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External Schema for Topic Map Database

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In order to cope with large-scale topic maps that store a lot of information, it is necessary to utilize topic map databases. Although, database management systems should provide users with external …

In order to cope with large-scale topic maps that store a lot of information, it is necessary to utilize topic map databases. Although, database management systems should provide users with external schema functions such as views, topic map databases do not have such functions. In this paper, we propose a method of implementing a view function, by focusing on the fact that the substructure of topic maps can be regarded as a topic map. In order to realize the idea, we developed an access control system based on the view function. Through an experiment to measure the execution time, we confirmed that these functions work correctly and have little effect on the execution time.

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  • 1. External  Schema  of     Topic  Map  Databases Keita  Nabeta1,  Takashi  Kojima2,     Yuki  Kuribara1,  Takashi  Yamazaki1,  Masaomi  Kimura2   1Graduate  School  of  Engineering,  Shibaura  InsEtute  of  Technology   2Faculty  of  Engineering,  Shibaura  InsEtute  of  Technology  
  • 2. Contents •  IntroducEon   •  Method   –  Method  to  divide  the  topic  map   –  VIEW   –  Access  control  system     •  Experiment   •  Result  &  Discussion   •  Conclusion 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 2
  • 3. Topic  Map  Database •  A  topic  map  database  should  provide  an  efficient   method  to  process  data  (e.g.  retrieval,  update).   30  /  9  /    2010 External  Schema  of  Topic  Map  Database Update Retrieval Topic  map 3
  • 4. External  Schema •  In  order  to  limit  user  access  to  a  part  of  some  topic   map,  it  is  desirable  that  the  database  has  external   schema.   –  e.g.)  privacy,  violent  content 30  /  9  /    2010 External  Schema  of  Topic  Map  Database Accessible 4
  • 5. External  schema  of  relaEonal  databases •  RelaEonal  databases  (RDB)  provide  us  with  an  external   schema,  VIEW.   30  /  9  /    2010 External  Schema  of  Topic  Map  Database Original  relaEon VIEW projecEons  and     selecEons Users  can  access  the  VIEW  as  if  it  is  a  table,  since  the  VIEW  has   the  same  structure  as  the  original  table.   5
  • 6. External  schema  of  topic  maps •  We  can  regard  the  substructure  of  topic  maps  as  a   topic  map.   •  Therefore,  we  can  expect  that  it  is  possible  to  realize   the  external  schema  of  topic  maps  by  defining  the   substructure. 30  /  9  /    2010 External  Schema  of  Topic  Map  Database View 6
  • 7. ObjecEve  of  our  study 30  /  9  /    2010 External  Schema  of  Topic  Map  Database We  implement  the  VIEW  to  the  topic  map   database.   –  In  order  to  define  a  VIEW,  we  propose  the  method  to   specify  the  substructure  of  a  topic  map.   –  We  also  propose  the  way  to  realize  the  funcEon  to  access   the  VIEW. 7
  • 8. The  method  to  divide  the  topic  map •  In  order  to  divide  the  topic  map  into  substructures,   we  employed  a  network  clustering  technique  as  an   example  to  define  substructure.   –  We  regard  topics  and  associaEons  as  nodes  and  edges.   –  We  can  specify  a  group  of  topics  connected  to  each  other.   30  /  9  /    2010 External  Schema  of  Topic  Map  Database 8
  • 9. Clustering  syntax •  We  implemented  clustering  syntax.   –  The  query  in  this  syntax  returns  all  topics  that  belong  to   the  cluster  including  an  input  topic  as  a  parameter.   –  The  VIEW  is  realized  by  appending  this  syntax  to  predicates   in  query  as  is  done  to  realize  VIEW  in  RDB.   30  /  9  /    2010 External  Schema  of  Topic  Map  Database topicA cluster(topicA)? 9
  • 10. •  We  realized  VIEW  by  adding  the  cluster  syntax  to   predicates  in  a  given  query.         Views 30  /  9  /    2010 External  Schema  of  Topic  Map  Database topic-­‐name($TOPIC,  $NAME)? topic-­‐name($TOPIC,  $NAME)  AND  cluster(topicA)? User’s  query Append  ‘AND’  operaEor  and  cluster  syntax AND 10
  • 11. Access  control  system •  We  implemented  the  funcEon  to  access  the  VIEW  as  an  access   control  system.   •  For  the  access  control  system,  we  use  following  informaEon.   –  User  list   •  User  Name   •  Password   •  User  ID   •  Group  ID   –  Authority  list   •  ID  (User  ID  /  Group  ID)   •  ObjecEve  syntax   •  Predicate 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 11
  • 12. Flow  of  access  control  mechanism 30  /  9  /    2010 External  Schema  of  Topic  Map  Database User  Name   Password User  ID Group  ID User  A aaaa 1 100 User  B bbbb 2 200 ID Objec6ve  syntaxes Predicates 1 topic-­‐name cluster(topicA)? 200 topic-­‐name cluster(topic1178)? User  list Authority  list User  Name:  ‘User  A’   Password:  ‘aaaa’ Query:   topic-­‐name($TOPIC,$NAME)? User  ID:  1   Group  ID:  100 topic-­‐name($TOPIC,$NAME)          AND  cluster(topicA)? 12
  • 13. DemonstraEon  of  the  VIEW  and  the   access  control  funcEon •  In  order  to  demonstrate  the  VIEW  and  the  access   control  funcEon.   –  Query:        topic-­‐  name($TOPIC,  $NAME)?   –  User:      a  user  without  access  limitaEon  (User  A)      a  user  with  access  limitaEon  access  (User  B)   30  /  9  /    2010 External  Schema  of  Topic  Map  Database 13
  • 14. The  result  returned  to  the  use  without   access  limitaEon  (User  A) Input  your  user  name  and  password   User  name:  User  A     Password:  aaaa     You  succeeded  to  access  database     Select  Topic  Maps:  queryTM(Poke.db4o.pokmeonTM)     Query:  topic-­‐name($TOPIC,  $NAME)?   Row:  174    $TOPIC  =  bulbasaur      $NAME  =  bulbasaur    $TOPIC  =  ivysaur      $NAME  =  ivysaur      $TOPIC  =  venusaur      $NAME  =  venusaur          .            .        .            .        .            .    $TOPIC  =  monster      $NAME  =  monster    $TOPIC  =  pokemon      $NAME  =  pokemon    $TOPIC  =  instance-­‐of    $NAME  =  instance-­‐of   30  /  9  /    2010 External  Schema  of  Topic  Map  Database UserA  can  extract     all  topics  and     their  names. 14
  • 15. The  result  returned  to  the  use  with   access  limitaEon  (User  B) Input  your  user  name  and  password   User  name:  User  B     Password:  bbbb     You  succeeded  to  access  database     Select  Topic  Maps:  queryTM(Poke.db4o.pokmeonTM)     Query:  topic-­‐name($TOPIC,  $NAME)?   Row:  10    $TOPIC  =  raichu      $NAME  =  raichu    $TOPIC  =  picachu      $NAME  =  picachu    $TOPIC  =  magnemite    $NAME  =  magnemite    $TOPIC  =  magneton    $NAME  =  magneton    $TOPIC  =  voltorb      $NAME  =  voltorb    $TOPIC  =    electrode      $NAME  =  electrode    $TOPIC  =    jolteon      $NAME  =  jolteon    $TOPIC  =  electric      $NAME  =  electric    $TOPIC  =  electabuzz    $NAME  =  electabuzz    $TOPIC  =  zapdos        $NAME  =  zapdos   30  /  9  /    2010 External  Schema  of  Topic  Map  Database UserB  can  extract     only  topics  and     their  names  in   the  cluster. 15
  • 16. Experiment •  We  evaluated  the  increase  of  execuEon  Eme  caused   by  the  addiEon  of  access  control  procedures   –  using  following  two  topic  maps.   30  /  9  /    2010 External  Schema  of  Topic  Map  Database Pokemon  topic  map Large-­‐scale  random  topic  map Topic 174 2,998 Base  name 174 2,998 AssociaEon 432 9,118 Role 864 18,236 Occurrence 172 0 16
  • 17. Verifying  affect  of  execuEon  Eme •  (As  an  example)  we  used  the  typical  query:   –  ‘topic-­‐name($TOPIC,  $NAME)?’.     •  We  calculated  the  average  execuEon  Eme  of  100   trials  under  the  following  condiEons:     –  query  execuEon  without  access  control   –  execuEon  of  queries  submiked  by  user  without  access   limitaEon   –  execuEon  of  queries  submiked  by  user  with  access   limitaEon 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 17
  • 18. Average  execuEon  Eme 3,580.00   1,717.19   3,579.76   1,696.60   3,293.59   1,488.61   0   1,000   2,000   3,000   4,000   Large-­‐scale  random  topic   map   Pokemon  topic  map   Without  access   control   User  without   access  limitaEon   User  with  access   limitaEon   ms 30  /  9  /    2010 External  Schema  of  Topic  Map  Database The  user  authenEcaEon  does  not  affect  the  execuEon  Eme   for  a  topic  map  that  has  up  to  3,000  topics. 18
  • 19. Conclusion •  We  proposed  a  method  to  create  VIEW.   –  We  proposed  the  cluster  syntax  to  specify  a  substructure   of  topic  map.   –  By  appending  the  ‘AND’  operator  and  the  cluster  syntax  to   the  given  query,  we  realized  the  external  schema  (VIEW)  of   topic  maps.   –  We  also  implemented  the  funcEon  to  access  the  VIEW. 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 19
  • 20. Conclusion •  We  confirmed  that  there  is  only  small  increase  on   execuEon  Eme  caused  by  the  addiEon  of  the  access   control  mechanism     –  for  topic  maps  that  have  up  to  3,000  topics. 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 20
  • 21. PerspecEve •  We  will  study  the  way  to  realize  inserEon  and   deleEon  operaEons  to  the  VIEW.     •  It  is  necessary  to  discuss  the  way  to  define  the   substructure  of  topic  maps  other  than  method  based   on  clustering  technique.   30  /  9  /    2010 External  Schema  of  Topic  Map  Database 21
  • 22. Thank  you  for  your  akenEon! 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 22
  • 23. References 1.  Yuki  Kurabara,  Takeshi  Hosoya,  Masaomi  Kimura:  TOME:  Topic  Maps   Database  Extended.  The  4th  South  East  Asian  Technical  University   ConsorEum  (SEATUC)  Symposium.  pp.245—248  (2010)   2.  Versant  CorporaEon:  db4objects,  hkp://www.db4o.com/   3.  Joerg  Reichardt,  Stefan  Bornhold  :  StaEsEcal  mechanics  of  community   detecEon,Physical  ReVIEW  E,  vol.  74,  016110,  pp.1-­‐-­‐14  (2006)     4.  Pokemon  Topic  Map,hkp://www.ontopia.net/omnigator/models/ topicmap_complete.jsp?tm=pokemon.ltm   5.  WANDORA,  hkp://www.wandora.org/   6.  Motomu  Naito:  An  IntroducEon  to  Topic  Maps.  Tokyo  Denki  University   Press(2006)   7.  Ontopia:  tolog  Language  tutorial,  hkp://www.ontopia.net/   8.  ISO/IEC  JTC1/SC34,  Topic  Map  –  Data  Model,hkp:// www.isotopicmaps.org/sam/sam-­‐model/ 30  /  9  /    2010 External  Schema  of  Topic  Map  Database 23

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