The document discusses testing the use of the SERONTO ontology for semantic data integration of distributed ecological databases from ALTER-Net and LTER Europe. Five databases were independently mapped to SERONTO concepts and queries could be run across the integrated data without knowledge of the underlying database structures. However, the effort required for mapping was significant and maintaining reference lists will be crucial. More use cases are needed to fully evaluate SERONTO's potential for LTER data integration.

1. Semantic Data Integration I6 Core Group Nic Bertrand Herbert Schentz LTER-Europe Conference, Mallorca, Dec. 2008

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

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

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

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