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Semantic Data Integration I6 Core Group Nic Bertrand Herbert Schentz LTER-Europe Conference, Mallorca, Dec. 2008
Overview ,[object Object],[object Object],[object Object],[object Object]
Architecture Goal: Enable seamless access to distributed data  Allow  local  data analysis for all members  with their own tools Distributed Socio-Ecological  Data See all data as if it came from ONE Data Source Distributed  Data mining with local tools Portal
Longer term vision Distributed Applications Extend seamless access to distributed services (SOA) Allow  local  data analysis for all members  with their own tools and common services See all data as if data came from ONE Data Source processed within ONE application Distributed  Socio-ecological  Data Distributed  Data Mining With local tools
Role of Ontology  Distributed Data Mining with local tools Distributed Socio-Ecological Data SERONTO SERONTO: basis to discover, retrieve and integrate distributed heterogenous data  common concepts and structures Portal
Testing... Why? ,[object Object],[object Object],[object Object]
Proof of concept: Acceptance Criteria  •  The databases must have different structures and must have been developed independently of SERONTO; •  The databases must feature reference lists (e.g. species lists); •  The database structures must not be altered as a result of the integration work; •  New concepts may be imported into SERONTO as and when required; •  The databases must contain data relevant to Long Term Ecological Research (e.g. vegetation surveys, records of species occurrences, measurement of biotic and abiotic components).
Testing: Connecting 5 databases JOKL cultural landscapes JODI vegetation 2835 floodplain ECN Summary Database More about the databases: Independently developed,  Not developed for the purpose of data integration Different data models  Different languages Similar data types collected in ALTER-Net,  Some obvious integration points  (e.g. Vegetation) Pythia vegetation SERONTO
Data Integration using SERONTO Import Ontology Connect Databases Query SERONTO Results
Getting value sets back SERONTO parameter_method parameter method Value_sets Unit Scale
Data Integration Results ,[object Object],SERONTO
Data Integration Results import diverse ecological databases JOKL cultural landscapes JODI vegetation 2835 floodplain ECN Summary Database Pythia vegetation
Data Integration Results Extend SERONTO Classes Using the content of the databases (SERONTO Core does not  contain domain specific concepts) Map databases to SERONTO (Simple and complex mappings) Query individual databases directly Query multiple databases from the SERONTO (Simple and Complex queries) Map once, reuse data many times, querying does not require knowledge of the structures of the databases Semantic data integration is possible
Open Questions ,[object Object],[object Object],[object Object],[object Object],[object Object],SERONTO Core domain ontologies ? <?xml version=&quot;1.0&quot; encoding=&quot;UTF-8&quot;?> <flg:flogic xmlns:flg=&quot; http://www.wsmo.org/2004/d16/d16.2/v0.1/ &quot;> <!-- Test data to test the WSML F-Logic XML syntax --> <!-- The following <rule></rule> encodes this fact (taken from the F-Logic JACM paper, page 7): bob[name -> &quot;Bob&quot;; age -> 40; affiliation -> cs1[dname -> &quot;CS&quot;; mngr -> bob; assistents -> {john, sally}] this encoding writes only elementary molecules --> <rule> <head> <molecule> <object> <constant name=&quot;bob&quot;/> </object> <superclass isaType=&quot;:&quot;> <class> <constant name=&quot;empl&quot;/> </class> </superclass> <methodSpec arrow=&quot;->&quot;> <name> <constant name=&quot;name&quot;/> </name> <result> <oid> <constant name=&quot;&quot;Bob&quot;&quot;/> </oid> </result> Portal Query Databases Performance
Possible uses for LTER Europe Distributed Data Mining with local tools Distributed Socio-Ecological Data SERONTO &   Domain Ontologies common concepts and domain knowledge Portal Seamless access... Ready for use now

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Semantic data integration proof of concept

  • 1. Semantic Data Integration I6 Core Group Nic Bertrand Herbert Schentz LTER-Europe Conference, Mallorca, Dec. 2008
  • 2.
  • 3. Architecture Goal: Enable seamless access to distributed data Allow local data analysis for all members with their own tools Distributed Socio-Ecological Data See all data as if it came from ONE Data Source Distributed Data mining with local tools Portal
  • 4. Longer term vision Distributed Applications Extend seamless access to distributed services (SOA) Allow local data analysis for all members with their own tools and common services See all data as if data came from ONE Data Source processed within ONE application Distributed Socio-ecological Data Distributed Data Mining With local tools
  • 5. Role of Ontology Distributed Data Mining with local tools Distributed Socio-Ecological Data SERONTO SERONTO: basis to discover, retrieve and integrate distributed heterogenous data common concepts and structures Portal
  • 6.
  • 7. Proof of concept: Acceptance Criteria • The databases must have different structures and must have been developed independently of SERONTO; • The databases must feature reference lists (e.g. species lists); • The database structures must not be altered as a result of the integration work; • New concepts may be imported into SERONTO as and when required; • The databases must contain data relevant to Long Term Ecological Research (e.g. vegetation surveys, records of species occurrences, measurement of biotic and abiotic components).
  • 8. Testing: Connecting 5 databases JOKL cultural landscapes JODI vegetation 2835 floodplain ECN Summary Database More about the databases: Independently developed, Not developed for the purpose of data integration Different data models Different languages Similar data types collected in ALTER-Net, Some obvious integration points (e.g. Vegetation) Pythia vegetation SERONTO
  • 9. Data Integration using SERONTO Import Ontology Connect Databases Query SERONTO Results
  • 10. Getting value sets back SERONTO parameter_method parameter method Value_sets Unit Scale
  • 11.
  • 12. Data Integration Results import diverse ecological databases JOKL cultural landscapes JODI vegetation 2835 floodplain ECN Summary Database Pythia vegetation
  • 13. Data Integration Results Extend SERONTO Classes Using the content of the databases (SERONTO Core does not contain domain specific concepts) Map databases to SERONTO (Simple and complex mappings) Query individual databases directly Query multiple databases from the SERONTO (Simple and Complex queries) Map once, reuse data many times, querying does not require knowledge of the structures of the databases Semantic data integration is possible
  • 14.
  • 15. Possible uses for LTER Europe Distributed Data Mining with local tools Distributed Socio-Ecological Data SERONTO & Domain Ontologies common concepts and domain knowledge Portal Seamless access... Ready for use now