1. A MARC-LOM Crosswalk for e-Learning
Yang Cao, Fuhua Lin, Rory McGreal, etc
May 19, 2004

2. Introduction Demand For Online Education /e-Learning
Reuse of Learning Resources
Learning objects [IEEE]
Why Crosswalk
Minimize the amount of time needed to create and maintain the metadata
Maximize metadata’s usefulness to the widest community of users

3. Introduction (ctd) What is Crosswalk? Objectives
A crosswalk is a semantic or technical mapping (sometimes both) from one metadata standard to another
Objectives
Developing automated tool for converting from MARC to LOM
Investigating the issues and challenges of this crosswalk

4. What is MARC MARC -- MAchine-Readable Cataloging
00941nam a 020114s flum b a001 0 eng  a  a  aDLCbengcDLCdDLC apcc00aQA76.9.D3bT 00a005.75/8221 aQA D3 T 1 aThuraisingham, Bhavani M.10aXML databases and the semantic Web /cBhavani Thuraisingham. aBoca Raton, FL :bCRC Press,c2002. a306 p. :bill. ;c24 cm. aIncludes bibliographical references and index. 0aDatabase management. 0aXML (Document markup language) 0aWeb site development. 0aSemantic Web. aCaAEAU. a- p-----m-r-aaap main comp2book1 aInv# ATHA Dated: Amt:$ On: Voucher#43778 For \us75.95

5. What is LOM? Learning Object Metadata
The LOM/Cancore standard focuses on the minimal set of properties needed to allow learning objects to be managed, located, and evaluated.
LOM/Cancore schema

6. <?xml version="1.0" encoding="UTF-8"?> <lom>
<general>
<identifier>
<catalog>ISBN</catalog>
<entry> </entry>
</identifier>
<title><string language="en">XML databases and the semantic Web </string></title>
<keyword>
<string language="en">Database management.</string>
</keyword>
</general>
<lifeCycle>
<contribute>
<role>
<source>LOMv1.0</source>
<value>Author</value>
</role>
<entity><vcard>BEGIN:VCARD VERSION:3.0FN: … END:VCARD</vcard> </entity>
</contribute>
</lifeCycle>
<technical>
<format>non-digital</format>
<location>QA D3 T </location>
</technical>
<right /> ….

7. Design of MARC-LOM Crosswalk
The Marc to LOM converter is a web- based program that takes the metadata of library materials in MARC format and converts them into LOM format
MARC-LOM
Converter
LOM
MARC

8. MARC – LOM converter

9. Process of MARC-LOM Conversion

10. An Example of Mapping MARC
… …. ‑020114s flum b a001 0 eng ‑ ­a ‑ ­a ‑ ­aDLC­beng …. aXML databases and the semantic Web …
MARC-XML elements
<controlfield tag="008">020114s flum b a001 0 eng </controlfield>
<datafield tag="245" ind1="1" ind2="0">
<subfield code="a">XML databases and the semantic Web </subfield>
</datafield>
LOM XML elements
<language>en</language>
<title>
<string language="en">XML databases and the semantic Web </string>
</title>

11. Semantic Mapping
A mapping of each element in the source metadata standard with a semantically equivalent element in the target metadata standard
Requires in-depth knowledge and specialized expertise in the associated metadata standards
Mapping is an iterative process involving ongoing refinement, revision, and, even rethinking of element matches.

12. LOM/CANCORE ELEMENT MARC TAG & SUBFIELD MARC DESCRIPTION CONDITIONS
MARC 21 to LOM/CanCore Crosswalk Table
LOM/CANCORE ELEMENT
MARC TAG & SUBFIELD
MARC DESCRIPTION
CONDITIONS
1.1 Identifier
020 a
ISBN
If MARC tag is 020, then the catalog = ISBN
022 a
ISSN
If MARC tag is 022, then the catalog = ISSN
856 u
Electronic Location and Access
1.2 Title
245 a
Title
245 b
Remainder of title
1.3 Language
008/35-37
Language
1.4 Description
520 a
Summary
1.5 Keyword
600 a
Subject – Personal
610 a
Subject – Corporate
650 a
Subject – Topical
611 a
Subject-Conference
2.1 Version
250 a
Edition
2.3 Contribute
Role
100 a
Personal author
Field present if item was created by the entry.

13. Technical Mapping
Employs a set of computer programs and transformation languages
Extensible Stylesheet Language Transform (XSLT) to programmatically change extensible Markup Language (XML) metadata records from MARC-XML format to LOM XML format
Differences in terminology and structures existed in two metadata standards and the mapping needs “semantic” mapping not just simple element or structure mapping.

14. Challenges in Mapping Lack of common terminology
Different structures of metadata standards
Expertise in element mapping
one to one
one to many
many to one
Loss of information

15. MARC XML <?xml version="1.0" encoding="UTF-8"?> <record>
<leader>00941nam a 4504</leader>
<controlfield tag="008">020114s flum b a001 0 eng </controlfield> ….
<datafield tag="090" ind1=" " ind2=" ">
<subfield code="a">QA D3 T </subfield>
</datafield>
<datafield tag="245" ind1="1" ind2="0">
<subfield code="a">XML databases and the semantic Web </subfield>
<subfield code="c">Bhavani Thuraisingham.</subfield>
<datafield tag="650" ind1=" " ind2="0">
<subfield code="a">Database management.</subfield>
…..
<subfield code="a">Semantic Web.</subfield>
……….

16. LOM
<?xml version="1.0" encoding="UTF-8"?> <lom xmlns:xsl=…>
<general>
<identifier>
<catalog>ISBN</catalog>
<entry> </entry>
</identifier>
<title>
<string language="en">XML databases and the semantic Web </string>
</title>
<keyword>
<string language="en">Database management.</string>
</keyword>
</general>
<lifeCycle>
<contribute>
<role>
<source>LOMv1.0</source>
<value>Author</value>
</role>
<entity>
<vcard>BEGIN:VCARD VERSION:3.0 FN:Bhavani M.Thuraisingham N:Thuraisingham; Bhavani; M. END:VCARD</vcard>
</entity>

17. Conclusion and Future Work
The MARC-LOM Crosswalk
Allows MARC based library content metadata to interact with XML based digital repositories
Enables the simplification of the creation/maintenance of metadata and their utilization in e-Learning
Brings us one step closer to enabling the use of intelligent agents on the semantic web
Future work
Focus on interoperability functions including finding resources and retrieving them, and supporting interactions between repositories

18. Acknowledgement
This project is funded by Industry Canada and was part of an initiative called IMEC (Interoperable Metadata for e-Learning in Canada) as well as the pan-Canadian eduSource project funded by CANARIE, Canada’s broadband research network.
The software application was based partially on the work of the Library of Congress.

19. References
1. CIHE: The Council for Industry and Higher Education, Response to the joint consultation document from HEFCE and the Learning and Skills Council (2002),
2. Cao, Y., Jim, G.: Agent Programmability in a Multi-Agent Learning Environment. Proceeing of the 11th International Conference on Artificial Intelligence in Education. Australia(2003).
3. Learning Technology Standards Committee (LTSC):
4. CETIS Group:
5. MERLOT:
6. Wisconsin Online Resource Center - Wisc-Online Learning Object Project:
7. Digital Library for Earth System Education (DLJESE):
8. MAchine-Readable Cataloging (MARC):
9. IEEE Learning Object Metadata (LOM):
10. CanCore Initiative
11. MARC-XML architecture architecture.html
12. St. Pierre, M., LaPlant, W. P. Jr. : Issues in Crosswalking Content Metadata Standards (1998)

20. THANKS !
THANKS!