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WP-ESIP Federation Interoperability J AMES F REW University of California, Santa Barbara

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Presentation on theme: "WP-ESIP Federation Interoperability J AMES F REW University of California, Santa Barbara"— Presentation transcript:

1 WP-ESIP Federation Interoperability J AMES F REW University of California, Santa Barbara http://www.bren.ucsb.edu/~frew

2 WP-ESIP Federation Interoperability Background –CAN interoperability requirements –Federation Interoperability Working Group (FIG) Interoperability criteria –System-wide Interface Layer (SWIL) –Catalog interoperability Proposed technologies

3 CAN Interoperability Requirements Specific –Make public-domain products available on Internet –Announce products and services through GCMD –Comply with Federal standards (e.g. FGDC) Philosophy –Interoperability best resolved experimentally –Federation must decide how much

4 CAN Interoperability Requirements Process –Each ESIP proposes one of {V0, ECS, CIP, FGDC GEO, custom} as System-Wide Interface Layer (SWIL) –custom: permits the ESIP to be searched and queried as if it is part of a larger whole –Federation determines and evolves these standards and interfaces –SWIL-specific funding available

5 cluster What is the SWIL? ESIP SWIL customer A common view of the Federation that all its participants agree to support

6 SWIL Elements Online services –How you can reach us Vocabularies and models –What language(s) we speak User interfaces –What we look like

7 Federation Interoperability Working Group (FIG) May 1998 (1 st Federation meeting) –FIG established; charged with coordinating development of SWIL –Kenn Gardels elected chair Summer/Fall 1998 –Inventory relevant systems, protocols, and standards, and ESIP activities

8 FIG Timeline (contd) Dec 1998 (2 nd Federation meeting) –Endorse layered implementation strategy metadata data functions –Endorse clusters of ESIPs as bottom-up interoperability mechanism Winter/Spring 1999 –FIG tiger team prepares catalog interoperability (CI) evaluation criteria –April 1999: loss of Kenn Gardels; Yonsook Enloe acting chair

9 FIG Timeline (contd) May 1999 (3 rd Federation meeting) –CI evaluation criteria presented and approved –James Frew elected chair Summer 1999 –CI-level SWIL candidate systems solicited 4 proposals as of 13 Jul 1999 Evaluation team forming –30 Aug - 02 Sep 1999 FIG at UCLA: synthesize CI SWIL

10 Light touch –Just metadata, not data Satisfies basic requirements –GCMD –FGDC Satisfies query larger whole sub-requirement max(!/$): best chance to do something quickly –Many existing or pending alternatives Catalog Interoperability Rationale

11 Overall Criteria Allow single, multiple, or composite solutions –Multiple: must be equivalent –Composite: should be seamless Security and access control –Expose subsets of catalog information Comply with relevant standards Discover and describe services as well as data

12 Overall Criteria: Risks Maturity Acceptance –By users –By providers Support Technological change –Continue to support obsolete technologies –Migrate to newer technologies

13 Catalog Interoperability Criteria Discovery / search Browse Logical data model User interface Local extensibility Technology Scalability / Bottlenecks Costs Compatibility

14 Discovery Specificity –Collection –Granule Retrieval capabilities –Ranking –Relevance –extent of search compliance Search capabilities –Geospatial bounding-box –including Z –Fielded search –Free text –Temporal –Common vs. local attributes Search

15 Browse Specificity –By collection E.g. coverage summaries –By granule Options –Static Fixed parameters –On-demand User-specified parameters Vocabularies –Valids / Domains –Use applicable standards Inter-attribute relationships –Parent-child –Thesauri –Other TBD Data Model

16 User Interface Implementation –Web browser –Other clients Java app Z39.50 Internet search engines Extensibility –APIs Open & complete –Encodings XML Attributes Vocabularies Search capabilities Retrieval capabilities Data access Provide access to local extensions Local Extensibility

17 Technology Portability –Platform dependencies Implementation –Language –communication Persistent connections Non-standard ports and/or protocols Firewalls Number of providers Number of users Volume of data Performance –Rates –Latencies Asymmetric degradation Fault tolerance Scalability and Bottlenecks

18 Costs plug-in –Purchase –Construction –Configuration –Administration Distribution –Providers –Federation Existing systems, clusters, and protocols –GCMD –V0 –Z39.50 Compatibility

19 Proposed Interoperability Technologies GCMD Mercury EOSDIS Version 0 Big Sur DIAL MOCHA

20 Global Change Master Directory (GCMD) Purpose –Search and discovery tool for Earth science data set descriptions –Metadata services: search –Data services: subscription –Direct links to data through alternative interfaces –Z39.50 access to FGDC Clearinghouse

21 Mercury – Metadata Search and Data Retrieval Purpose –XML Web-based system providing common view of disparate metadata and data files –Metadata services: directory-level search –Data services: search and access –FGDC and Z39.50 compliant

22 EOSDIS Version 0 – Metadata Publication and Data Ordering Purpose –Automated search, order, and access for online and nearline archives –Metadata publication: search and access –V0 protocol (PRODUCT_REQUEST message): order and access –Access to local data services

23 Big Sur Purpose –Integrated, distributed data and metadata for search, browse, and access –Metadata services: input data attributes; data history –Data services: functional processing; links to visualization and access tools –Accessible from platforms connected to a Big Sur database

24 Data and Information Access Link (DIAL) Purpose –Web-based software tools for organizing and distributing metadata –Metadata services: search, query, browse, and access –Data services: access and order in multiple formats –Dynamic visualization, X-Y plotting, animation, subsetting, etc. –Integrated with EOSDIS V0 and GCMD

25 MOCHA - Middleware for Integrating Distributed Data Purpose –Java architecture for integrating distributed heterogeneous data –Metadata services: distributed queries using XML & RDF –Data services: executes shipped code at data sources for filtering and aggregation –Java middleware deploys plug & play code to data sources –Use XML to exchange and interpret metadata and code

26 Conclusion Bottom-up interoperability is already happening –Web, clusters, etc. Federation-wide challenge: synthesize a common view –Cook up a nourishing batch of SWIL without losing the flavors of each ingredient


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