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Interoperability ~ An Introduction

Interoperability ~ An Introduction. Cyndy Chandler Biological and Chemical Oceanography Data Management Office (BCO-DMO) Woods Hole Oceanographic Institution 26 July 2008 OOS Interoperability Planning Workshop

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Interoperability ~ An Introduction

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  1. Interoperability ~An Introduction Cyndy Chandler Biological and Chemical Oceanography Data Management Office (BCO-DMO)Woods Hole Oceanographic Institution26 July 2008OOS Interoperability Planning Workshop National Space Science and Technology CenterUniversity of Alabama at Huntsville, AL USA slide 1 of 21

  2. Discussion Points • What do we mean by “interoperability”? • Why does it matter? • How do we achieve interoperability? • What are some of the expected challenges and effective strategies? slide 2 of 21

  3. slide 3 of 21

  4. What do we mean by “interoperability”? • the ability to exchange data and information between two or more systems (separated by a recognized boundary) with minimal loss of information • clients of interoperable systems may be machines • syntactic interoperability • file formats • data structures • exchange protocols • semantic interoperability • term definitions (controlled vocabularies) slide 4 of 21

  5. Interoperability . . . a wee bit more from MMI • a client should not be required to possess in depth understanding of the data in order to access them • interoperable systems should be designed to support machine access (not just people clients) • interoperable metadata systems should be designed to support automated, accurate, lossless, machine-to-machine exchange of information slide 5 of 21

  6. Why does interoperability matter? • improved open access to public data • enabling data mining, cataloging systems, portals, mash-ups • ecosystem researchers are asking global questions • model developers need access to data from a variety of domains (biology, chemistry, etc and social and economic data too) • we must rise to the challenge of designing interoperable data systems that are up to these tasks slide 6 of 21

  7. How do we achieve interoperability? What are some of the expected challenges? • varied funding sources and governing agencies • projects with different priorities and leadership • distributed data systems • large volume, heterogeneous data • expectation of near real-time availability slide 7 of 21

  8. * What are some of the effective strategies? • adopt standards • use controlled vocabularies • publish metadata databases • use Semantic Web technologies • build community slide 8 of 21

  9. This is going to be difficult . . . • best solutions will be found through community recognition of local implementations • Baker & Chandler, in press. publication expected in DSR II before end of 2008.Title: Enabling Long-Term Oceanographic Research: Changing Data Practices, Information Management Strategies and Informatics online:  http://dx.doi.org/10.1016/j.dsr2.2008.05.009final draft complete: 9-JUL-2008 slide 9 of 21

  10. * The data … controlled vocabularies community buildingmetadatastandards CMarZGEOTRACESIron SynthesisNACPOCBUS GLOBECUS JGOFSUS SOLAS slide 10 of 21

  11. Ocean Observatory Data … • expecting large volume, heterogeneous data to be made available in near real time • in the past, large volume data sets tended to be more homogeneous (e.g. fewer columns); while data sets with many columns tended to be smaller in sizeHomogeneous HeterogeneousSensor data Manual observationsPhysical Biology, ChemistryData from ocean observatory sensor arrays are/will be a continuous stream of large volume, heterogeneous data. slide 11 of 21

  12. * Ocean Observatory Data … • attempting to reduce this challenge by • identifying 20 IOOS core variables • recognizing the importance of metadata • identifying common use cases • adopting common standards (OGC and SWE) • fostering community-wide involvement and communications • sponsoring mysterious, after-dark gatherings in Huntsville, AL providing little more information beyond street address and suggested footwear . . . slide 12 of 21

  13. Semantic Web • Semantic Web technologies offer one solution setnext four slides are courtesy of Peter Fox (HAO/ESSL/NCAR) and are from an April 2008 presentation slide 13 of 21

  14. Semantic Web Basics • The triple: {subject-predicate-object} Interferometer is-a optical instrument Optical instrument has focal length An ontology is a representation of this knowledge • W3C is the primary (but not sole) governing organization for languages, specifications, best practices, etc. • RDF - Resource Description Framework • OWL 1.0 - Ontology Web Language (OWL 1.1 on the way) • Encode the knowledge in triples, in a triple-store, software is built to traverse the semantic network, it can be queried or reasoned upon • Put semantics between/ in your interfaces, i.e. between layers and components in your architecture, i.e. between ‘users’ and ‘information’ to mediate the exchange (P. Fox, 2008) slide 14 of 21

  15. Added value Education, clearinghouses, other services, disciplines, etc. Semantic interoperability Added value Added value Semantic query, hypothesis and inference Semantic mediation layer - mid-upper-level Added value * VO API Web Serv. VO Portal Query, access and use of data Mediation Layer • Ontology - capturing concepts of Parameters, Instruments, Date/Time, Data Product (and associated classes, properties) and Service Classes • Maps queries to underlying data • Generates access requests for metadata, data • Allows queries, reasoning, analysis, new hypothesis generation, testing, explanation, etc. Semantic mediation layer - VSTO - low level Metadata, schema, data DBn DB2 DB3 … … … … DB1 (P.Fox, 2008) slide 15 of 21

  16. Semantic Web Methodology and Technology Development Process • Establish and improve a well-defined methodology vision for Semantic Technology based application development • Leverage controlled vocabularies, etc. Adopt Technology Approach Leverage Technology Infrastructure Science/Expert Review & Iteration Rapid Prototype Open World: Evolve, Iterate, Redesign, Redeploy Use Tools Analysis Use Case Develop model/ontology Small Team, mixed skills (P. Fox, 2008) slide 16 of 21

  17. The Information Era: Interoperability Modern information and communications technologies are creating an “interoperable” information era in which ready access to data and information can be truly universal. Open access to data and services enables us to meet the new challenges of understanding the Earth and its space environment as a complex system: • managing and accessing large data sets • higher space/time resolution capabilities • rapid response requirements • data assimilation into models • crossing disciplinary boundaries. (P. Fox, 2008) slide 17 of 21

  18. Semantic Web technologies being used in some of Peter Fox’s informatics projects: • Semantically-Enabled Science Data Integration (SESDI): http://sesdi.hao.ucar.edu • Semantic Knowledge Integration Framework (SKIF): http://skif.hao.ucar.edu • Semantic Web forEarth and Environmental Terminology (SWEET): http://sweet.jpl.nasa.govSWEET is a JPL project to provide a common semantic framework for a variety of Earth science initiatives. slide 18 of 21

  19. * more challenges . . . • reality check: insufficient metadata … researcher aboard R/V Oceanus, August 2008, talking about metadata for shipboard sampling "I feel like I'm so busy with all the other little things in a cruise that I don't have time to worry about making up log sheets. But if someone puts an already made log sheet in front of me, I'll use it." "When I see projects with good metadata, it just makes my heart go pitter patter." Data originators recognize that recording metadata is a good idea, and they will even record metadata ~ if we make it easy for them to do so. slide 19 of 21

  20. more challenges . . . • reality check: heterogeneous data sets … The BCO-DMO database includes many data sets in which depth and temperature are reported and more than 25 different definitions of each. slide 20 of 21

  21. Community building • Share knowledge gained doing implementation at the local level – participate in workshops and publish • Fall 2008 AGU Meeting in San Francisco, CA8-12 December; Earth and Space Science InformaticsIN12: Strategies for Improved Marine and Synergistic Data Access and Interoperability IN19: From Data to Synthesis: Next-Generation Science ApplicationsAbstract Submission Deadline: 10 September 2359 UT Thank you . . . cchandler@whoi.edu * slide 21 of 21

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