1. McGuinness Geon 5/5/2005 SOLAR-TERRESTRIAL ONTOLOGIES (for VSTO and Beyond) Peter Fox 1, Deborah McGuinness 3, Don Middleton 2, Stan Solomon 1, Jose Garcia 1, Luca Cinquini 2, Patrick West 1, James Benedict 3 1 High Altitude Observatory, NCAR 2 Scientific Computing Division, NCAR 3 McGuinness Associates Partially funded by NSF (Computer and Information Science and Engineering (CISE) in the Shared Cyberinfrastructure (SCI) division)

2. McGuinness Geon 5/5/2005 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

3. McGuinness Geon 5/5/2005 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

4. McGuinness Geon 5/5/2005 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.

5. McGuinness Geon 5/5/2005 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

6. McGuinness Geon 5/5/2005 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, …

7. McGuinness Geon 5/5/2005 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

8. McGuinness Geon 5/5/2005 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

9. McGuinness Geon 5/5/2005 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… *based on AAAI ’99 Ontologies panel – McGuinness, Welty, Ushold, Gruninger, Lehmann

10. McGuinness Geon 5/5/2005 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 http://www.w3.org/2004/Talks/0412-RDF-functions/slide4-0.html

11. McGuinness Geon 5/5/2005 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

12. McGuinness Geon 5/5/2005 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.

13. McGuinness Geon 5/5/2005 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

14. McGuinness Geon 5/5/2005 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

15. McGuinness Geon 5/5/2005 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?

16. McGuinness Geon 5/5/2005 More Information Virtual Solar Terrestrial Observatory (VSTO): http://vsto.hao.ucar.edu Semantic Web for Earth and Environmental Terminology (SWEET): http://sweet.jpl.nasa.gov Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR): http://cedarweb.hao.ucar.edu Center for Integrated Space Weather Modeling (CISM): http://www.bu.edu/cism Mauna Loa Solar Observatory (MLSO): http://mlso.hao.ucar.edu W3C’s Web Ontology Language (OWL) - http://www.w3.org/TR/owl-features/ Peter Fox pfox@ucar.edu Deborah McGuinness dlm@ksl.stanford.edu See the Poster !!!