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Background          Collection             Storage and management   Retrieval




            Managing ontologies for modelling the
         physical and political structure of a university

                                 Sebastian Rahtz
Background                Collection         Storage and management       Retrieval



                                       Background


      Our problem is to come up with a framework in which to model
      the structure of the University, both political and physical.
             • what do we record?
             • how do we store it?
             • how do we allow retrieval from it?

      Remember, in what follows, that Oxford is unusual in having
      legal entities (the colleges) distinct from the University. Other
      institutions will have something similar.
Background                Collection          Storage and management      Retrieval



                                       Oxpoints I


      The first generation of our work, which we called Oxpoints:
             • Covered colleges and departments as general-purpose
              ‘units’
             • Modelled a hierarchical arrangement of buildings within
              units
             • Showed time-based data as an attribute of e.g. a college
             • Was managed as a large XML file mediated through a
              series of ad hoc XSLT transformations
             • Used the Text Encoding Initiative schema
Background                Collection          Storage and management          Retrieval



                       Problems with this approach


             • It did not cope with change over time (buildings change
              hands, departments migrate and amalgamate)
             • It did not allow for a building being used by several
              departments at once
             • It did not record any relationships between units; e.g. that
              a research group is part of a department, or that a rare
              books library is part of a bigger library
             • It was not easily extensible to other data types and
              relationships in the future (network access ducts? wireless
              access points? bicycle stands? trees?)
Background            Collection         Storage and management         Retrieval



                  Requirements for Oxpoints II


      Time based data A time dimension should be introduced to be
                 able to create historical maps.
      Rich Relationships It should be able to express many different
                   kind of relationships between entities in the
                   system.
      More Entities Besides colleges and buildings many more
                   entities should be added to the system (e.g. drain
                   covers).
      Extendable Since nobody could pin down where OxPoints was
                 to be going it should be as easy as possible to
                 extend the system in any way imaginable.
Background            Collection        Storage and management         Retrieval



                The underlying framework: RDF

      We conducted research for several months and finally decided
      to go with an RDF (a standard maintained by the W3C, meant
      to express relationships between entities) based solution.
      Time based data We have found a way to introduce a time
                 dimension using named graphs
      Rich Relationships RDF is meant to express rich
                   relationsships.
      More Entities RDF has no restrictions on the elements it talks
                   about. As long as you can make up a URI for the
                   element, you can use RDF to describe it.
      Extendable RDF is very generic and meant to be extended.
Background             Collection          Storage and management         Retrieval



                    The implementation: Gaboto
      Gaboto (http://gaboto.sf.net) is an open source generic
      RDF storage engine that allows for automatic mapping from
      RDF to Java objects and is able to cope with time in RDF. It
      was developed for Oxpoints, but is completely generic.
      Gaboto gives you RDF's flexibility of storing objects, their
      properties and relationships between objects while mapping
      these structures to first class Java objects.
      The mapping rules are all configured in an XML configuration
      file from which the necessary classes are automatically
      generated. So the basic steps in using Gaboto are:
        1. Write configuration file, define objects, their properties and
           relationships.
        2. Execute configuration script, that basically generates a jar
           file.
        3. Plug in the jar file and start writing your system.
Background                  Collection                Storage and management         Retrieval



                                 Ontology examples
      <ObjectProperty xmlns="http://www.w3.org/2002/07/owl#"
        about="#associatedWith">
        <comment xmlns="http://www.w3.org/2000/01/rdf-schema#"
        >Defines that two entities are associated with one another (N:M)</comment>
      </ObjectProperty>
      <ObjectProperty xmlns="http://www.w3.org/2002/07/owl#"
        about="#capacity">
        <comment xmlns="http://www.w3.org/2000/01/rdf-schema#"
        >The number of cars that can park</comment>
        <domain xmlns="http://www.w3.org/2000/01/rdf-schema#"
          resource="#Carpark"/>
      </ObjectProperty>
      <ObjectProperty xmlns="http://www.w3.org/2002/07/owl#"
        about="#occupies">
        <comment xmlns="http://www.w3.org/2000/01/rdf-schema#"
        >Describes that a unit occupies a place</comment>
        <range xmlns="http://www.w3.org/2000/01/rdf-schema#"
          resource="#Place"/>
        <domain xmlns="http://www.w3.org/2000/01/rdf-schema#"
          resource="#Unit"/>
      </ObjectProperty>
      <Class xmlns="http://www.w3.org/2002/07/owl#"
        about="#Building">
        <subClassOf xmlns="http://www.w3.org/2000/01/rdf-schema#"
          resource="#Place"/>
      </Class>
      <Class xmlns="http://www.w3.org/2002/07/owl#"
        about="#College">
        <subClassOf xmlns="http://www.w3.org/2000/01/rdf-schema#"
          resource="#Unit"/>
      </Class>
Background                 Collection               Storage and management   Retrieval



             The configuration file (simplified sample)
      <GabotoEntity name="Unit" type="Unit">
        <properties>
          <property name="address" type="Address" uri="adr"/>
          <property name="homepage" type="Website" uri="hasHomepage"/>
          <property name="OUCSCode" type="String" uri="hasOUCSCode"/>
          <property name="itHomepage" type="Website" uri="hasITHomepage"/>
          <property name="name" type="String" uri="title"/>
          <property
              name="occupiedBuildings"
              type="Building"
              collection="bag"
              uri="occupies">
            <indirectProperty uri="hasLocation" n="2"/>
          </property>
          <property name="primaryPlace" type="Place" uri="primaryPlace">
            <indirectProperty name="location" uri="hasLocation" n="1"/>
          </property>
          <property name="subsetOf" type="Unit" uri="subsetOf">
            <indirectProperty uri="hasLocation" n="3"/>
            <unstoredProperty uri="parent"/>
          </property>
          <property name="weblearn" type="Website" uri="hasWeblearn"/>
          <passiveProperty
              name="hasSubsets"
              type="Unit"
              relationshipType="1:N"
              uri="subsetOf"/>
        </properties>
      </GabotoEntity>
Background                 Collection         Storage and management     Retrieval



    So we move to the second generation of Oxpoints



             • Still covers colleges, departments, libraries, museums, and
              carparks, but also anything else one may encounter
             • Models political units, physical buildings and a set of
              relationships between them
             • Is managed in an RDF database
             • Has an explicit RDF ontology, using external standards
              where appropriate (Dublin Core, GML, vCard)
             • Explicitly models time and changes
Background                  Collection   Storage and management   Retrieval



                       Types of objects in our system

             • Building
             • Division
             • DrainCover
             • Entrance
             • Faculty
             • Group
             • Image
             • Room
             • ServiceDepartment
             • Site
             • WAP
             • Website
Background                Collection       Storage and management   Retrieval



                   Types of relationship in our system
             • associatedWith
             • capacity
             • hasITHomepage
             • hasLocation
             • hasOBNCode
             • hasOLISCode
             • hasOUCSCode
             • hasPrimaryPlace
             • hasWeblearn
             • homepage
             • inImage
             • occupies
             • physicallyContainedWithin
             • subsetOf
Background                    Collection          Storage and management   Retrieval



                                           Collection

      We have collected information on about 1000 ‘political entities’:
             Library                                     743
             Unit                                        19
             College                                     45
             Department                                  186
             Museum                                      7


      along with
             Carpark                                             10
             building                                            277
             relationships                                       891
             coordinates of points                               283
Background                Collection         Storage and management      Retrieval



                     Where did this data come from?


             • Our central registration database provided the core
              structure of units, addresses etc
             • Library system provided the catalogue of library codes and
              names
             • Our own nosing around added web page links and photos
             • Coordinates were created about 50% from walking around
              with a GPS, 50% from reading off Google Earth
             • Our Estates Department provided a set of their building
              codes and informal building descriptions
Background                Collection         Storage and management         Retrieval



                         How are things identified?



             • Everything has a unique, stable Oxpoints ID (simply a
              number)
             • Registration codes are stored as properties of relevant
              objects
             • Library codes are stored as properties of relevant objects
             • Buildings have an optional property of their Estates code
             • Objects all have a type
Background               Collection            Storage and management   Retrieval



                        Storage and management



      An initializing Gaboto can read data from
             • Serialized RDF representation
             • A relational database backend for Jena
             • A TEI-encoded XML file

      The first of these is the backup format.
      Editing data is currently a manual task.
Background                Collection           Storage and management     Retrieval



                                       Future plans



      We intend to manage
             • A read-only Gaboto instance, reinitialized every day, to
              deliver lookup services
             • A read/write Gaboto instance linked to a relational
              database for managing changes and additions
             • A map-based interface for adding data
Background                 Collection           Storage and management       Retrieval



                                        Retrieval



      The main retrieval mechanism is via a web service which can:
             • Select objects by type, by internal ID, and by various codes
               (from registration, estates, libraries etc)
             • Follow relationships (eg from political entity to buildings
               which it occupies)
             • Sort by properties (typically dc:title)
             • Serialize the results in a variety of formats
Background            Collection        Storage and management    Retrieval



                            Supported formats


      We currently support
              xml Serialized RDF in XML.
              json Serialized as JSON for consumption by Javascript
                   etc (with optional callback function)
              kml Summary information in the KML format used by
                  Google Earth and Google Maps
             gjson The summary form used by KML, serialized as
                   JSON (with optional callback function)
      We also currently convert KML to any format supported by
      gpsbabel (support for many GPS and satnav devices)
Background             Collection             Storage and management   Retrieval



                                    Demonstration
        1. Oxford Colleges (using Google Maps):
             http://maps.google.co.uk/?q=http:
             //m.ox.ac.uk/oxpoints/colleges.kml
        2. Oxford Museums:
           http://m.ox.ac.uk/oxpoints/museums.kml
        3. Balliol College: http://maps.google.co.uk/?q=http:
           //m.ox.ac.uk/oxpoints/oucs/ball.kml&z=16
        4. Balliol College (RDF):
             http://m.ox.ac.uk/oxpoints/oucs/ball.xml
        5. Balliol College (JSON):
             http://m.ox.ac.uk/oxpoints/oucs/ball.json
        6. Balliol College: http://maps.google.co.uk/?q=http:
             //m.ox.ac.uk/oxpoints/oucs/ball.kml&z=16
        7. Balliol College (all buildings):
             http://maps.google.co.uk/?q=http:
             //m.ox.ac.uk/oxpoints/oucs/ball/occupies.kml
        8. All Souls College and Ashmolean Museum:
Background            Collection        Storage and management       Retrieval



                                   Arcana

        1. (using old Oxpoints) Map of Oxford in Google Earth
           showing colleges, and time line
             http://www.oucs.ox.ac.uk/oxpoints/colleges.kml
        2. Map of Oxford using Open Streetmap showing university
           departments
             http://www.oucs.ox.ac.uk/oxpoints/test9.html
        3. Map of Oxford showing running route, with background on
           old Ordnance Survey map. http://wheresthepath.
           googlepages.com/wheresthepath.htm; using GPX data;
           result is picture3.png
        4. Oxford University carparks, displayed on TomTom
             http://m.ox.ac.uk/oxpoints/Carpark.tomtom

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Managing Ontologies

  • 1. Background Collection Storage and management Retrieval Managing ontologies for modelling the physical and political structure of a university Sebastian Rahtz
  • 2. Background Collection Storage and management Retrieval Background Our problem is to come up with a framework in which to model the structure of the University, both political and physical. • what do we record? • how do we store it? • how do we allow retrieval from it? Remember, in what follows, that Oxford is unusual in having legal entities (the colleges) distinct from the University. Other institutions will have something similar.
  • 3. Background Collection Storage and management Retrieval Oxpoints I The first generation of our work, which we called Oxpoints: • Covered colleges and departments as general-purpose ‘units’ • Modelled a hierarchical arrangement of buildings within units • Showed time-based data as an attribute of e.g. a college • Was managed as a large XML file mediated through a series of ad hoc XSLT transformations • Used the Text Encoding Initiative schema
  • 4. Background Collection Storage and management Retrieval Problems with this approach • It did not cope with change over time (buildings change hands, departments migrate and amalgamate) • It did not allow for a building being used by several departments at once • It did not record any relationships between units; e.g. that a research group is part of a department, or that a rare books library is part of a bigger library • It was not easily extensible to other data types and relationships in the future (network access ducts? wireless access points? bicycle stands? trees?)
  • 5. Background Collection Storage and management Retrieval Requirements for Oxpoints II Time based data A time dimension should be introduced to be able to create historical maps. Rich Relationships It should be able to express many different kind of relationships between entities in the system. More Entities Besides colleges and buildings many more entities should be added to the system (e.g. drain covers). Extendable Since nobody could pin down where OxPoints was to be going it should be as easy as possible to extend the system in any way imaginable.
  • 6. Background Collection Storage and management Retrieval The underlying framework: RDF We conducted research for several months and finally decided to go with an RDF (a standard maintained by the W3C, meant to express relationships between entities) based solution. Time based data We have found a way to introduce a time dimension using named graphs Rich Relationships RDF is meant to express rich relationsships. More Entities RDF has no restrictions on the elements it talks about. As long as you can make up a URI for the element, you can use RDF to describe it. Extendable RDF is very generic and meant to be extended.
  • 7. Background Collection Storage and management Retrieval The implementation: Gaboto Gaboto (http://gaboto.sf.net) is an open source generic RDF storage engine that allows for automatic mapping from RDF to Java objects and is able to cope with time in RDF. It was developed for Oxpoints, but is completely generic. Gaboto gives you RDF's flexibility of storing objects, their properties and relationships between objects while mapping these structures to first class Java objects. The mapping rules are all configured in an XML configuration file from which the necessary classes are automatically generated. So the basic steps in using Gaboto are: 1. Write configuration file, define objects, their properties and relationships. 2. Execute configuration script, that basically generates a jar file. 3. Plug in the jar file and start writing your system.
  • 8. Background Collection Storage and management Retrieval Ontology examples <ObjectProperty xmlns="http://www.w3.org/2002/07/owl#" about="#associatedWith"> <comment xmlns="http://www.w3.org/2000/01/rdf-schema#" >Defines that two entities are associated with one another (N:M)</comment> </ObjectProperty> <ObjectProperty xmlns="http://www.w3.org/2002/07/owl#" about="#capacity"> <comment xmlns="http://www.w3.org/2000/01/rdf-schema#" >The number of cars that can park</comment> <domain xmlns="http://www.w3.org/2000/01/rdf-schema#" resource="#Carpark"/> </ObjectProperty> <ObjectProperty xmlns="http://www.w3.org/2002/07/owl#" about="#occupies"> <comment xmlns="http://www.w3.org/2000/01/rdf-schema#" >Describes that a unit occupies a place</comment> <range xmlns="http://www.w3.org/2000/01/rdf-schema#" resource="#Place"/> <domain xmlns="http://www.w3.org/2000/01/rdf-schema#" resource="#Unit"/> </ObjectProperty> <Class xmlns="http://www.w3.org/2002/07/owl#" about="#Building"> <subClassOf xmlns="http://www.w3.org/2000/01/rdf-schema#" resource="#Place"/> </Class> <Class xmlns="http://www.w3.org/2002/07/owl#" about="#College"> <subClassOf xmlns="http://www.w3.org/2000/01/rdf-schema#" resource="#Unit"/> </Class>
  • 9. Background Collection Storage and management Retrieval The configuration file (simplified sample) <GabotoEntity name="Unit" type="Unit"> <properties> <property name="address" type="Address" uri="adr"/> <property name="homepage" type="Website" uri="hasHomepage"/> <property name="OUCSCode" type="String" uri="hasOUCSCode"/> <property name="itHomepage" type="Website" uri="hasITHomepage"/> <property name="name" type="String" uri="title"/> <property name="occupiedBuildings" type="Building" collection="bag" uri="occupies"> <indirectProperty uri="hasLocation" n="2"/> </property> <property name="primaryPlace" type="Place" uri="primaryPlace"> <indirectProperty name="location" uri="hasLocation" n="1"/> </property> <property name="subsetOf" type="Unit" uri="subsetOf"> <indirectProperty uri="hasLocation" n="3"/> <unstoredProperty uri="parent"/> </property> <property name="weblearn" type="Website" uri="hasWeblearn"/> <passiveProperty name="hasSubsets" type="Unit" relationshipType="1:N" uri="subsetOf"/> </properties> </GabotoEntity>
  • 10. Background Collection Storage and management Retrieval So we move to the second generation of Oxpoints • Still covers colleges, departments, libraries, museums, and carparks, but also anything else one may encounter • Models political units, physical buildings and a set of relationships between them • Is managed in an RDF database • Has an explicit RDF ontology, using external standards where appropriate (Dublin Core, GML, vCard) • Explicitly models time and changes
  • 11. Background Collection Storage and management Retrieval Types of objects in our system • Building • Division • DrainCover • Entrance • Faculty • Group • Image • Room • ServiceDepartment • Site • WAP • Website
  • 12. Background Collection Storage and management Retrieval Types of relationship in our system • associatedWith • capacity • hasITHomepage • hasLocation • hasOBNCode • hasOLISCode • hasOUCSCode • hasPrimaryPlace • hasWeblearn • homepage • inImage • occupies • physicallyContainedWithin • subsetOf
  • 13. Background Collection Storage and management Retrieval Collection We have collected information on about 1000 ‘political entities’: Library 743 Unit 19 College 45 Department 186 Museum 7 along with Carpark 10 building 277 relationships 891 coordinates of points 283
  • 14. Background Collection Storage and management Retrieval Where did this data come from? • Our central registration database provided the core structure of units, addresses etc • Library system provided the catalogue of library codes and names • Our own nosing around added web page links and photos • Coordinates were created about 50% from walking around with a GPS, 50% from reading off Google Earth • Our Estates Department provided a set of their building codes and informal building descriptions
  • 15. Background Collection Storage and management Retrieval How are things identified? • Everything has a unique, stable Oxpoints ID (simply a number) • Registration codes are stored as properties of relevant objects • Library codes are stored as properties of relevant objects • Buildings have an optional property of their Estates code • Objects all have a type
  • 16. Background Collection Storage and management Retrieval Storage and management An initializing Gaboto can read data from • Serialized RDF representation • A relational database backend for Jena • A TEI-encoded XML file The first of these is the backup format. Editing data is currently a manual task.
  • 17. Background Collection Storage and management Retrieval Future plans We intend to manage • A read-only Gaboto instance, reinitialized every day, to deliver lookup services • A read/write Gaboto instance linked to a relational database for managing changes and additions • A map-based interface for adding data
  • 18. Background Collection Storage and management Retrieval Retrieval The main retrieval mechanism is via a web service which can: • Select objects by type, by internal ID, and by various codes (from registration, estates, libraries etc) • Follow relationships (eg from political entity to buildings which it occupies) • Sort by properties (typically dc:title) • Serialize the results in a variety of formats
  • 19. Background Collection Storage and management Retrieval Supported formats We currently support xml Serialized RDF in XML. json Serialized as JSON for consumption by Javascript etc (with optional callback function) kml Summary information in the KML format used by Google Earth and Google Maps gjson The summary form used by KML, serialized as JSON (with optional callback function) We also currently convert KML to any format supported by gpsbabel (support for many GPS and satnav devices)
  • 20. Background Collection Storage and management Retrieval Demonstration 1. Oxford Colleges (using Google Maps): http://maps.google.co.uk/?q=http: //m.ox.ac.uk/oxpoints/colleges.kml 2. Oxford Museums: http://m.ox.ac.uk/oxpoints/museums.kml 3. Balliol College: http://maps.google.co.uk/?q=http: //m.ox.ac.uk/oxpoints/oucs/ball.kml&z=16 4. Balliol College (RDF): http://m.ox.ac.uk/oxpoints/oucs/ball.xml 5. Balliol College (JSON): http://m.ox.ac.uk/oxpoints/oucs/ball.json 6. Balliol College: http://maps.google.co.uk/?q=http: //m.ox.ac.uk/oxpoints/oucs/ball.kml&z=16 7. Balliol College (all buildings): http://maps.google.co.uk/?q=http: //m.ox.ac.uk/oxpoints/oucs/ball/occupies.kml 8. All Souls College and Ashmolean Museum:
  • 21. Background Collection Storage and management Retrieval Arcana 1. (using old Oxpoints) Map of Oxford in Google Earth showing colleges, and time line http://www.oucs.ox.ac.uk/oxpoints/colleges.kml 2. Map of Oxford using Open Streetmap showing university departments http://www.oucs.ox.ac.uk/oxpoints/test9.html 3. Map of Oxford showing running route, with background on old Ordnance Survey map. http://wheresthepath. googlepages.com/wheresthepath.htm; using GPX data; result is picture3.png 4. Oxford University carparks, displayed on TomTom http://m.ox.ac.uk/oxpoints/Carpark.tomtom