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Semantic data integration proof of concept

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  • 1. Semantic Data Integration I6 Core Group Nic Bertrand Herbert Schentz LTER-Europe Conference, Mallorca, Dec. 2008
  • 2. Overview ■Testing goals ■Test Architecture ■Results ■Outlook: Applicability for LTER-Europe
  • 3. Architecture Goal: Enable seamless access to distributed data Allow local data analysis for all members with their own tools Distributed Distributed Socio-Ecological Data mining Data with local tools Portal See all data as if it came from ONE Data Source
  • 4. Longer term vision Extend seamless access to distributed services (SOA) Allow local data analysis for all members with their own tools and common services Distributed Distributed Data Mining Socio-ecological With local tools Data Distributed Applications See all data as if data came from ONE Data Source processed within ONE application
  • 5. Role of Ontology SERONTO common concepts and structures Portal Distributed Socio- Distributed Data Ecological Data Mining with local tools SERONTO: basis to discover, retrieve and integrate distributed heterogenous data
  • 6. Testing... Why? ■To validate the use of SERONTO for data integration of ALTER-Net and LTER Europe ■Test the feasibility of mapping REAL ecological data to SERONTO ■Test the querying of the connected database(s) from the semantic concepts in SERONTO
  • 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 2835 floodplain More about the databases: Independently developed, Pythia Not developed for the purpose of data vegetation integration JOKL Different data models cultural Different languages landscapes Similar data types collected in ALTER-Net, Some obvious integration points ECN Summary (e.g. Vegetation) Database JODI vegetation SERONTO
  • 9. Data Integration using SERONTO Connect Databases Import Ontology SERONTO Query Results
  • 10. Getting value sets back SERONTO parameter method parameter_method Value_sets Unit Scale
  • 11. Data Integration Results ➢ Import SERONTO and Units Ontologies into Ontostudio SERONTO
  • 12. Data Integration Results import diverse ecological databases 2835 floodplain Pythia vegetation ECN Summary Database JOKL cultural landscapes JODI vegetation 12
  • 13. Data Integration Results Extend SERONTO Classes (SERONTO Core does not Using the content of the databases 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 13
  • 14. Open Questions <?xml version=quot;1.0quot; encoding=quot;UTF-8quot;?> <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 --> SERONTO <!-- The following <rule></rule> encodes this fact (taken from the F-Logic JACM paper, page 7): bob[name -> quot;Bobquot;; age -> 40; affiliation -> cs1[dname -> quot;CSquot;; mngr -> bob; Core assistents -> {john, sally}] this encoding writes only elementary molecules --> <rule> <head> <molecule> <object> <constant name=quot;bobquot;/> </object> <superclass isaType=quot;:quot;> Databases <class> <constant name=quot;emplquot;/> </class> </superclass> <methodSpec arrow=quot;->quot;> <name> <constant name=quot;namequot;/> </name> ? <result> <oid> <constant name=quot;quot;Bobquot;quot;/> </oid> </result> domain ontologies Query Portal Performance
  • 15. Possible uses for LTER Europe SERONTO & Domain Ontologies common concepts and domain knowledge Portal Distributed Socio- Distributed Data Ecological Data Mining with local tools Seamless access... Ready for use now