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Metadata Standards for Open Educational Resources

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One of the most important components of an e-learning system is the learning material. The widespread adoption of e-learning has led to the development of many learning object repositories that store high quality learning materials specifically created for e-learning. Resource discovery of learning materials can be made effective by semantically tagging them with standard metadata. This paper highlight the use of metadata in e-learning systems with a review of the most widely used metadata standards for Open Educational Resources.
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METADATA STANDARDS FOR OPEN EDUCATIONAL RESOURCES
Manu C.1 and Mohamed Haneefa K.2
1 Research Scholar, University of Calicut, Kerala, E- mail: cvmanu@gmail.com
2Assistant Professor, Department of Library & Information Science, University of Calicut,
Kerala, E-mail: dr.haneefa@gmail.com
Abstract
One of the most important components of an e-learning system is the learning material.
The widespread adoption of e-learning has led to the development of many learning object
repositories that store high quality learning materials specifically created for e-learning.
Resource discovery of learning materials can be made effective by semantically tagging
them with standard metadata. This paper highlight the use of metadata in e-learning
systems with a review of the most widely used metadata standards for Open Educational
Resources.
Keywords: Metadata Standards, Open Educational Resources, Learning Objects, E-
learning, Learning Resource Metadata Initiative, Dublin Core, IEE LOM
1. Introduction
E-learning has emerged as an important learning platform to facilitate and enhance the
process of learning through the application of Information and Communication
Technologies. Online learning object repositories are the major resources for e - learning.
The most important component of any e-learning system is the learning object. Learning
Object repositories store and provide access to quality learning materials which are
specifically created for e-learning.
An e-learning system should ensure the maximum use of these learning objects through
efficient retrieval mechanisms. To increase the visibility of learning objects it should be
properly tagged with a set of metadata which describes educational artifacts such as the
subject content, intended user group etc. Metadata is fundamental to effective retrieval and
use of digital materials, as well as the organization, preservation, and management of
those materials in the digital environment. To fulfill the above purposes different types of
metadata can be used. Descriptive metadata can be used for describing or identifying
information resources. Structural metadata documents relationships among objects.
Administrative metadata provides information to help manage a resource and “Use
metadata” tracks the level and type of use of information resources (Gilliland, 1998).
However, sharing and reuse of learning objects across various repositories or learning
management systems can be achieved only by using a common metadata standard for
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describing the learning object. For the description of learning objects there are several
metadata standards available and the selection of an ideal metadata standard is very
important for ensuring maximum visibility and interoperability between learning object
repositories. Use of metadata standards, automatic metadata generation, staff capacities
and interoperability are some important areas of research related to metadata and
metadata management.
2. Open Educational Resources
In 2002, UNESCO convened a group of academics to study impact of the
OpenCourseWare initiative of the Massachusetts Institute of Technology (MIT) on higher
education institutions in developing countries. The forum coined the term ‘Open
Educational Resources (OER)’ and they defined it as “The open provision of educational
resources, enabled by information and communication technologies, for consultation, use
and adaptation by a community of users for noncommercial purposes” (UNESCO, 2002).
In its simplest form, the concept of Open Educational Resources describes any
educational resources (including curriculum maps, course materials, textbooks, streaming
videos, multimedia applications, podcasts, and any other materials that have been
designed for use in teaching and learning) that are openly available for use by educators
and students, without an accompanying need to pay royalties or license fees (Butcher,
2011).
The major difference between OER and any other educational resource is its license.
Thus, an OER is simply an educational resource that incorporates a license that facilitates
reuse, and potentially adaptation, without permission from the copyright holder.
3. Importance of Metadata in E-Learning Systems
ALCTS (Association for Library Collections and Technical Services) Task Force on
Metadata (2000) defines metadata as “structured, encoded data that describe
characteristics of information-bearing entities to aid in the identification, discovery,
assessment, and management of the described entities”. Moreover metadata is also a
tool for the management of information resources, whether they are electronic and
available on the Internet or in physical format; metadata enables the management of the
lifecycle wherein the resources are created, modified and used.
One of the requirements for a federated information system is interoperability, the ability of
one computer system to access and use the resources of another system (Komatsoulis,
2008). The interoperability between e-learning systems will ensure wider reach of the
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learning objects to the intended users. Properly provided metadata can act as a key to
interoperability (Haynes, D, 2004).
Similar to traditional cataloging and indexing, metadata performs three main functions. It
supports resource discovery, locates the specific resource by inclusion of a digital
identifier, and organizes electronic resources into collections bringing similar resources
together and distinguishing dissimilar resources. In addition it provides information needed
to administer and manage the collection. Technical metadata is needed to allow digital
objects to be re-presented in new technical environments.
A metadata scheme has three components – semantics, content and syntax. An extension
adds elements to an existing scheme to describe a particular resource type, handle
material on a particular subject, or address the needs of a particular user community.
Profiles are subsets of a larger scheme that are implemented by a particular user
community. Metadata can be embedded in an electronic resource or stored in a separate
file.
4. Important Educational Metadata Standards
Metadata standard is the set of metadata elements and rules for their use that have been
defined for a particular purpose. In common usage, the terms scheme, schema and
standard are used interchangeably. A metadata scheme is the set of descriptor types
available to be applied to information. Numerous standard schemes have been developed
to address specific information use and management needs. These standards have
emerged from the needs of specific interest groups to standardize how they classify
information. Many different metadata schemes are being developed in a variety of user
environments and disciplines.
Several educational metadata standards have been proposed over time in order to better
describe learning objects. A widely adopted metadata element set for this purpose is IEEE
Learning Object Metadata (LOM), a standard which has been designed especially for the
description of educational resources. Apart from LOM, other well known metadata
standards designed to be used in the field of education are IMS and Dublin Core. The
latest entrant in this category is the Learning Resource Metadata Initiative (LRMI) which is
an extension of the Schema.org.
It is observed that, in practical scenarios a single metadata schema may not be adequate
for efficiently describing learning objects. In order to overcome this problem, the use of
“Application Profiles” is proposed. According to Rachel Heery and Manjula Patel (2000)
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application profiles consist of data elements drawn from one or more namespace schemas
combined together by implementors and optimised for a particular local application.
Application profiles are useful as they allow the implementor to declare how they are using
standard schemas. The goal is to efficiently fulfill the application's special needs and to
retain interoperability with its base schema. Therefore, applications that utilize application
profiles can benefit by exploiting the features of an existing schema and by enriching them
with desired characteristics. Some popular application profiles are CanCore and Sharable
Content Object Reference Model (SCORM).
4.1 The IEEE Learning Object Metadata
The IEEE 1484.12.1 2002 Standard for Learning Object Metadata is an internationally
recognised open standard published by the IEEE Learning Technology Standard
Committee (IEEE LTSC) for the description of learning objects. IEEE 1484.12.1 is the first
part of a multipart standard, and describes the LOM data model. The LOM data model
specifies which aspects of a learning object should be described and what vocabularies
may be used for these descriptions; it also defines how this data model can be amended
by additions or constraints.
For this standard, a metadata instance for a learning object describes relevant
characteristics of the learning object to which it applies. The conceptual data schema
specified in this part permits linguistic diversity of both learning objects and the metadata
instances that describe them. This conceptual data schema specifies the data elements
which compose a metadata instance for a learning object.
The LOM defines the minimal set of attributes to manage, locate and evaluate learning
objects. These attributes or Data Elements are grouped in to nine categories:
1. General category groups the general information that describes the learning
object as a whole.
2. Lifecycle category groups the features related to the history and current state
of this learning object and those who have affected this learning object during its
evolution.
3. Meta-Metadata category groups information about the metadata instance itself
(rather than the learning object that the metadata instance describes).
4. Technical category groups the technical requirements and technical
characteristics of the learning object.
5. Educational category groups the educational and pedagogic characteristics of
the learning object.
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6. Rights category groups the intellectual property rights and conditions of use for
the learning object.
7. Relation category groups features that define the relationship between the
learning object and other related learning objects.
8. Annotation category provides comments on the educational use of the learning
object and provides information on when and by whom the comments were
created.
9. Classification category describes this learning object in relation to a particular
classification system
Within each category is a hierarchy of data elements to which the metadata values are
assigned. Examples of learning-related metadata elements found in the Education
category are Typical Age Range (of the intended user), Difficulty, Typical Learning Time,
and Interactivity Level.
IEEE 1484.12.3 - 2005 Standard for eXtensible Markup Language (XML) Schema Binding
for Learning Object Metadata Data Model defines how LOM records should be
represented in XML; it does so not by providing a single XML Schema but by providing
several options which can be tailored to particular application profiles of the data model.
4. 2 IMS Metadata
The IMS Global Learning Consortium (http://www.imsglobal.org/) develops and promotes
the adoption of open technical specifications for inter operable learning technology. Their
Meta-Data Information Model Specification is based on the IEEE LOM scheme with only
minor modifications. The latest version of the IMS Learning Resource Meta-Data
specification (Version 1.3) adopts the IEEE data model and XML binding, and provides
best practice guidelines for their use. These guidelines allow the software developers and
the implementers to create instructional materials that are inter operable across authoring
tools, learning management systems, and run time environments.
4. 3 Dublin Core
The Dublin Core Metadata Initiative (http://dublincore.org/) is an open forum engaged in
the development of interoperable online metadata standards that supports a broad range
of purposes and business models. The Dublin Core standard includes two levels: Simple
and Qualified. The simple Dublin Core contains fifteen elements. The elements are Title,
Subject, Description, Type, Source, Relation, Coverage, Creator, Publisher, Contributor,
Rights, Date, Format, Identifier and Language. The qualified Dublin Core includes three
additional elements Audience, Provenance and RightsHolder, as well as a group of
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element refinements (also called qualifiers) that refine the semantics of the elements in a
way that may be useful in resource discovery.
The Dublin Core metadata contains metadata elements useful for general purpose
applications but it does not contain attributes describing the pedagogical perspective of a
document. In order to cope with educational concerns, DC-Education Application Profile
has been proposed.
The DC Education Working Group has proposed a schema for describing educational
resources. Along with that a joint DCMI/IEEE LTSC Task Force was also constituted. The
recommendation of the DC Education Working Group suggests a schema incorporating:-
Various standard DC elements and recommended qualifiers
DC Education ‘namespace’ (domain specific) extensions such as
DCEducation Element: audience
DCEducation Audience qualifier: mediator
DCEducation Element: standard
DCEducation Standard qualifier: identifier
DCEducation Standard qualifier: version
DCEducation Relation qualifier: conforms to
Various IEEE Learning Object Metadata (LOM) elements such as
InteractivityType
InteractivityLevel
TypicalLearningTime
We can see from this schema extract that it consists of DC ‘standard’ elements, domain
specific additions to recommended standard DC elements, and particular elements from
name spaces such as IEEE LOM.
4.4 Learning Resource Metadata Initiative
In June 2011, major search engines Bing, Google, and Yahoo (later joined by Yandex)
formed Schema.org to create a standard method of tagging webpages across the Internet
with descriptive and semantic metadata, sometimes called microdata. The goal is to create
a standardized schema for webmasters to use for markup to ensure the maximum benefit
for their efforts and to aid users who utilize these tags in online search queries. On - page
markup helps search engines understand the information on web pages and provide richer
search results. A shared markup vocabulary makes easier for webmasters to decide on a
markup schema and get the maximum benefit for their efforts. Search engines want to
make it easier for people to find relevant information on the web. Markup can also enable
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new tools and applications that make use of the structure.
The Learning Resource Metadata Initiative (LRMI) is a project led by Creative Commons
(CC) and the Association of Educational Publishers (AEP) to establish a common
vocabulary for describing learning resources. The project has developed a standard
metadata framework for tagging learning resources online. The vocabulary is the first
independently developed industry-specific framework addressing education that is
designed to work with schema.org, thereby improving the practical search and discovery of
learning resources online. A common framework for tagging and organizing learning
resources will increase the interoperability and transparency of OER repositories.
LRMI Specification
The LRMI specification is a collection of properties to describe educational resources. It
builds on the extensive vocabulary provided by Schema.org, and predominantly,
Schema.org/CreativeWork and the LRMI-created Educational Audience. Version 1.1 of the
LRMI specification has been accepted into Schema.org with the exception of useRightsUrl.
Different properties of learning resources as defined by the LRMI specification Version 1.1
is shown in the Table 1.
Schema.org already defines the metadata schema for basic information about material on
the Web, such as a “Creative Work” in the form of a “Book,which has metadata like
author, publisher, datePublished, etc. It also defines specific metadata for types like Article,
ImageObject, AudioObject, VideoObject, and so forth. LRMI identified five properties that
are already covered by schema.org which are relevant to learning objects. The properties
already defined by schema.org and identified by LRMI as relevant to learning objects are
shown in the Table 2.
LRMI extends the work being done by Schema.org that aims to standardize website
markup in general. LRMI can become the de facto standard for tagging educational
content online, it’s what the search engines will look for when they crawl the web for
learning resources.
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Table 1
LRMI specification - Version 1.1
Property
Expected
Description
educationalRole schema.org/Text
The role that describes the target
audience of the content.
educationalAlignment
schema.org/Align
mentObject
An alignment to an established
educational framework.
educationalUse schema.org/Text
The purpose of the work in the
context of education. Eg:
“assignment” , “group work”
timeRequired
schema.org/
Duration (ISO
8601)
Approximate or typical time it
takes to work with or through this
learning resource for the typical
intended target audience. Eg:
“P30M” , “P1H25M”
typicalAgeRange
schema.org/Text
The typical range of ages the
content’s intended end
user. Eg:
“7-9″ , “18-”
interactivityType
schema.org/Text
The predominant mode of
learning supported by the
learning resource. Acceptable
values are active, expositive, or
mixed. Eg: “active” , “mixed”
learningResourceType
schema.org/Text The predo
minant type or kind
characterizing the learning
resource. Eg : presentation” ,
“handout”
useRightsURL
schema.org/URL
The URL where the owner
specifies permissions for using
the resource.
Eg:“http://creativecommons.org/li
censes/by/3.0/“
isBasedOnURL
schema.org/URL
A resource that was used in the
creation of this resource. This
term can be repeated for multiple
sources.
Name schema.org/Text The title of the resource.
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Table 2
Properties of learning resource that are currently covered by Schema.org
Property
Expected
Description
Name schema.org/Text The title of the resource.
About schema.org/Text The subject of the content.
dateCreated schema.org/Date
The date on which the resource
was created.
author schema.org/
Person The individual credi
ted with the
creation of the resource.
publisher schema.org/
Organization
The organization credited with
publishing the resource.
inLanguage schema.org/
Language
The primary language of the
resource.
5. Conclusion
The development and adoption of new xml schema based metadata standards shows the
influence that search engines, like Google, have in making open educational resources
discoverable. In this new scenario it becomes the responsibility of the individual and the
institution to ensure the OERs they create are appropriately described and that metadata
is optimised for search and retrieval. The better an OER is tagged with proper metadata
the more it reaches to the intended audience.
The development of Linked Data technologies based on RDF (Resource Description
Framework) specifications has also made its impact on the way in which educational
resources are described for the semantic web. Dublin Core vocabularies have been
represented in an RDF Schema and hence Dublin core continues as an important
metadata standard for describing educational resources.
As all the major search engines are using schema.org for semantic indexing and LRMI
specification is accepted into Schema.org it seems that LRMI will soon become the de
facto metadata standard for Open Educational Resources. As search engines begin using
the LRMI specification and as a critical mass of educational content is tagged in a
consistent manner, filtering this content will become substantially easier, allowing
educators, students, and others to find relevant educational resources.
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... The Learning Resource Metadata Initiative (LRMI) started a project with the same name in 2011 to establish a vocabulary for describing learning resources (see https://dublincore.org/about/lrmi/). For several years, the advantages of providing metadata as LRMI have been discussed in the community, for example, in (Haneefa & Chembrakuzhi, 2014). LRMI was not designed to describe objects with a monolithic set of metadata but rather for the use of socalled microdata. ...
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To provide Open Educational Resources (OER) according to the recognised FAIR principles (improve Findability, Accessibility, Interoperability, and Reuse of digital assets), it is necessary to describe the educational material by means of meaningful metadata. There are conflicting demands to comply with. On the one hand, the educational resources should be described in as much detail as possible for accurately fitting search results. On the other hand, only strictly necessary information should be obligatory to keep the obstacles for authors as low as possible. An additional goal is to allow easy connection between repositories, thus allowing federated search and harvesting of metadata, for example, by search engines or other interested parties. Operators of OER repositories from several federal states in Germany (HOOU, OERNDS, ORCA.nrw, VCRP, VHB, ZOERR) have developed a metadata profile focussing on OER in the context of higher education. The initiators strive to reach the mentioned objectives and to establish a standard in the field. The metadata profile is based on the well-established Learning Object Metadata Standard (LOM). The chapter describes the decision process and why certain choices are made to reach the intended goals. Furthermore, the importance of editorial supervision for a sound quality of the material and metadata will be discussed. The chances and challenges are illustrated based on practical experiences with the establishment and daily operation of the Zentrales OER Repositorium der Hochschulen in Baden- Württemberg (ZOERR) .
... General OER Recommender systems [11], [12], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [30], [30], [30], [30], [42] , [44], [45] , [46], [49], [50], [51], [52], [53], [54], [56], [57], [58], [59] [100], [104], [111], [113], [114], [126], [127], [129], [131] OER in MOOCs [28], [60], [55], [61], [62], [13], [16] Solutions for teaching purposes or general solutions that could be applied to teaching purposes (Teacher oriented) OER Recommenders for teachers or could be adopted for teaching purposes [34], [35], [36], [17], [37], [31], [20], [36], [22], [39], [24], [25], [26] [27], [40], [29], [41], [42], [43], [44], [45], [46], [47], [31], [48], [49], [50], [51], [52], [53], [54], [124], [125], [128], [130] Generalities Literature reviews, SLR, surveys,, [63], [64], [65], [66] , [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78] ; [79], [80], [81], [82], [83], [84, [85], [86], [87], [88], [89], [90], [91], [92], [93] ; [94] ; [95] ; [96] ; [97], [98], [99], [101], [102], [103], [105], [106], [107], [108], [109], [110], [112]; [115], [6] ...
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background: In recent years, recommender systems (RS) have grown in popularity among learning and education stakeholders, while open educational resources (OER) have begun to be deployed to improve the education field. The selection of OERs should not be haphazard; rather, it should be based on the learning objectives and (RS) commonly utilized to overcome the abundance of OER. Objective: The aim of this paper is to examine the current advances in OER recommenders and the different commonly used recommendation approaches and technical features, to position our future research alongside the existing. Method: A systematic literature review with a deductive approach using the grounded theory technique, combining quantitative and qualitative analysis by adopting open coding (inductive and deductive) for content analysis. Databases: we employed Google Scholar as a search engine to crawl data. Results: The findings are presented according to the (Bernard, H. Russell .2000) process. We present the results of the analysis using quotes from interviews that illuminate the theory (exemplars). Conclusion: The review reveals an emerging interest in the area; nevertheless, hybrid interactive systems; chatbot-based, dedicated to course creators are lacking. Further and future research is needed
... Some identified metadata standards for this purpose are Dublin Core namespace and legacy namespace, IEEE LOM (IEEE, 2002), ISO/IEC 19788-5 Metadata Learning Resource (MLR), Learning Resource Metadata Initiative (LRMI), Dublin Core Education Application Profile, SCORM Metadata and CanCore Hilera & Hoya, 2010;OER-C, 2014;Pons et al., 2011;Temesio, 2015). Although there are different metadata standards, IEEE LOM is a widely adopted metadata element set to describe learning objects (Chembrakuzhi & Haneefa, 2014;Santos-Hermosa et al., 2017). On the flip side, some of these standards are fully compatible with the IEEE LOM standard (Cuspoca et al., 2020;Roy et al., 2010). ...
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One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service-Oriented Architecture (SSOA) for cancer research by the National Cancer Institute's cancer Biomedical Informatics Grid (caBIG).
A basic guide to open educational resources (OER) Vancouver: Commonwealth of Learning
  • A Kanwar
  • S Uvalic-Trumbic
  • N Butcher
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Available at http://www.libraries.psu.edu/tas /jca/ccda.old/tf-meta6 Forum on the impact of Open Courseware for higher education in developing countries final report
Task Force on Metadata Final Report (2000). Available at http://www.libraries.psu.edu/tas /jca/ccda.old/tf-meta6.html UNESCO (2002). Forum on the impact of Open Courseware for higher education in developing countries final report. Retrieved from http://unesdoc.unesco.org/images/0012/ 001285/128515e.pdf
Retrieved from http://cancore.athabascau.ca/en/ DCMI education community. Retrieved from http
  • Cancore Metadata Initiative
Cancore Metadata Initiative. Retrieved from http://cancore.athabascau.ca/en/ DCMI education community. Retrieved from http://dublincore.org/groups/education/
Sharable Content Object Reference Model (SCORM)
  • Schema
  • Faq
Schema.org FAQ. Retrieved from http://schema.org/docs/faq.html. Sharable Content Object Reference Model (SCORM). Retrieved from http://www.adlnet.org/scorm/