SONet (Scientific Observations Network) and OBOE (Extensible Observation Ontology):

1. SONet (Scientific Observations Network) and OBOE (Extensible Observation Ontology): Facilitating data interoperability within the environmental and ecological sciences through advanced semantic approaches Mark Schildhauer, Director of Computing National Center for Ecological Analysis and Synthesis Univ. Calif, Santa Barbara TDWG 2008, Fremantle AU Oct. 19-25

2. Motivation An oncoming deluge of ecological data…

3. Motivation • And locating desired information is already quite difficult… …Why is this?

4. Motivation • Ecological data are highly heterogeneous… • Variable syntax (csv, xls), • Structures (tables, rasters, hierarchical) • Semantics (terminology, units, methods) • Derived from many disciplines: genomic, cellular, physiology, morphology, biodiversity, populations, communities, ecosystems • Need for abiotic data too: hydrology, geospatial, climatology

5. Our Semantic Approach • Climbing the semantic ladder: Ontologies Semantic Annotations Metadata Data

6. Our Semantic Approach • Method for linking elements of data objects (e.g., columns in a table) to consistent and potentially rich sets of concepts • Semantic Annotations link EML attributes to concepts defined in a Formal Ontology • Store and retrieve annotations and ontologies in Metacat

7. Document Relationships (semantic annotation)

8. OBOE Quick Overview • Extensible Observation Ontology (OBOE) • Based on the assumption that much of scientific data consists of observations • OBOE provides a high-level abstraction of scientific observations and measurements • Enables data (or metadata) structures to be linked to domain-specific ontology concepts

9. OBOE– Extensible Observation Ontology Slide from Josh Madin

10. Observation Based Structured Query • Both datasets contain “tree lengths” • Annotation search for “tree length” would return both datasets • Structured search allows the search to be limited by the observed entity (e.g. a tree or a tree branch) • Increase precision and recall

11. Emerging Observational Data Models

12. SONet: A Community-Driven Scientific Observations Network to achieve Semantic Interoperability of Environmental and Ecological Data Project Organizers Mark Schildhauer1, Shawn Bowers2, Corina Gries3, Deborah McGuinness4, Philip Dibner5, Josh Madin6, Matt Jones1, Luis Bermudez7, John Graybeal7 1NCEAS UC Santa Barbara, 2UC Davis Genome Center3CAP/LTER and Univ. of Arizona, 4McGuinness Associates,5OGC Interoperability Institute, 6Macquarie University, 7Monterey Bay Aquarium Research Institute

13. Motivation MANY different “semantic” efforts underway in earth/biodiversity/environmental sciences, all converging on use of OBSERVATIONAL data construct SPECIALIZED needs and concerns of different domains may drive semantic technology solutions to be diverse and incompatible OPPORTUNITY exists for communicating and coordinating among different domains to achieve greater interoperability of emerging semantic technology solutions BENEFIT is providing cross-disciplinary scientists with more seamless and powerful access to a broad range of relevant data and information

14. Objectives of SONet Broad Objectives • Address semanticinteroperability issues in environmental and ecological data [sharing, discovery, integration] • Build a network of practioners (SONet), including domain scientists, computer scientists, and information managers • Build generic, cross-disciplinary data interoperability solutions • Immediate Goals to Develop • An extensible and open observations data model to unify existing domain-specific approaches • A semantic (ontology) framework for scientific terminology, and corresponding domain extensions • Demonstration prototypes using these to address current interoperability issues

15. Working Groups • Subgroup 1 • Collect interoperability requirements • Define common, unified data model • Engage tool & data providers, data consumers • Subgroup 2 • Identify and catalog common observation types (semantics) • Engage data providers and information managers • Subgroup 3 • Define general extension ontologies of scientific terms • Focus work on outputs of group 2 • Engage range of domain scientists • Subgroup 4 • Define and prototype demonstration projects • Ensure compatability of subgroups Subgroup 1: Core Data Model for Observations Subgroup 2: Catalog of Common Field Observations Subgroup 4: Demonstration Projects Core SONetTeam Subgroup 3: Scientist-Oriented Term Organization • Each group consists of two team leads • Postdoc funded to work on demonstration projects & help ensure compatibility across subgroups

16. Workshops & Outreach • Community workshops … to bring together project members, data managers, domain scientists, computer scientists, and members of the larger environmental informatics community • Workshop 1: Collect detailed requirements and use cases for each SONet subgroup • Workshop 2: Refine and extend use cases; Discuss and evaluate proposed data models and representations • Workshop 3: Present and discuss refined data models and representations; early evaluation and feedback • Workshop 4: Training; discuss and plan SONet sustainability … continue from prior NSF workshop on observation data models … approximately 20-25 participants at each workshop

17. Initial Project Timeline • Workshops and meetings: Year 1: first community workshop, project meeting Year 2: second community workshop, project meeting Year 3: last two community workshops, including training • Project has just recently officially started Community Workshop (4)(training, sustainability) Community Workshop (1)(requirements & use cases) Community Workshop (2)(use cases & modeling) Community Workshop (3) (modeling & refinement) Project Leaders Meeting (1) (orientation & planning) Project Leaders Meeting (2) (evaluation & planning) Year 1 Year 2 Year 3 setup project mgmt. infrastructure, Postdoc hiring finalize community participants, meeting preparation document results, begin implementation & interoperability tests, setup network website document results, continue impl. & interop. tests continue impl. & interop. tests, meeting preparation finalize impl. & interop. tests, sustainability planning document results, execute plan for sustainability

18. Observation standards for review

19. Opportunity for Collaboration • TDWG community interests and SONet? • Observations and Specimen Records Interest Group • Observations Task Group • Contact Steve Kelling (OSR); Matt Jones (Observations Task Group) • Biological Descriptions Interest Group (SDD)