1. The Importance of Metadata in the E-Learning Environment
Presented by Thuli Khoza
Walter Sisulu University E-Learning Conference 2010
2-3 November 2010

2. Overview What is metadata? Why use metadata? What is e-Learning?
Why e-Learning?
What is a learning object?
Need for metadata in e-Learning
Metadata standards
Metadata creation
The presentation will address the following topics

3. Overview (cont’) Dublin Core Metadata Standard (DC)
Learning Object Metadata (LOM)
Mapping LOM element set to DC element set
Value of metadata in e-Learning
Conclusion

4. What is metadata?
Metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource.
Metadata is often called data about data or information about information.
Therefore, metadata needs to provide information that:
􀂃 certifies the authenticity and degree of completeness of the content
􀂃 establishes and documents the context of the content
􀂃 identifies and exploits the structural relationships that exist between and within information objects
􀂃 provides a range of intellectual access points for an increasingly diverse range of users
provides some of the information that an information professional might have provided in a physical reference or research setting

5. Why Use Metadata?
Metadata provides an essential link between the information creator and the information user
We can ensure that this objective is met by using metadata in accordance with international standards
Ancient Roman Symbol standards
(Roman Standards.jpg (copyright has expired and now in public domain)

6. What is e-Learning?
Refers to the use of Internet technologies to deliver and support education (Florea, 2010)
Education & training delivered via library portals and institutional repositories
Also known as web-based, virtual learning, online learning and distance learning

7. Why e-Learning?
Allows learning to take place anytime, anywhere, any device and at an individual’s own pace
Just in time information
Less expensive
Easily accessible

8. What is a learning object?
Learning object is any entity, digital or non digital that may be used and re-used for learning, education or training (IEEE Learning Technology Standards Committee ,2001)
Breaking of educational resources into modular chunks with each object having its own description (Krull, 2005)

9. What is a learning object? (cont’)
Learning objects include:
Instructional content
Multimedia content
Software tools
Learning objectives

10. Need for metadata in e-Learning
Facilitate discovery of learning objects
Help organize content in web-based e-learning environments
Facilitate interoperability and integration of legacy resources
Provide digital identification of learning objects
Support archiving of digital objects
Facilitate preservation
Source: National Information Standards Organization Understanding metadata
Resource Discovery
Metadata serves the same functions in resource discovery as good cataloging does by:
• allowing resources to be found by relevant criteria;
• identifying resources;
• bringing similar resources together;
• distinguishing dissimilar resources; and
• giving location information.
Organizing Electronic
Resources
As the number of Web-based resources grows exponentially, aggregate sites or portals are increasingly useful in organizing links to resources based on
audience or topic. Such lists can be built as static webpages, with the names and locations of the resources “hardcoded” in the HTML. However, it is more efficient and increasingly more common to build these pages dynamically from metadata stored in databases.
Various software tools can be used to automatically extract and reformat the information for Web applications.
Interoperability
Describing a resource with metadata allows it to be understood by both humans and machines in ways that promote interoperability.
Interoperability is the ability of multiple systems with different hardware and software platforms, data structures, and interfaces to exchange data with minimal loss of content and functionality. Using defined metadata schemes, shared transfer protocols, and crosswalks between schemes, resources across the network can be searched more seamlessly. Two approaches to interoperability are cross-system search and metadata harvesting. The Z39.50 protocol is commonly used for cross-system search. Z39.50 implementers do not share metadata but map their own search capabilities to a common set of search attributes. A contrasting approach taken by the Open Archives Initiative is for all data providers to translate their native metadata to a common core set of
elements and expose this for harvesting. A search service provider then gathers the metadata into a consistent central index to
allow cross-repository searching regardless of the metadata formatsused by participating repositories.
Digital Identification
Most metadata schemes include elements such as standard numbers to uniquely identify the work or object to which the metadata refers. The location of aobject may also be given using a file name, URL (Uniform Resource Locator), or some more persistent identifier such as a PURL (Persistent URL) or DOI (Digital Object Identifier). Persistent identifiers are preferred because object locations often change, making the standard URL (and therefore the metadata record) invalid. In addition to the actual elements that point to the object, the metadata can be combined to act as a set of identifying data,
differentiating one object from another for validation purposes.
Archiving and Preservation
Most current metadata efforts center around the discovery of recently created resources. However, there is a growing
concern that digital resources will not survive in usable form into the future. Digital information is fragile; it can be corrupted or altered,
intentionally or unintentionally. It may become unusable as storage media and hardware and software technologies change. Format
migration and perhaps emulation of current hardware and software behavior in future hardware and software platforms are strategies for
overcoming these challenges. Metadata is key to ensuring that resources will survive and continue to be accessible into the future.
Archiving and preservation require special elements to track the lineage of a digital object (where it came from and how it has changed
over time), to detail its physical characteristics, and to document its behavior in order to emulate it on future technologies. Many organizations internationally
have worked on defining metadata schemes for digital preservation, including the National Library of Australia, the British Cedars Project (CURL Exemplars
in Digital Archives), and a joint Working Group of OCLC and the Research Libraries Group (RLG). The latter group developed a framework outlining types of
presentation metadata. A follow-up group, PREMIS (PREservation Metadata: Implementation Strategies)— also sponsored by OCLC and RLG—is developing a set of core elements and strategies for the encoding, storage, and management of preservation metadata within a digital preservation system. Many of these initiatives are based on or compatible with the ISO Reference Model for an Open Archival Information System (OAIS).
The Framework of Guidance for Building Good Digital Collections, available on the NISO website, articulates six principles applying to good metadata:
• Good metadata should be appropriate to the materials in the collection, users of the collection, and intended, current and likely use of the digital object.
• Good metadata supports interoperability.
• Good metadata uses standard controlled vocabularies to reflect the what, where, when and who of the content.
• Good metadata includes a clear statement on the conditions and terms of use for the digital object.
• Good metadata records are objects themselves and therefore should have the qualities of archivability, persistence, unique identification, etc.
Good metadata should be authoritative and verifiable.
• Good metadata supports the long-term management of objects in collections.
Metadata is key
to ensuring that
resources will
survive and
continue to be
accessible into
the future.

11. Metadata standards Structure standards (Metadata schemas)
-schemes or element sets, e.g.
Dublin Core elements, DDI elements VRA Core Categories, MODS elements, MARC elements, Learning Object Metadata elements
Presentation standards
-for display / presentation to users
(e.g. OPAC local display settings)
ISBD areas and punctuation
CSS style sheet for XML display
Value standards
-controlled vocabularies for the values
of elements, e.g. LCSH, DDC
Content standards
-rules, guidelines
e.g. AACR2, RDA and
In-house Best Practice
Encoding standards
-for machine readability, communication and exchange
e.g. XML, MARCXML, HTML
Metadata schemas
Many different metadata schemes are being developed in a variety of user environments and disciplines.
Examples:
Dublin Core
The Dublin Core Metadata Element Set arose from discussions at a 1995 workshop sponsored by OCLC and the National Center for Supercomputing Applications (NCSA).
The original objective of the Dublin Core was to define a set of elements that could be used by authors to describe their own Web resources. Faced with a proliferation of electronic resources and the inability of the library profession to catalog all these resources, the goal was to define a few elements and some simple rules that could be applied by noncatalogers.
VRA (Visual Resources
Association ) Core – a metadata scheme for describing a visual work and its representations such as a painting or sculpture. Version 3.0 of the VRA Core Categories consists of 17 metadata elements which can be used as applicable to describe each of these versions and relate them to each other: Record Type, Type, Title, Measurements, Material, Technique,
Creator, Date, Location, ID Number, Style/Period, Culture,Subject, Relation, Description, Source, and Rights. Like the Dublin Core, the VRA Core scheme does not specify any particular syntax or rules for representing content.
Metadata Object Description Schema (MODS)
The Metadata Object Description Schema (MODS) is a descriptive metadata schema that is a derivative of MARC 21 and intended to either carry selected data from existing MARC 21
records or enable the creation of original resource description records. It includes a subset of MARC fields and uses languagebased tags rather than the numeric ones used in MARC 21 records. In some cases, it regroups elements from the MARC 21 bibliographic format.
MARC 21 (MAchine Readable
Cataloging) -- a formatting, record structure, and encoding standard for electronic bibliographic cataloging records developed by the Library of Congress. The “21” refers to the version of MARC issued in 1998 that integrated the U.S. and Canadian versions of MARC.
MARCXML – a metadata scheme for working with MARC data in a XML environment
XML (Extensible Mark-up Language). XML, developed by the World Wide Web Consortium (W3C), is an extended form of HTML that allows for locally defined tag sets and the easy exchange of structured information.
Metadata schemes or element setsStandardized sets such Dublin Core, VRA and MODS•
Data content standardsRules or guidelines for input•
Data value standardsLists of allowed values for an element•
Data format or encoding standards
How to encode the metadata•
Data presentation standardsDisplay of the metadata
MsWord style sheet
Catalogue display

12. Metadata creation Who creates metadata? Varies by discipline
The resource being described
Always a cooperative effort
Technical staff
Information Specialists
Which metadata standards do we use?
Who creates metadata? The answer to this varies by discipline, the resource being described, the tools available, and the expected outcome, but it is almost always a cooperative effort. Much basic structural and administrative metadata is supplied by the technical staff who initially digitize or otherwise create the
digital object, or is generated through an automated process. For descriptive metadata, it is best in some situations if the originator of the resource provides the
information. This is particularly true in the documentation of scientific datasets where the originator has significant understanding of the rationale for the dataset and the uses to which it could be put, and for which there is little if any textual information from which an indexer could work.
However, many projects have found that it is more efficient to have indexers or other information professionals create the descriptive metadata, because the authors or creators of the data do not have the time or the skills. In other cases, a combination of researcher and information professional is used.
The researcher may create a skeleton, completing the elements that can be supplied most readily. Then results may be supplemented or reviewed by the information specialist for consistency and compliance with the schema syntax and local guidelines.
Dublin core is the most popular metadata standard. But the lom standard will also be discussed
arning Object metadata

13. Dublin Core Metadata Standard (DC)
Arose from series of workshops
Results from the Dublin Core Metadata Initiative (DCMI)
Consists of 15 basic elements
Dublin Core Qualifiers used to refine scope of an element
Qualified Dublin Core metadata element set is used in DSpace with refinements. Thus additional qualifiers are define for some DC elements. The title, language and date is mandatory elements. I will explain the qualifiers later in the presentation

14. Dublin Core Metadata Standard (DC) (cont’)
Elements are optional and repeatable
May be presented in any order
Qualified Dublin Core metadata element set is used in DSpace with refinements. Thus additional qualifiers are define for some DC elements. The title, language and date is mandatory elements. I will explain the qualifiers later in the presentation

15. Dublin Core Metadata Element Set
Identification and primary characteristics
Title
Identifier
Date
Language
Type
Format
Intellectual responsibility and ownership
Creator
Contributor
Publisher
Rights
Subject content
Subject
Description
Coverage
Relationships with other resources
Relation
Source
The Dublin Core is an internationally recognized metadata standard composed of fifteen basic elements, or descriptive categories, used to describe a variety of digital resources. The semantics of these elements have been established through consensus by an international, cross-disciplinary group of professionals from the library, museum, publishing, computer science, and text encoding communities, as well as from other related fields of scholarship. The Dublin Core Metadata Initiative Element Set has been approved by the American National Standards Institute (ANSI) and assigned the number Z39.85.
Source: Miller, Steven J., Metadata for digital collections: an online workshop.

16. Learning Object Metadata (LOM)
LOM standard
Developed by IEEE Learning Technology Standards Committee (LTSC)
Enable the use and reuse of technology supported learning resources
Defines the minimal set of attributes
Attributes grouped into 9 categories
70 attributes grouped into 9 categories
It is structural

17. Learning Object Metadata Standard element set
Presents general formation about the learning object such as title, language, and keywords
General
Life cycle
Outlines the history of the development of the learning object including changes that have occurred in features during its evolution, eg, version and current status
Meta-metadata
Information about the metadata instance itself rather than the learning object that the metadata instance describes
Technical
Information about technical requirements and technical characteristics of the learning object
Educational
Outlines educational and pedagogic characteristics of the learning object

18. Learning Object Metadata Standard element set (cont’)
Rights
Information about intellectual property rights and conditions for using the learning object
Relation
Outlines features that define the relationships between the learning object and other related learning objects
Annotation
Provides comments about experiences of using the learning object. Includes details about who created the comments and when the comments were created
Classification
Describes the learning object in relation to a particular classification
Source: ( Mwanza, D 2005)

19. Mapping LOM element to DC element set
DC.Identifier
General.Identifier.Entry
DC.Title
General.Title
DC.Language
General. Language
DC.Description
General.Description
DC.Subject
General. Keyword or Classification with Classification.Purpose equals "Discipline" or "Idea".

20. Mapping LOM element to DC element set (cont’)
DC.Coverage
General.Coverage
DC.Type
Educational.LearningResourceType
DC.Date
LifeCycle.Contribute.Date when LifeCycle.Contribute.Role has a value of "Publisher".
DC.Creator
LifeCycle.Contribute.Entity when LifeCycle.Contribute.Role has a value of "Author".
DC.OtherContributor
LifeCycle.Contribute.Entity with the type of contribution specified in Role.
DC.Publisher
LifeCycle.Contribute.Entity when LifeCycle.Contribute.Role has a value of "Publisher".

21. Mapping LOM element to DC element set (cont’)
DC.Format
Technical.Format
DC.Rights
Rights.Description
DC.Relation
Relation.Resource.Description
DC.Source
Relation.Resource when the value of Relation. Kind is "IsBasedOn".
Source: (IEEE, 2002)

22. Value of metadata in e-learning
Good metadata
Facilitates accessibility
Reusability
Affordability
Manageability
Durability
Scalability
Adaptability
Accessibility- metadata should make it possible for users to access learning content stored remotely
Reusability – re use of learning objects- Return on investments for institutions
Affordability- metadata allows integration with various software- results in learning effectiveness and reduction in costs
Manageability – metadata should make it possible for the system to track appropriate information about the user and content
Durability – content produced once and used many times in different platforms without duplication of effort, economic benefits
Scalability – reduces redundancy & duplication of effort
Adaptability – Appropriate metadata will allow learners and instructional designers to choose learning objects that can be adapted to specific instructional purposes

23. Conclusion
The growth in ICT’s in higher education calls for relevant metadata standards
Metadata should aim for return on investment for higher education institutions
Improvement in organizational quality and efficiency
Improve learner efficiency in retrieving and evaluating learning objects

24. References
Bird, S. & Simons, G The OLAC metadata set and controlled vocabularies. In: Association for Computational Linguistics. ACL-2001 Workshop on Sharing Tools on Resources. [Online]. Toulouse, France 6-11 July ACL. Available at:
[Accessed 20 July 2010].
CDP Metadata Working Group Dublin Core metadata best practices. Version [Online]. Available at: [Accessed 20 July 2010].
Dublin Core Metadata Initiative Dublin Core metadata element set. Version 1.1 [Online]. DCMI. Available at: [Accessed 20 July 2010].
Dublin Core Metadata Initiative Using Dublin Core. [Online]. DCMI. Available at: [Accessed 20 July 2010].
IEEE LTSC Draft Standard for Learning Object Metadata (IEEE [Online]. Available at: [Accesssed 27 October 2010}
JISC Digital Media Metadata and digital images. [Online]. In: Still images: managing your digital resources. JISC Digital Media. Available at: [Accessed: 21 July 2010].

25. References (cont.)
Florea, N.V New forms of human resources development: e-Learning in education. Buletinul, vol. 62 pp.
JISC Digital Media Controlling your language: a directory of metadata vocabularies. [Online]. In: Cross media: managing your digital resources. JISC Digital Media. Available at: [Accessed: 21 July 2010].
Krull, G.E An investigation of the development and adoption of educational metadata standards for the widespread use of learning objects. Masters thesis, Rhodes University.
Miller, S.J Metadata for digital collections: an online workshop. [Online]. University of Wisconsin-Milwaukee, School of Information Studies. Available at: [Accessed 20/07/2010].
Mwanza, D. & Engeström, Y Managing content in e-learning environments. British Journal of Educational Technology, Vol, 36 no. 3 pp
Taylor, C An Introduction to metadata. [Online]. Brisbane, Australia: University of Queensland. Available at: [Accessed: 21 July 2010].

26. Thank you