_mapping, Item Mapping
  Rule
• fi'Käyttöpaikka', en'Place of Use' Label
  Definition
• ).
• place_sub_category( ParentCategory, SubCategory )
  -
• SubCategoryProperty 'http//www.cs.helsinki.fi
  /seco/ns/2004/03/placesisContainedBy',
• rdf( SubCategory, SubCategoryProperty,
  ParentCategory ).
• place_of_use_item_mapping( ResourceURI,
  CategoryURI ) -
• Relation 'http//www.cs.helsinki.fi/seco/ns/20
  04/03/artifactsusedIn',
• rdf( ResourceURI, Relation, CategoryURI ).

15
The Logic Server Ontodella

• Projection adaptability has been tested with
  different data sets
• Museum item data and ontologies from the
  MuseumFinland project
• Yellow-page service provider data and ontologies
  from the IWebS project
• A further Java-based development of the
  projection system has additionally been tested
  with
• Website data and categorisations from the
  dmoz.org directory
• Further work Neither implementation currently
  supports adding or deleting of individual
  categories or items from the knowledge base

16
The Logic Server Ontodella

• Semantically links individual items to each other
  by utilizing defined logic rules, for example
• same_user( Subject, Target, Explanation ) -
• ItemToUserRelatingProperty
• 'http//www.cs.helsinki.fi/group/seco/ns/2004/03/a
  rtifacts'user,
• rdf( Subject, ItemToUserRelatingProperty,
  User ), the users of our current item
• not( some_instance_of_unknown( User ) ),
  who are not unknown
• rdf( Target, ItemToUserRelatingProperty, User
  ), other items used by that user
• viewable( TargetURI ), make sure they
  are viewable
• SubjectURI \ TargetURI, don't link
  the item with itself
• list_labels( User, RelLabel ), get a
  description of the linking resource
• ExplanationcommonResources(RelationInstanceU
  RI), label(fiRelLabel).

17
Implementation

• The Logic Server Ontodella
• Adaptable to a wide variety of semantic data
  Facet hierarchy projection and semantic link
  generation are based on extendable logic rules.
  The projection rules have been tested with three
  different data sets.
• The Multi-Facet Search Engine Ontogator
• Scalable to accommodate large amounts of data
• Easily integrated and extended with additional
  functionality
• OntoViews-C, the Interaction and Control
  Component
• Easily integrated and extended with additional
  functionality
• Able to provide its functionality also to other
  programs as Semantic Web Services

18
Implementation

• The Logic Server Ontodella
• Adaptable to a wide variety of semantic data
  Facet hierarchy projection and semantic link
  generation are based on extendable logic rules.
  The projection rules have been tested with three
  different data sets.
• The Multi-Facet Search Engine Ontogator
• Scalable to accommodate large amounts of data
• Easily integrated and extended with additional
  functionality
• OntoViews-C, the Interaction and Control
  Component
• Easily integrated and extended with additional
  functionality
• Able to provide its functionality also to other
  programs as Semantic Web Services

19
The Multi-Facet Search Engine Ontogator

• Is a generic view-based RDF search engine
• Defines and implements an RDF-based query
  interface defined as an OWL ontology
• Replies to queries in RDF/XML that has a fixed
  structure.
• The query operations are based on category and
  item selectors. The functionality of the engine
  can be extended by implementing new selector
  types (keyword search and geolocation search in
  OntoViews, for example)
• Has been tested with dmoz.org data to scale to up
  to 2.3 million items and 275.000 categories with
  search times of about 5 seconds.
• Future work Does not yet scale well to
  accommodate multiple simultaneous users

20
Implementation

• The Logic Server Ontodella
• Adaptable to a wide variety of semantic data
  Facet hierarchy projection and semantic link
  generation are based on extendable logic rules.
  The projection rules have been tested with three
  different data sets.
• The Multi-Facet Search Engine Ontogator
• Scalable to accommodate large amounts of data
  Ontogator has been tested with dmoz.org data to
  scale to up to 2.3 million items and 275.000
  categories with search times of about 5 seconds.
• Easily integrated and extended with additional
  functionality The architecture allows for
  extensions by implementing new types of selectors
  (keyword, geolocation). The RDF query model and
  fixed structure RDF/XML result allow for easy
  integration.
• OntoViews-C, the Interaction and Control
  Component
• Easily integrated and extended with additional
  functionality
• Able to provide its functionality also to other
  programs as Semantic Web Services

21
Implementation

• The Logic Server Ontodella
• Adaptable to a wide variety of semantic data
  Facet hierarchy projection and semantic link
  generation are based on extendable logic rules.
  The projection rules have been tested with three
  different data sets.
• The Multi-Facet Search Engine Ontogator
• Scalable to accommodate large amounts of data
  Ontogator has been tested with dmoz.org data to
  scale to up to 2.3 million items and 275.000
  categories with search times of about 5 seconds.
• Easily integrated and extended with additional
  functionality The architecture allows for
  extensions by implementing new types of selectors
  (keyword, geolocation). The RDF query model and
  fixed structure RDF/XML result allow for easy
  integration.
• OntoViews-C, the Interaction and Control
  Component
• Easily integrated and extended with additional
  functionality
• Able to provide its functionality also to other
  programs as Semantic Web Services

22
The Interaction and Control Component OntoViews-C

• Built on top of the Apache Cocoon architecture
• The Cocoon architecture is based upon the concept
  of pipelines, comprised of modular components
  (generators, transformers and serializers) that
  consume and/or produce XML
• This forces a modular, reusable and extendable
  design
• In OntoViews, all components produce not only
  XML, but valid RDF/XML. This, along with a
  generator for handling HTTP requests, allows for
  the exposition of all parts of the system as Web
  Services

23
Implementation

• The Logic Server Ontodella
• Adaptable to a wide variety of semantic data
  Facet hierarchy projection and semantic link
  generation are based on extendable logic rules.
  The projection rules have been tested with three
  different data sets.
• The Multi-Facet Search Engine Ontogator
• Scalable to accommodate large amounts of data
  Ontogator has been tested with dmoz.org data to
  scale to up to 2.3 million items and 275.000
  categories with search times of about 5 seconds.
• Easily integrated and extended with additional
  functionality The architecture allows for
  extensions by implementing new types of selectors
  (keyword, geolocation). The RDF query model and
  fixed structure RDF/XML result allow for easy
  integration.
• OntoViews-C, the Interaction and Control
  Component
• Easily integrated and extended with additional
  functionality Cocoon architecture forces a
  modular, reusable and extendable design. All
  components operate independently, consuming
  and/or producing RDF/XML
• Able to provide its functionality also to other
  programs as Semantic Web Services All subparts
  of the system are available to be used via Web
  Services

24
Summary OntoViews is

• A search engine based on the semantics of the
  content Concept-based Multi-Facet and keyword
  search
• Browsing functionality based on the semantic
  relations in the underlying knowledge base
  Classification tree view, explicit semantic links
  in item view
• Usable for an end-user Based on the tested and
  true Flamenco interface
• Easily integrated and extended with additional
  functionality Seamless integration in the user
  interface of keyword and other searches, the
  search architecture allows for extensions, and
  the Cocoon control architecture forces a modular,
  reusable and extendable design. All components
  operate independently, consuming and/or producing
  RDF/XML.
• Usable with a variety of different devices
  Different user interfaces and functionality for
  different devices
• Adaptable to a wide variety of semantic data
  Facet hierarchy projection and semantic link
  generation are based on extendable logic rules.
  The projection rules have been tested with three
  different data sets.
• Scalable to accommodate large amounts of data
  OntoViews has been tested with dmoz.org data to
  scale to up to 2.3 million items and 275.000
  categories with search times of about 5 seconds.
• Able to provide its functionality also to other
  programs as Semantic Web Services All subparts
  of the system are available to be used via Web
  Services
• Future work Ideas about dynamic facet creation,
  further optimizations to improve scalability
• Available for download at http//www.cs.helsinki.f
  i/group/seco/museums/dist/