Flora and Fauna of the Great Lakes Region:

1. Flora and Fauna of the Great Lakes Region: A Multimedia Digital Collection University of Michigan - University Library

2. Collaborators • University Library - • Major investment in digital library content, infrastructure and architecture • Museum of Zoology and Herbarium • Strong collections; increasing pressure to serve a wider audience especially via the Web • Exhibits Museum of Natural History University of Michigan - University Library

3. Project Goals • To develop increased access to the Great Lakes region portions of the Museums collections • To develop an extensible infrastructure for putting natural history collections online • To explore, prototype and test tools for using the online resources for a variety of scholarly and educational purposes University of Michigan - University Library

4. Museum Goals • Additional support for digitizing collections • Opening their collections to new audiences • Opportunity to explore partnership with the Library • Support for maintenance and long-term access to their data University of Michigan - University Library

5. (screen shot) University of Michigan - University Library

6. (screen shot) University of Michigan - University Library

7. Library Goals • Extend digital library support from the humanities to the natural sciences • Test the ability of the existing architecture to support new subjects and methods of inquiry • Extend digital library architecture to include cross-class searching - text, image, collection database records University of Michigan - University Library

8. Digital Library Holdings at the University of Michigan Holdings as of March 2001 • Full electronic text 31,558 • Pages/images 6,684,342 • Bibliographic Records 57,081,109 • Words 2,536,312,477 • Bytes 190,629,303,672 University of Michigan - University Library

9. Digital Library Architecture at the University of Michigan • Image class • Federation of diverse collection databases • Support for image retrieval • Text class • Other classes such as bibliographic data and archival finding aids • Retrieval software available for licensing • Middleware is Open Source (DLXS) University of Michigan - University Library

10. New Challenge - Cross-Class Searching • To facilitate searching across text, image, and collection database records • To return results to users in ways that will be useful to them, rather than simply reflecting the characteristics of the underlying systems University of Michigan - University Library

11. New Content • Supplementing the museum collection databases with: • Field notes • Surrogate records and page images • Images • New photography and digitization of existing slides and negatives • Major monographs • Full text searching University of Michigan - University Library

12. New Audiences • Non-specialist users • Lifelong learners • Undergraduate students • K-12 users • Specialist users working in areas such as biodiversity research - working outside the confines of a single discipline University of Michigan - University Library

13. Metadata Challenges • Federate data from multiple existing databases • Augment data to serve new audience and uses • Create metadata for new materials • Provide basis for coherent shared displays of search results University of Michigan - University Library

14. Collections Databases—Federation Fish Catalog Mammals Databases Fungus Catalog Field Notes (New Content) Image Metadata Digital Library Metadata University of Michigan - University Library

15. Mammals Example UMMZ Zoology Database Fields Table 2 Table 1 Location ID LOCAcronym LOCDATE Latitude D Latitude M Latitude S Longitude D Longitude M Longitude S Latitude NS Longitude EW Map Data Map Code LocField OceanCont Country State County Gear Collectors LocTime Drainage Temp. Depth Locality LocRemarks (incl. Orig Field #) Primary ID LastMod Catalog Alcohol Skeleton Clear Stain Genus Species Subspecies Field[#] Determiner Cataloger Type Status Size Remarks Rodents databasefields Museum no. Sex Skin Skull Skeleton Fluid Baculum Glans Karyotype Field no. Day Month Year Country Locality Collector LN Initials 2nd collector Initials Order Family Genus Species Subspecies Batch no. Comments # individuals State County University of Michigan - University Library

16. Augmenting Existing Content • Common Names • Geospatial Referencing • Dates University of Michigan - University Library

17. Collections Databases—Federation Fish Catalog Mammals Databases Fungus Catalog Field Notes (New Content) Image Metadata Digital Library Metadata Species Name Lookups Geospatial Lookups ISO Date Lookups University of Michigan - University Library

18. Collections Databases—Augmentation Fish Catalog Mammals Databases Fungus Catalog Digital Library Metadata Species Name Lookups Geospatial Lookups ISO Date Lookups University of Michigan - University Library

19. New Databases • Field Notes • Image Metadata University of Michigan - University Library

20. Field Notes Structure—Collection Event Collection Event Species Account Field Catalog (projected) Join File Page Image Table Species Table Volume Data Collector Data Location Data University of Michigan - University Library

21. Field Notes Structure—Species Account Collection Event Species Account Field Catalog (projected) Join File Page Image Table Species Table Volume Data Collector Data Location Data University of Michigan - University Library

22. New Processes • Matching field content to authoritative forms for lookup construction (A miracle happens here) • Lookup export to originating databases (if time and funds permit) University of Michigan - University Library

23. Mapping Image Collections into the Image Services Metadata Structure (what do art and fungi have in common?) University of Michigan - University Library

24. Dual Model of Image Representation VRA Representation Model • Work=physical entity that exists, has existed at some time in the past, or that could exist in the future (fish, field notes page, painting, etc) • Image=a visual representation of a work University of Michigan - University Library

25. Work/Image Relationships • One work may have multiple image representations (picture of whole frog, frog parts, x-rays, etc.) • Images may have sequential derivations (photo is digitized, digital file has thumbnail, etc.) University of Michigan - University Library

26. Separating Work Data from Image Data Collector Collection Date Data is inherited Photographer Photograph Date Frog=Work Frog=Work Photo of Frog=Image Digitizer Digitization Date Digitized Photo of Frog (derived image) University of Michigan - University Library

27. Why? • Work only needs to be described once • Image history is documented • Each image is associated with data (like creation dates) that are specific to its existence University of Michigan - University Library

28. Storing data in the Digital Library • Image database relates work and image metadata • Metadata exported as records with 1:1 correspondence with image file names • Digital Library stores metadata and image files using standard image class model core categories • User search calls up metadata and linked images University of Michigan - University Library

29. Desired result • Users can search across classes and collections using core fields (species, common name, location, date) or keywords • Users can search within collections using fields chosen from originating database • Displays can be customized to show common or custom field labels. University of Michigan - University Library