1. Adoption of RDA-DFT Terminology and Data Model to the Description and Structuring of Atmospheric Data Aaron Addison, Rudolf Husar, Cynthia Hudson-Vitale

2. Background DataFed & the Air Quality Community Catalog Problem Addressed Facilitate data interoperability Extend data discovery to non-domain researchers

3. RDA Data Foundation and Terminology (DFT) Data Foundation & Terminology WG

4. RDA Data Foundation and Terminology (DFT) Adoption plan ●Map DFT model to DataFed/AQ Com Cat data model ●Assess potential RDA/DFT compliance ●Real-world evaluation of outcome

5. RDA Data Foundation and Terminology (DFT) Adoption Activities & Timeline: TrainingOngoing Draft DataFed data model and inventory terms and evaluate existence of PID’sMarch Virtual ServerMarch Mirror site of AQComCatMarch User testingMarch Compare DFT model to DataFed data modelMarch/April Create/assign PID’s to AQComCatApril Reboot AQCom CatMay Add new datasource to AQComCat - test understandability of terms with data suppliers.June Conduct post-DFT implementation usability of AQComCatJuly Publish paper/report on findingsAugust

6. RDA Data Foundation and Terminology (DFT) Adoption Outcomes ●Report on usability of RDA DFT model ●Assess fit of the RDA DFT model to DataFed data model ●Evaluate improved discoverability/reuse ●Engage with Data Foundation and Terminology Working Group

7. Thank you!

8. RDU - Project RDU- Compliant Catalog Current Catalog DTR Adopt, Refine RDU products

9. Interaction with RDU Groups DTR Data Type Registries WG (Register Types) PID Information Types WG (Get PID ??) DFT Data Foundation and Terminology WG (Data Model…?) DFData Fabric IG (DataFed Use Case?)

10. Data Type Registry for Sharing and Reuse We will use the RDA Type registry (L. Lannom) Registry needs to be federated… e.g. with GCMD registry

11. What is Data Typing? Data ‘typing’ is the characterization of data structure, contexts, assumptions and other info needed to describe and understand the data. The ‘types’ need to be: Defined and understood by data producers and consumers Types should have multiple levels/granularity –single observation to data sets..(how??) Each type is to have a PID Permanently associated with the data they describe Standardized (OGC, ISO), unique (PID), and discoverable (TypeRegistry?) Data typing should aid the discovery, understanding, sharing and reuse of data.. across domains Automated processing of large data collections is a necessity Which requires a machine readable types, i.e. a clear data model for typing (clarify ???) ‘Composability’: lower level/base types can form more complex composite types (how???)

12. Global Change Master Directory (GCMD) Extensive collection of keywords and UUID’s; Possible use for ‘Types’ Do we combine it with AQ ComCat Types? Any other registries to federate?GCMD The GCMD/IDN release Version 8.1 of the GCMD/IDN Science Keywords. RESTFul service (API), is also available. Keyword List:GCMD/IDN Science Keywordsservice (API),Keyword List Science and Services Keywords: Category, Topic, Term, Variable, Level, Detailed, Variable, UUID Other ‘Types’ (Some are useful – to be defined formally, ID-d, in RDU Type registry : Data Centers, Projects, Instruments, Platforms, Locations, Horizontal Resolution, Vertical Resolution, Temporal Resolution, URL Content Types

13. Project Outputs and Outcomes, Next Steps Outputs: Develop a data model for suitable for describing atmospheric data Identify basic and composite types for atmospheric data Register these types in DTR Attach ‘types’ to data in DataFed Type-based search interface to DataFed data. Outcomes Real-world testing of Typing concepts and Registry Understanding of domain-specific issues and approaches, lessons learned Interaction with multiple RDU Groups … contribution to Data Fabric Recommendations for next phase Next steps outlined ???

14. ToDo’ s Combine AQComCat, GCMD, Other ‘keywords’/facets/ Formally define ‘RDU Types – Names, descriptions’, Get PIDs Check, reconcile types with concepts of DTR, PID, DFT WGs – is it OK? Register Types in Type Registry Incorporate Type-based metadata into AQComCat Test catalog usability before, after

15. CF - Climate & Forecast Conventions GCMD Instruments GCMD Platform GCMD Temp Res GCMD Keywords Observation (Parameter) Currently, neither the Observations, nor the Attributes are uniquely defined Some metadata standards and conventions already exist – but can not be forced to RDA ‘standardized’ Need ‘wrapper’ and ‘adopter’ components to harmonize and integrate metadata Attributes (Facets) has

16. Data Type Model: Atmospheric (Earth?) Observation Parameter Name, Desc., STD/Ref. ID Earth Observation Spatial Extent LatMinMax, LonMinMax Spatial Coverage Point, Grid, Trajectory, Image Spatial Resolution 10 Km Spatial Extent TimeMin, TimeMax Time Coverage Time Resolution Year, Month, Day, Hour, Min Instrument InSitu, RemoteSens Platform Domain Distributor Data type Originator What/How Measured Where and When Data Source, Access Provenance

17. DataFed: Federated Data System DataFed System of Systems architecture is suitable for integrating data Standard data access is a key interoperability protocol Heterogeneous data can be non-intrusively standardized by mediators Service-based architecture delivers tailored products to diverse uses System of Systems architecture is suitable for integrating data Standard data access is a key interoperability protocol Heterogeneous data can be non-intrusively standardized by mediators Service-based architecture delivers tailored products to diverse uses System of Systems architecture is suitable for integrating data Standard data access is a key interoperability protocol Heterogeneous data can be non-intrusively standardized by mediators Service-based architecture delivers tailored products to diverse uses System of Systems architecture is suitable for integrating data Standard data access is a key interoperability protocol Heterogeneous data can be non-intrusively standardized by mediators Service-based architecture delivers tailored products to diverse uses

18. System of Systems architecture is suitable for integrating data Heterogeneous data can be non-intrusively standardized by mediators

19. Shared Data Pool Observ. Emission Model Satellite Monitorig Network Benefits Informing the Public Protecting Health Global Policies Atmosph. Science EOs. & Modeler EO Service Provider Discipline Scientist Health & Env. Analyst Policy & Manager Air Quality Decision Systems In the new GEOSS paradigm, EOs should be accessible from a shared virtual data pool

20. Data Sharing Infrastructure Std. Servers Emission Model Satellite Monitorig Network Data Pool Benefits Informing the Public Health Effects Climate Impact Science & Education Std. Tools User Tools DataFed Information Infrastructure DataFed is an implementation of the GEOSS data sharing paradigm DataFed also includes client applications for data browsing, exploration and analysis These flexible tools can be used on any dataset form anywhere on the Web. Adaptors