1. Federated Databases for the Geosciences CSIG July 21, 2005 Douglas S. Greer

2. Overview Database Federation Primer –Basic concepts and principles –DB2 Information Integrator The CHRONOS Federated Database –Integration of 7 independently developed geoscience databases

3. Top-Level View of a Federated Database Applications Federated Database Data Source AData Source DData Source CData Source B

4. Federated DB Data Sources Geographically Distributed Data Sources Heterogeneous Data Sources –Relational Databases – most common –Non-relational Sources –Web Pages / Web Services –Flat Files

5. Federated Databases May or may not actually contain data Federated database can create Global Views that define data in a uniform way across the data sources Applications can then access data through the global view using the standardized SQL schema

6. IBM DB2 Information Integrator Provides a framework for strategic information integration to help applications access, manipulate and integrate diverse and distributed data sources across multiple servers in real time. Can access structured and unstructured data types including relational databases such as Oracle, MySQL, PostgreSQL and MS SQL Server

7. Connecting to the Remote Database Step 1 – Create WRAPPER –Mechanism that the federated server uses to communicate with a data source –Identifies “Driver” code Step 2 – Identify SERVER – Identifies the connection to a data source –Specifies which WRAPPER to use –Directly or Indirectly specifies the server name, server type, version, database name and special parameters

8. Connecting to the Remote Database Step 3 – Specify USER MAPPING –Maps between a federated database user and an authorized user (account and password) of a data source Step 4 – Define NICKNAMES –Pointer to a table or view in a data source –Creates a binding between a local name and the data source name and hides the associated metadata details

9. A Simple Federated View CREATE VIEW AS SELECT (Database #1 SQL Command) UNION SELECT (Database #2 SQL Command) UNION SELECT (Database #3 SQL Command)

10. Identifying Data Sources CREATE VIEW AS SELECT ‘PALEOSTRAT’ AS db_name genus_id AS genus … FROM PSTRAT.tbl_taxonomy … UNION SELECT ‘PALEOBIOLOGY’ AS db_name genus_name AS genus …

11. Materialized Views Federated databases normally do not store data locally. Data from remote sites is fetched as needed. Materialized Views create a local copy of a Global-View. –Advantage: faster access –Disadvantages: Data may be stale. Refreshes required Several of the CHRONOS Global-Views have versions that use materialized views to increase performance

12. CHRONOS Project Create a dynamic, interactive and time-calibrated framework for Earth history Network of chronostratigraphy databases Online stratigraphic record Visualization and analytical tools Develop a better understanding of fundamental Earth processes through time

13. CHRONOS Federated Databases The following databases are all part of the CHRONOS Federated Database at SDSC based on IBM’s DB2 Information Integrator –Neptune –PaleoStrat –PaleoBiology –Janus –TimeScale –FAUNMAP –MIOMAP

14. Neptune Database Developed at ETH Zürich and currently hosted by Iowa State University Contains microfossil occurrences reported in DSDP and ODP samples PostgreSQL based Contains four basic types of data: Fossil Records, Taxonomy, Age models and Biogeography data Schema contains approximately 20 tables with hundreds of thousands of taxonomic occurrences

15. PaleoStrat Database Developed at Boise State University in collaboration with the CHRONOS Designed to support geoscience tools with broad applicability Contains sedimentary, paleontologic and stratigraphic data MS SQL Server based Approximately 120 tables with thousands taxonomic occurrences Data from other databases currently being loaded

16. PaleoBiology Database Hosted by the National Center for Ecological Analysis and Synthesis (NCEAS) at the University of California at Santa Barbara Contains collection-based occurrence and taxonomic information about marine and terrestrial animals and plants MySQL based 16 tables with hundreds of thousands of taxonomic occurrences

17. Janus Database Database for the Integrated Ocean Drilling Program (IODP) hosted at Texas A&M University Contains numerous types of ocean drilling data collected by United States, Japanese and European ships Oracle based Approximately 580 tables with millions of taxonomic occurrences

18. TimeScale Database Contains data and information from the 2004 Global Time Scale of the International commission on Stratigraphy and 19 other time scales Supports web service conversions tools PostgreSQL based Approximately 25 tables with thousands of data records

19. FAUNMAP Database Hosted by Illinois State Museum Contains information about the historical distribution of mammal species in the United States MySQL based Approximately 30 tables with tens of thousands of data records

20. MIOMAP Database Hosted by University of California, Berkeley Contains comprehensive spatial and temporal analysis of Miocene mammal taxa for the Western United States MySQL based Thousands of records in a relatively small number of tables

21. The Taxa Global-View Simple View to list taxa in all of the databases CHRONOS Taxa –Database Name –Table_Name –Taxon_ID –Genus –Species

22. Taxa Global View Example

23. Conop9 Application Developed by Peter M. Sadler, Dept. of Earth Sciences, Univ. of California Riverside Correlates stratigraphic sections by minimizing the number of inconsistencies in the order of first and last occurrences of fossils between sections Originally developed for flat files then adapted to CHRONOS DB2/II global-views

24. CONOP9 Data Correlation

25. Conop9 Global View Developed for the Conop9 Application The Conop9 SDSC global-view provides a much larger collection of data than that available in the older flat file system The CHRONOS global-view presents exactly the data needed by Conop9 but uses different SQL statements for each database – this involves joins across four tables in Neptune, seven tables in PaleoStrat and five tables in Janus

26. Conop9 Global-View Attributes CHRONOS Conop Global View Fields –Database Name –Genus –Species –Taxon_id – Used to create Conop9 input tables –Hole_id – Which stratigraphic section does this come from –LAD – Last Appearance Datum, newest observation of this taxa for this hole –FAD – First Appearance Datum, oldest observation of this taxa for this hole –LAD and FAD are the result of an SQL computation

27. Conop9 Global View Example

28. Age-Depth Plot

29. Age/Depth Plot Global-Views Uniform Global-View of hole location for ADP application Surprisingly there are significant differences between databases CHRONOS Hole_Summary –Database Name –Hole_ID –Latitude –Longitude

30. Age/Depth Plot Views Uniform Global-View for Hole/Taxa Description for ADP application CHRONOS Hole_Desc –Database Name –Hole_ID –Elevation –Meters_of_Section –Taxa_Count

31. Age/Depth Global View Example

32. Questions ?