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Metadata and Cross-Collection Searching in Luna’s Insight. Problem: Integrating Access to Visual Collections. Diverse visual resources and descriptions Multiple repositories at Cornell, multiple digital collections, distributed digital collections

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Metadata and cross collection searching in luna s insight

Metadata and Cross-Collection Searching in Luna’s Insight

Cornell Institute for Digital Collections


Problem integrating access to visual collections
Problem: Integrating Access to Visual Collections

  • Diverse visual resources and descriptions

    • Multiple repositories at Cornell, multiple digital collections, distributed digital collections

    • Different discovery methods and metadata formats

  • Searchers are on their own to be aware of collections, know how to link to them, and search different interfaces

Cornell Institute for Digital Collections


1 st solution a shared union catalog for images
1st Solution: A Shared Union Catalog for Images

  • Adopted MultiMIMSY 2000 from Willoughby Associates

    • Museum collections management software

    • Moved data from stand-alone applications into it

    • For the past 4 years, have worked on developing shared standards and practices

Cornell Institute for Digital Collections


Mimsy demo
MIMSY Demo

Cornell Institute for Digital Collections


Standards issues
Standards Issues

  • No museum descriptive standard

    • CIDOC reference framework as a glue?

  • We have tried to follow VRA 3.0

  • Use AAT, ULAN, TGN, for data values

Cornell Institute for Digital Collections


Is vra 3 0 too complex
Is VRA 3.0 too complex?

  • [example]

Cornell Institute for Digital Collections


2nd integration solution insight from luna imaging
2nd Integration Solution: Insight from Luna Imaging

  • Addresses issues of collection diversity

    • Can search multiple collections at once

  • Addresses issues of metadata diversity

    • Maps data to a common standard

    • Allow searching across multiple heterogeneous collections

Cornell Institute for Digital Collections


Insight demo
Insight Demo

  • Selected features:

    • General search and display attributes

    • Cross-collection searching

    • Variable metadata displays

    • Annotation tool

    • Support for formats

Cornell Institute for Digital Collections


Insight s support of descriptive complexity
Insight’s support of descriptive complexity

  • Controlled vocabulary lists and repeating values for fields;

  • Hierarchical structures and values;

  • Groups of fields that should be treated together, e.g., artist name, life dates, nationality;

  • Display order of values, fields, and groups of fields

Cornell Institute for Digital Collections



Insight v3 Data Structure

  • Replicates source data in a format common to all Insight collection databases

Values

Terms

Inverted Index Tables

Tables

Joins

Fields

FieldGroups

Mapping Tables

Objects

People

Location

Location

Hierarchy

Events

Source Data Tables


Collection

Manager

Virtual

Collection

A

Virtual

Collection

B

Virtual

Collection

C

Virtual

Collection

D

Repository

A

Repository

B

Repository

C

Insight Virtual Collection Manager


StandardID

StandardName

FieldID

DisplayName

MappingStandard

MappingStandardFieldID

1

ObjectID

9

Maker

CDWA

102

2

DublinCore

6

Creator

CDWA

102

3

VRA

6

Creator

CDWA

102

4

VRA v3.0

16

Creator

CDWA

102

4

VRA v3.0

19

Personal Name

CDWA

102

5

CIMI

68

Creator Name

CDWA

102

5

CIMI

79

Creator General

CDWA

102

6

USMARC

10

Main Entry

CDWA

102

6

USMARC

11

Added Entry

CDWA

102

15

Dalton Museum

6

Artist Name

CDWA

102

Standards Field Mapping Mapping collection fields to standard fields to allow searching across separate collection databases

  • Maps Artist Nameto CDWA FieldID 102 (Creation-Creator-Identity-Names)

Field Mapping Results for “Artist Name”

Cornell Institute for Digital Collections


Built in metadata standards
“Built-in” Metadata Standards

  • Dublin Core

  • MARC

  • VRA 2.0

  • VRA 3.0

  • CDWA

    You can add whatever you like

Cornell Institute for Digital Collections


Implementation data into insight
Implementation: Data into Insight

  • Currently, export desired data as Text files, clean it up, and import into Insight

  • This year – link tables between the two systems?

Cornell Institute for Digital Collections


What is ahead for insight
What is ahead for Insight?

  • Development of stand-alone cataloging tool (May?)

  • Further support for hierarchical objects

    • Books, letters

  • Links to LDAP and Kerberos authentication

  • GIS support

Cornell Institute for Digital Collections


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