1. Why are Ontologies Important ? Luis Bermudez QARTOD III November 2-4, 2005

2. Ontology-Philosophy “ Most fundamental branch of metaphysics. It studies being or existence as well as the basic categories thereof—trying to find out what entities and what types of entities exist. ” - Wikipedia

4. “ Because any ontology is, among other things, a social / cultural artifact, there is no purely objective perspective from which to observe the whole terrain of concepts. Instead of asking, “what hierarchical representation of concepts best captures the universal relationships among general ideas,” it is more productive to ask “what specific purpose do we have in mind for this conceptual map of entities and what practical difference will this ontology make? ” -Wittgenstein, Tractatus Logico-Philosophicus.

6. SWEET Ontologies http://sweet.jpl.nasa.gov/ontology/ Earth Realms Physical Phenomena Physical Processes Physical Properties Physical Substances Sun Realms Biosphere Data Data Centers Human Activities Material Things Numerics Sensors Space Time Units

7. Ontologies - Computer Science Specification of conceptualizations Body of Water Class RiverLake Has water Is inland body Has a relative defined channel LakeRiver Example: 1. Properties of real world objects are identified. 2. Similarities are identified. 3. Concepts are created 4. and are expressed as a class. 5. Classes are related. Subclass

8. Hydrologic Unit RegionSubregionAccounting Unit Cataloging Unit Is part of Mid Atlantic Delaware Lower Delaware Schuylkill Is part of Subclasses Is Transitive Infer isPartOf Class Looks like a Real world objects Instances

9. What is an Ontology? Catalog/ ID General Logical constraints Terms/ glossary Thesauri “narrower term” relation Formal is-a Frames (properties) Informal is-a Formal instance Value Restrs. Disjointness, Inverse, part- of… Deborah McGuinness

10. Why Ontologies To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge Cartic Ramakrishnan LSDIS Lab, University of Georgia

11. Why do we have a presentation about ontologies in a QARTOD meeting ?

12. Do we need to share explictly QARTOD concepts ? Quality Levels Flags Sensors Instrument Methodology Calibration procedures QC software procedures Methods of verification and validation Methods for manual checking Malfunctions

13. WHP CTD data quality codes WMO IGOSS observation quality codes Can we state this explictly ?

14. MMI and ontologies

15. Semantic Issues Search for sea temperature data Sea surface Temperature sea_water_ temperature TEMP BODC GCMD CF Don’t sure what data will get retrieved ? Ocean Temperature GCMD

16. Solving semantic issues

17. Harmonization DTD CommaSeparatedValues HTML TabSeparatedValues RelationalDatabase XML/XSD RDF OWL

18. Web Ontology Language: OWL W3C Recommendation 02/04. Based on RDF. (-> URI ) Inference capabilities. Restriction of inherit properties. Can be used to express specifications and vocabularies Body of Water River

19. Domain Ontologies Repository

20. VOC2OWL

21. VINE Vocabulary Integration Environment

22. Community role

23. Mapping Results

25. http://marinemetadata.org

26. Data Source Data Provider Data User gets processes: formats/archives publishes gets processes: uses/analyzes sends gets processes: formats/archives sends Ingests from instruments

27. About MMI MMI = Marine Metadata Interoperability Initiative. NSF funded and SURA (Southeastern Universities Research Association) supported. Initially one year project (September 2005). In the process of getting extended (NOAA and NSF). Organization; Executive committee (5), Steering committee (17), technical committee(~25), and contributors. Community of more than 200 members (October 2005). Deliverables: –Community web site with metadata content, guidance –Interoperability Demonstrations –Workshop: “Advancing Domain Vocabularies” –Tools : VINE Voc2OWL, Tethys, Web Services

28. http://marinemetadata.org/tethys 1.Implement two methods and make them available using SOAP web services.Implement 2.Convert the parameters, sources, and units used in their system to an ontology.Convert (tool VOC2OWL ascii to OWL) 3.Map the terms used in the system to the MMI preferred ontology: Standard vocabulary for discovery (GCMD) and for usage (CF).Map

29. Steering Committee Members Robert Arko, LDEO Julie Bosch, NOAA Francisco Chavez, MBARI Ben Domenico, Unidata Karen Stocks, SDSC Steve Hankin, NOAA - Ocean.US/DMAC Roy Lowry, BODC Mark Musen, Stanford Univ Michael Parke, Univ of Hawaii Lola Olsen, NASA Goddard Dawn Wright, Oregon State Univ Bob Weller, WHOI John Graybeal, MBARI. PI. (ExecComm)graybeal@mbari.org Stephanie Watson, CeNCOOS. (ExecComm)swatson@mbari.org Philip Bogden, SURA/SCOOP. (ExecComm)bogden@gomoos.org Stephen Miller, Scripps. (ExecComm)spmiller@ucsd.edu

30. National Science Foundation 1 SURA, the Southeastern Universities Research Association (http://www.sura.org),http://www.sura.org NOAA (including the Coastal Services Center), ONR, the Office of Naval Research (http://www.onr.navy.mil),http://www.onr.navy.mil OceanUS and regional IOOS systems. 1 NSF Grant ATM-0447031 Credits

31. Thank you ! bermudez@mbari.org ask@marinemetadata.org