Image Databases in Practice

28
1 Metadata for Asset Management Peter B. Hirtle Co-Director Cornell Institute for Digital Collections

Transcript of Image Databases in Practice

Page 1: Image Databases in Practice

1

Metadata for Asset Management

Peter B. HirtleCo-Director

Cornell Institute for Digital Collections

Page 2: Image Databases in Practice

2

Problem: Imaging projects produce many digital files

Page 3: Image Databases in Practice
Page 4: Image Databases in Practice

4

Problem redux…

How to you locate, manage, and display scanned images?

Page 5: Image Databases in Practice

5

One possible answer: Put identifying information into the file

header Problems with this approach

Hard to search and retrieve May change over time May not be able to migrate data

Page 6: Image Databases in Practice

6

Second approach

Use an image management system to manage images:

A software application (often a database) used for organizing, managing, and providing access to digital media

Page 7: Image Databases in Practice

7

Image management system

Provides tools for searching(Descriptive metadata)

Provides public and internal links to the images

(Structural metadata)

Provides the control elements needed for short and long-term access

(administrative metadata)

Page 8: Image Databases in Practice

8

Metadata for image management No single accepted standards for each type of

metadata Descriptive metadata

MARC, DC, MOA2, EAD, VRA, Open Archives Initiative Structural metadata

LC RFP’s, MOA2, DOIs Administrative metadata

DIG 35, NISO draft standard, MOA2, in process preservation standards such as CEDARS

Page 9: Image Databases in Practice

9

Key concept: metadata is seldom fixed

You will be massaging the metadata throughout the life of the project

To conform to emerging standards To adjust to new technical environments To add functionality

Once you start a digital project, you are committed to it for life

Page 10: Image Databases in Practice

10

So where do you get an image management solution?

No single off the shelf solution Solutions vary according to:

complexity performance cost

Page 11: Image Databases in Practice

11

What is the “ideal solution”…?

Dependent upon your needs: size of database expected demand for images volatility of the data available technical resources

Page 12: Image Databases in Practice

12

Other elements to consider....

Access to a controlled thesaurus Flexibility in database design The expected life-span of the data If permanent, the potential for

migration Adherence to database standards Adherence to data content standards

Page 13: Image Databases in Practice

13

Three classes of solutions Generic database applications

Desktop Client/server

Specialized image management programs

SGML-based solutions

Page 14: Image Databases in Practice

14

Generic database applications

Most common desktop programs MS Access, Filemaker Pro

Client/server applications Oracle, Informix (including Illustra), 4th

Dimension, object-oriented applications

Page 15: Image Databases in Practice

15

Demo Here

Page 16: Image Databases in Practice

16

Advantages to desktop programs Low initial cost for desktop programs Desktop programs are relatively easy to

program and use Simple data import and export Growing 3rd-party market of add-ons

(especially web tools)

Page 17: Image Databases in Practice

17

Disadvantages

Desktop solutions limited in size(< 10,000?)

Few standardized data structures Web interfaces require customization High costs of programming

explicit with large applications hidden but real with desktop

Page 18: Image Databases in Practice

18

Specialized image management programs “Desktop” examples:

Canto’s Cumulushttp://www.canto-software.com/

ImageAXS http://www.dascorp.com

Portfolio (formerly Fetch)http://www.extensis.com/products/Portfolio/

Content (shown here)

Page 19: Image Databases in Practice

19

Advantages

Pre-defined data structure Built-in links to images Some are cross-platform Some have built-in links to the web Overall, less programming expertise

required

Page 20: Image Databases in Practice

20

Disadvantages

Fixed data structure Proprietary database structures Limited customization possible Web access is primarily via scripts

Page 21: Image Databases in Practice

21

Larger client/server image management programs

Library software Museum-oriented programs Document management programs Digital library solutions Other programs for newspaper photos,

stock photos, multimedia asset management, etc.

Page 22: Image Databases in Practice

22

Library systems Image-enabled library catalogs include

VTLS CARL OCLC Sitesearch Endeavor’s Voyager and ENCOMPASS RLG has a system in development

All library systems will head in this direction

Page 23: Image Databases in Practice

23

Advantages

Ready links between catalog and digital images

Built on common data structures MARC or Dublin Core

Increased likelihood they will exploit library-specific metadata

Greater possibility for shared resources

Page 24: Image Databases in Practice

24

Disadvantages Poor integration between images and

text No common repository standard No shared standard for utilizing

metadata Administrative hurdles

Do digital imaging and Library Systems talk to each other?

Page 25: Image Databases in Practice

25

SGML and XML-based systems

A new approach: using metadata encoded with SGML or XML

Based on document type definitions (DTD) Examples:

Photographs using EAD: California Heritage project

Text using Ebind (electronic binding DTD) Agora’s complete management system

Page 26: Image Databases in Practice

26

Why consider SGML?

Based on an international standard DTD’s may themselves become

standard Example: MOA2

May be more appropriate for text-oriented description

Links to other SGML or XML-encoded resources are possible

Page 27: Image Databases in Practice

27

Disadvantages to SGML

Little native client support for SGML SGML engines may not be as powerful as

relational databases XML databases are just being developed Native SGML software tends to be expensive Often it is easier to store data in a database,

and write it out with SGML XML tags for exchange or export

Page 28: Image Databases in Practice

28

Summary

No single imagebase package is likely to meet all your needs

Plan on continuously modifying databases, interfaces, and metadata

Monitor closely the work developing image database standards in the area of greatest interest to you

Avoid if possible the hidden costs of internal development