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  1. SOLAR-TERRESTRIAL ONTOLOGIES (for VSTO and Beyond) Peter Fox1, Deborah McGuinness3, Don Middleton2, Stan Solomon1, Jose Garcia1, Luca Cinquini2, Patrick West1, James Benedict3 1High Altitude Observatory, NCAR 2Scientific Computing Division, NCAR 3McGuinness Associates Partially funded by NSF (Computer and Information Science and Engineering (CISE) in the Shared Cyberinfrastructure (SCI) division) McGuinness Geon 5/5/2005

  2. Outline • Problem: • Sharing (Solar-Terrestrial) Scientific Data • Problem Setting: Virtual Observatories • Virtual Solar-Terrestrial Observatory Project • Solution Strategy: • Ontologies (providing a controlled vocabulary with unambiguous machine operational definitions) • Ontology-enabled tools • Connect /Extend /Validate complementary terminologies • Technology Status • Conclusion / Pointers McGuinness Geon 5/5/2005

  3. Background Scientists should be able to access a global, distributed knowledge base of scientific data that: • appears to be integrated • appears to be locally available But… data is obtained by multiple instruments, using various protocols, in differing vocabularies, using (sometimes unstated) assumptions, with inconsistent (or non-existent) meta-data. It may be inconsistent, incomplete, evolving, and distributed McGuinness Geon 5/5/2005

  4. Virtual Observatories Make data and tools quickly and easily accessible to a wide audience. Operationally, virtual observatories need to find the right balance of data/model holdings, portals and client software that a researchers can use without effort or interference as if all the materials were available on his/her local computer using the user’s preferred language. They are likely to provide controlled vocabularies that may be used for interoperation in appropriate domains along with database interfaces for access and storage and “smart” tools for evolution and maintenance. McGuinness Geon 5/5/2005

  5. Virtual Solar Terrestrial Observatory (VSTO) • a distributed, scalable education and research environment for searching, integrating, and analyzing observational, experimental, and model databases. • subject matter covers the fields of solar, solar-terrestrial and space physics • it provides virtual access to specific data, model, tool and material archives containing items from a variety of space- and ground-based instruments and experiments, as well as individual and community modeling and software efforts bridging research and educational use • 3 year NSF-funded project in first year McGuinness Geon 5/5/2005

  6. Content: Coupling Energetics and Dynamics of Atmospheric Regions WEB Community data archive for observations and models of Earth's upper atmosphere and geophysical indices and parameters needed to interpret them. Includes browsing capabilities by periods, instruments, models, … McGuinness Geon 5/5/2005

  7. Content: Mauna Loa Solar Observatory Near real-time data from Hawaii from a variety of solar instruments. Source for space weather, solar variability, and basic solar physics Other content used too – CISM – Center for Integrated Space Weather Modeling McGuinness Geon 5/5/2005

  8. VSTO Ontologies • Technology for encoding meaning of terms supporting interoperation across applications, education, reasoning, etc. • Beginning with common, high-leverage terminologies • ***Instruments • ***Parameters • Sun Realm … • Integrating with/extending Semantic Web for Earth and Environmental Terminology, GEON, … • Encoding in W3C’s OWL • Initial Use – Ontology-enhanced search and “smarter” portals McGuinness Geon 5/5/2005

  9. What is an Ontology? Thesauri “narrower term” relation Frames (properties) Formal is-a General Logical constraints Catalog/ ID Informal is-a Formal instance Disjointness, Inverse, part-of… Terms/ glossary Value Restrs. *based on AAAI ’99 Ontologies panel – McGuinness, Welty, Ushold, Gruninger, Lehmann McGuinness Geon 5/5/2005

  10. Semantic Web Layers Ontology Level • Language (OWL (RDF/XML compatible)) • Environments (inspired by FindUR, Chimaera, Ontolingua, OntoBuilder/Server, Sandpiper Tools, Cerebra, …) • Standards body leverage (W3C’s WebOnt, W3C’s Semantic Web Best Practices, EU/US Joint Committee, OMG ODM, Scientific Markup Standards, …) Rules • SWRL Logic • Description Logics Proof • PML, Inference Web Services and Infrastructure Trust • IWTrust McGuinness Geon 5/5/2005

  11. Instrument Class Excerpt • Radar • Incoherent Scatter • Ionospheric Doppler(aka HF) • Middle Atmosphere (aka MLT) • MST • MF • LF • Meteor Wind • Digisondes • Optical (hasBand, measuresTo, etc.) • Interferometers • Fabry-Perot • Michelson • IR • Doppler • Spectrometers • IR ([OH]) • Airglow Imagers • All-Sky Cameras • Lidar • Spectrometers • Polarimeter • Heliograph • Photometers • Single-Channel • Multi-Channel • Taxonomy of instruments • covering content areas. Currently • expanding and evaluating. • COMMENTS Welcome!!!! • Approach: • identify instruments & parameters • organize hierarchically • compare/extend SWEET (realms, properties, space, …) • scientific expert review • ontology expert review • related scientific review • populate instances (including meta-data) • use-case driven McGuinness Geon 5/5/2005

  12. Current Technology Focus • Instruments • Parameters • Meta-data • Use-Case • ** Ontology-enhanced search (initially for CEDARWEB and appropriately interconnected data portals) • What can I plot (x vs. y based on semantics) • Enhanced plotting using understanding of coordinate systems, relationships, data synthesis, transformations, etc. McGuinness Geon 5/5/2005

  13. Primary Integration Areas • Base Ontology: SWEET with extensions. This provides both validation for SWEET/GEON as well as content extensions • Virtual Observatory with its tool infrastructure • Scientific ontology-enabled search (note spectrum of options) • Meta data vocabulary, registry for instruments, data sets, etc. • Use Case Analysis McGuinness Geon 5/5/2005

  14. Conclusion I • Virtual Observatories are emerging (VSTO, Astrophysical, …) • Scientific Data Sharing is required • Ontologies can help with • Controlled vocabularies with unambiguous term meanings • Mapping/Merging support for data integration • Ontology-enhanced search • Meta-data descriptions • Consistency Checking • Completion • Structured, “surgical” comparative customized search • … • VSTO and GEON are natural/complementary partners • Communities can help each other by pooling resources over scientific ontology creation, use, evaluation, evolution, and environment development McGuinness Geon 5/5/2005

  15. Impact: Changing Science Scientists: What if you… • could not only use your data and tools but remote colleague’s data and tools? • understood their assumptions, constraints, etc and could evaluate applicability? • knew whose research currently (or in the future) would benefit from your results? • knew whose results were consistent (or inconsistent) with yours?… Funders: What if you … • could identify how one research effort would support other efforts? • (and your fundees) could reuse previous results? • (and your fundees) could really interoperate? CS: What if you had a sandbox and you … • could apply your techniques across very large distributed teams of people with related but different apps? • could compare your techniques with colleagues trying to solve similar problems? McGuinness Geon 5/5/2005

  16. More Information • Virtual Solar Terrestrial Observatory (VSTO): • Semantic Web forEarth and Environmental Terminology (SWEET): • Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR): • Center for Integrated Space Weather Modeling (CISM): • Mauna Loa Solar Observatory (MLSO): • W3C’s Web Ontology Language (OWL) - Peter Fox Deborah McGuinness See the Poster !!! McGuinness Geon 5/5/2005