1. Semantic Integration of Ecological Data Using the SERONTO Ontology
Nicolas Bertrand1, Herbert Schentz2, Bert Van der Werf3, Barbara Magagna2, Johannes Peterseil2, Sue Rennie1,
Centre for Ecology and Hydrology (UK), Umweltbundesamt (Austria), ALTERRA (Netherlands)
Introduction Proof of Concept F-Logic / OntoStudio
JOKL ECN
•F-Logic is an object oriented database language capable of
cultural Summary
landscapes Database expressing semantic queries.
ALTER-Net is a network of excellence for Long-Term Biodiversity, Ecosystem and Awareness Research spanning •OntoStudio is an ontology management system that can use F-Logic
24 institutions in 7 European countries. The aim is to develop an integrative research framework in biodiversity to connect databases (Oracle, MS-SQL, DB2, MySQL), Excel tables
research and monitoring to address biodiversity issues at a European scale. and folder structures of the file system
JODI 2835 Pythia •OntoStudio can import OWL ontologies into F-Logic.
A key objective is the development of a framework for distributed data, information and knowledge management. foodplain •F-Logic can then be used to query the connected systems
vegetation vegetation
The major challenge in achieving this objective is the provision of consistent data access and querying across •F-Logic differs significantly to OWL Description Logic (Closed World
multiple institutions and diverse data types. semantics vs Open World semantics)
Semantic approaches to data integration are seen as an enabling mechanism to carry out integrated socio-
ecological science at a global scale. The Socio-Ecological Research and Observation oNTOlogy (SERONTO) has Connect Databases
been developed building upon Umweltbundesamt’s (Federal Environment Agency – Austria) experiences in
developing a semantic database system for managing environmental data.
To validate the development of SERONTO and its uses for future data integration, a proof of concept study was
conducted.
Import
SERONTO
List of parameters
Scope
The scope of the proof of concept was to test:
• The feasibility of mapping relational databases to SERONTO
• Querying of the connected database(s) from the semantic concepts captured in SERONTO
SERONTO
The requirements for accepting the proof of concept were: Results
• The databases must have different structures and must have been developed independently of SERONTO; Query
• 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 Results
of species occurrences, measurement of biotic and abiotic components). •We could import SERONTO and Units Ontologies into Ontostudio 100
•We could import Database Schemata into Ontostudio 50
•We could do simple and complex database queries 0
SERONTO
•We could readily extend SERONTO classes from the contents of databases Region 1 Region 2
•We could map databases to SERONTO graphically where relations between parameter method
tables and concepts where appropriate
•We could create more complex mappings including at instance level using the parameter_method
Socio-Ecological Research and Observation Ontology F-Logic syntax
•We could query multiple connected databases from SERONTO
Value_sets Unit
Scale
Key Concepts in SERONTO
What is SERONTO?
SERONTO is a core ontology for ecological observations and Outlook
measurements
SERONTO allows to annotate WHAT is observed WHERE,
WHEN and HOW
SERONTO allows to annotate how the investigation items
were SELECTED from populations
SERONTO & Domain Ontologies
common concepts
and domain
Outstanding questions
knowledge
•Can SWRL / F-Logic be used interchangeably?
SERONTO is extended by DOMAIN Ontologies •Mapping of an OWL ontology sub property
SERONTO integrates reference lists Portal •Governance of global and local reference lists
Distributed Data
SERONTO has a versioning system Distributed Socio-
Ecological Data Mining •Mapping requires knowledge of the connected database, ontology and F-
with local tools
Logic. Effort involved is significant.
•Maintenance of mappings between reference lists is crucial
•Coupling of value sets and units as well as calculations must be further
Discover, retrieve and integrate data tested.
•Dealing with Globally Unique Identifiers
More information is available on the ALTER-Net I6 Wiki:
http://www5.umweltbundesamt.at/ALTERNet/index.php?title=Main_Page