ASC Annual Meeting - PowerPoint PPT Presentation

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ASC Annual Meeting

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Flora and Fauna of the Great Lakes Region: A Multimedia Digital Collection Collaborators University Library - Major investment in digital library content ... – PowerPoint PPT presentation

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Title: ASC Annual Meeting


1
Flora and Fauna of the Great Lakes Region
  • A Multimedia Digital Collection

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

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

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

5
(screen shot)
6
(screen shot)
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

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

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)

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

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

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

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

14
Collections DatabasesFederation
Fish Catalog
Mammals Databases
Fungus Catalog
Field Notes (New Content)
Image Metadata
Digital Library Metadata
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. Dep
th Locality LocRemarks (incl. Orig Field )
Primary ID LastMod Catalog Alcohol Skeleton Clear
Stain Genus Species Subspecies Field Determiner
Cataloger Type Status Size Remarks
Rodents database fields
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
16
Augmenting Existing Content
  • Common Names
  • Geospatial Referencing
  • Dates

17
Collections DatabasesFederation
Fish Catalog
Mammals Databases
Fungus Catalog
Field Notes (New Content)
Image Metadata
Digital Library Metadata
Species Name Lookups
Geospatial Lookups
ISO Date Lookups
18
Collections DatabasesAugmentation
Fish Catalog
Mammals Databases
Fungus Catalog
Digital Library Metadata
Species Name Lookups
Geospatial Lookups
ISO Date Lookups
19
New Databases
  • Field Notes
  • Image Metadata

20
Field Notes StructureCollection Event
Collection Event
Species Account
Field Catalog (projected)
Join File
Page Image Table
Species Table
Volume Data
Collector Data
Location Data
21
Field Notes StructureSpecies Account
Collection Event
Species Account
Field Catalog (projected)
Join File
Page Image Table
Species Table
Volume Data
Collector Data
Location Data
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)

23
Mapping Image Collections into the Image Services
Metadata Structure
  • (what do art and fungi have in common?)

24
Dual Model of Image Representation
  • VRA Representation Model
  • Workphysical entity that exists, has existed at
    some time in the past, or that could exist in the
    future (fish, field notes page, painting, etc)
  • Imagea visual representation of a work

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.)

26
Separating Work Data from Image Data
Collector Collection Date
Data is inherited
Photographer Photograph Date
FrogWork
FrogWork
Photo of FrogImage
Digitizer Digitization Date
Digitized Photo of Frog (derived image)
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

28
Storing data in the Digital Library
  • Image database relates work and image metadata
  • Metadata exported as records with 11
    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

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.
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