A methodology for defining essential metadata to catalog learning objects in repositories

8/7/2019 A methodology for defining essential metadata to catalog learning objects in repositories

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A methodology for defining essential metadata to cataloglearning objects in repositories

Avanilde Kemczinski, Srgio Vincius de S Lucena, Filipe Ventura Woll,Marcelo da Silva Hounsell, Edson Murakami

Computer Science Department (DCC)Universidade do Estado de Santa Catarina(UDESC) Joinville,SC - Brazil

Abstract. The use of metadata represents the cataloging of a Learning Object (LO) to formalize and structure itsinformation standardization. This article presents a methodology to select a number of essential metadata, which arecapable of meeting specific repository criteria without compromising the search engine issues and the interoperability.

Keywords: Repositories, Metadata Standards, Learning Objects. PACS: 01.40.Ha.

INTRODUCTION

As the Internet grows wide and the indexing technologies are improved, the need for cataloging the digitalresources on the network crops up. For this purpose, the metadata standards appear. Metadata can be defined as"data about data" in such a way that they are able to characterize other data [1]. They describe the digital objects byattributes, giving them consistent and real meaning. According to [2], metadata is used to identify resources, helpingto filter a search, and facilitating the recovery of a record.

According to [3], metadata are managed as elements within the repository, they're labeled and must have acontext. The context has a name and settings that can be specified in one or more languages that define the scopeand meaning of each type of metadata. It may contain information about areas, systems, databases, modeling or anyother environment variable determined by the owner of record.

Currently, the metadata have a high degree of application, because they allow the development of innovativeapplications and can be employed in various areas such as: Geographic Information Systems (GIS), Digital TV,Information Systems in general, Web Services and Semantic Web [3]. Some forms of using metadata include [3]: (i)interoperability between distributed objects on different platforms, (ii) standardized data exchange betweendistributed components, (iii) standardization of Learning Objects (LOs); (iv) services description and multimediacontent, and; (v) representation of contextual information.

A metadata schema is a set of attributes defined to suit a particular purpose. By identifying problems in storingand retrieving information by lack of standardization, several schemes were created to serve different purposes, and

were called metadata standards [3].This article is structured as follows: section 2 describes metadata standards and its applicability; section 3

presents the methodology for obtaining a minimal amount of metadata, which refers to the purpose of this article;section 4 presents an application of this methodology, which can be though of as a metadata elements approvalprocess for a thematic repository. After this, section 5 addresses questions on essential metadata approving process.Section 6 outlines the conclusions of this work.

2. METADATA STANDARDS

A standard is a formal document that specifies a set of metrics and technical processes that can be followed withthe aim of assuring quality to a product. In this sense, the adoption of a metadata standard is intends to provide


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definitions and to form a mechanism to automate registering features and cadastral data in a standardized andconsistent way [4]. Its use allows to define, to catalog, to discipline and to describe the contents of Learning Objects(LO), resulting in the database standardization and quality expansion and also in the reuse of LO [5].

One of the main reasons for the existence and use of metadata standards is related to the management andbroadcasting of information. The scientific communities have developed metadata standards so that their scientificproduction can be disseminated through information mechanisms like the Internet, libraries and digital databases, aswell as through electronic journals [7].

The importance of interoperability of information between producer communities and / or users of LOs has beenhighlighted [7], since by sharing data (through metadata standards) it minimizes the time in developing researchabout the production of such technology, as well as shortens the processing of generated information.

Several organizations have established standards of metadata for LOs, leading to various existing standards,among them the following stands out: the LOM - Learning Object Metadata [9]; the IMS-LD - InstructionalManagement System - Learning Design [10]; the ARIADNE - Alliance of Remote Instructional Authoring and Distribution Networks for Europe [11]; the SCORM - Sharable Content Object Reference Model [12]; the DCMI -Dublin Core Metadata Initiative [13]; the CanCore - Canadian Core Learning Metadata Aplicatiom Profile [14]; theOBAA - Agent based Learining Objects [15], and; the MTD-BR Brazilian Thesis and Dissertations Metadata [16].

Based on these standards, were adopted the methodology cited by[17], performing an expansion in the datasurveyed, with the intent to approve the selected metadata for cataloging LOs in the repository of LO to theInformation Area, named ROAI.

3. A METHODOLOGY FOR DEFINING ESSENTIAL METADATA

The methodology that will be described was based on the verification of which metadata are the most usedwithin all above mentioned standards as well as which are most used to catalog digital artifacts in repositories.According to [17], there is no mention in the literature about what particular metadata is more efficient than others.Thus, it is possible to follow different ways to get a set of metadata to catalog LO in a given repository. Therefore,one can adopt an existing and already elaborated metadata; others can specific a metadata schema based on theneeds and resources of the repository or even; some can adopt a minimum quantity of basic metadata. For the later amethodology for the selection of metadata to ROAI will be described.

Referring back to the standards above mentioned, the metadata definition methodology was to check whichmetadata are more commonly used by the standards and which are more commonly used for cataloging LOs inrepositories. This definition intends to obtain a minimum quantity of metadata but of higher frequency of use.

The methodology for obtaining essential metadata was realized in 4 steps [17]:a)

Step 1: A comparative process in order to highlight the metadata that are used by all standards taken intoaccount;

b)

Step 2: An analysis on multiple repositories in order to see which pieces of data are commonly used alongwith a literature review in order to discover the existence of similar work;

c)

Step 3: Union of the metadata listed in Step 1 with those data resulting from Step 2. Thus, resulting in thepredominant metadata present at both standards and repositories;

d)

Step 4: Verification of the most appropriate metadata standard that includes all predominant metadatafound in previous step.

At the end, essential metadata would be found for that type of repository, as the methodological process flowdiagram illustrates (see Figure 1).


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Figure 1. Fluxogram of the methodological process to defining Essential Metadata [17].

This "Essential Metadata" methodology has been used [17] to identify the metadata to be applied to theRepository of Learning Objects for the Informatics Area of Universidade do Estado de Santa Catarina (UDESC),called ROAI. This process was applied to obtain and subsequently validate the minimal metadata needed to cataloga LO in the repository without compromising filtering, searching and interoperability issues.

4. METHODOLOGY APLICATION

The methodology described above was used to approval the "essential metadata" obtained by [17] in aresearch entitled Learning Objects Repository for Informatics Area (ROAI ). The essential metadata obtained areshown in Table 1:

Category Metadata1 General 1.1.2 Entry

1.2 Title1.3 Language1.4 Description

2 Life Cycle 2.3.2 Author2.3.3 Date

4 Technical 4.1 Format4.2 Size


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5 Educational 5.2 Type of Learning Resource6 Rights 6.3 Description

Table 1: Essential Metadata for ROAI [17].

The step-by-step application of the methodology will be detailed in the following sessions.

4.1 The Most Used Metadata by the Standards

The first step is to perform a comparison between the metadata standards previously identified. This processverifies which are the metadata that all standards have in common. The standards searched and compared for thiscase were the CanCore, DCMI, ADL-SCORM, ARIADNE, IMS-LD, IEEE-LOM, MTD-BR, OBAA. Listed out allthe metadata for each standard, we compared which metadata elements are presents in all standards. Among thosestandards the OBAA is the one who contains the biggest quantity of metadata items. It encompasses all metadatafrom the IEEE-LOM once it is a proposal of extension to it (it adds two categories of metadata, which wereexcluded from the analysis because they are not part of the other standards). To help find the commonplace metadatabetween the standards, categories according to the IEEE-LOM were preferred. These categories are presented inTable 2.

Category DescriptionGeneral Groups general information that describes the LO as a whole . Lifecycle Describes the history and current state of this LO and those entities that have affected the

LO during its evolution. Meta-metadata Describes the metadata record itself (rather than the LO that this record describes).

Technical Describes the technical requirements and characteristics of the LO. Educational Describes the educational or pedagogic characteristics of the LO.

Rights Describes the intellectual property rights and conditions of use for the LO. Relation Defines the relationship to other LO, if any.

Annotation Provides comments on the educational use of the LO, and information on when and by

whom the comments were created. Classification Describes where the LO falls within a particular classification system.

Table 2: Categories of data elements of LOM Base Schema.

Table 3 compares the standards and their metadata. The legend used for comparison was the following:

(Y) inform that the standard also uses the described item;

(N) inform that the standard does not use the described item;

(O) indicates that the standard does not require the use of this item, in other words, its use is optional.

StandardsCategory

IEEE-LOM / IMS Learning Design CanCore DublinCore

SCORM AriadneMTD-

BROBAA

1 General This category, derived from the Dublin Core standard, group general information describingthe LO as a whole, and has the following data elements:

1.1 Identifier It is unique identifier of the learning object, and consists of two sub-elements:

1.1.1 Catalog Informs the name or identification of thecataloging scheme for this entry. Y N Y Y Y Y

1.1.2 Entry The value of the identifier which identifiesthe cataloging scheme that designates thisLO.

Y Y Y Y Y Y


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1.2 Title Name given to the LO.Y Y Y Y Y Y

1.3 Language Language used in learning object tocommunicate with the user. Y Y Y Y Y Y

1.4 Description Textual description about the LO.Y Y Y Y Y Y

1.5 Keywords Keywords describing the topic or subject of the LO. Y Y Y Y Y Y

1.6 Coverage The time, culture, geography or region towhich this LO applies to. N Y O N Y Y

1.7 Structure Underlying organizational structure of thisLO. The values of this metadata can be:atomic, collection, networked,hierarchical or linear.

N N O N Y Y

1.8AggregationLevel

The functional granularity of the LO. Theaggregation level can has the values below:1, 2, 3 e 4.

Y N O Y Y Y

Table 3:Comparison of general elements of category of LOM with other standards.

After mounting various comparative tables like this (one for every IEEE-LOM category), it resulted in the ninemetadata shown in Table 4 which are present in all standards (showing legend Y or, at least, O).

Category Metadata

1 General

1.1.2 Entry1.2 Title1.3 Language1.4 Description

2 Lifecycle 2.3.2 Entity2.3.3 Date4 Technical 4.1 Format5 Educational 5.2 Learning Resource Type6 Rights 6.3 Description

Table 4: The metadata most commonly used by the standards

The following procedure was the analysis of the data most commonly used by various repositories found in theliterature that is described following.

4.2 The Most Commonly Used Metadata by the Repositories

The analysis of the metadata that is most commonly used was based on a comparison between 11 repositories(national and international), these being: Economics Network [33], CAREO [23], ARIADNE KPS [24], Celts [25],Universit en Ligne [32], MERLOT [26], CART [27], LabVirt [28], BIOE [31] OE /e-tools [29] and Interred [30].For this analysis data already available [17] was used and the BIOE was added to it.

For the purposes of understanding, the Canadian Advisory Committee (CAC) [18] performed this analysis in 5of the 11 repositories listed above, checking out the metadata that is present in at least 60% of these repositories, inother words, at least 3 of the total of 5. This sort of criteria was used to carry out the same comparison with theother 6 repositories, this time searching for the metadata to be present in most of these 6, in other words, in at least4).

As a result, it was found that the following metadata are the most common among the repositories, being presentin 63,63%, of the repositories besides those analyzed in the study of the CAC.

When performing the intersection of the common metadata in most repositories, the following metadata wasobtained (Table 5):


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Category Metadata

1 General 1.2 Title

1.4 Description2 Lifecycle 2.3.2 Entity2.3.3 Date

4 Technical 4.1 Format4.3 Location5 Educational 5.2 Learning Resource type

Table 5: The most commonly used metadata by repositories

4.3 Predominant Metadata

The definition of predominant metadata refers to the step 3 of the methodology. The predominant metadata arethe metadata that are most used in the standards and the repositories. To specify them, the union of the mostcommonly used metadata in standards (Table 4) and the most commonly used metadata by repositories (Table 5).The following predominant metadata was obtained (see Table 6).

Category Metadata1 General 1.1.2 Entry

1.2 Title1.3 Language1.4 Description

2 Lifecycle 2.3.2 Entity2.3.3 Date

4 Technical 4.1 Format4.2 Size4.3 Location

5 Educational 5.2 Learning Resource Type6 Rights 6.3 Description

Table 6: Predominant metadata

4.4 The Choose of the Metadata Standard

The choice of a metadata standard is the one that includes the predominant metadata found so far. To do it, theamount of metadata in every standard which matches the predominant metadata, or not, was analyzed. The relationof metadata that make up each standard can be observed in Figure 2.

In figure 2 you can see that the Dublin Core standard is the one with the lowest "waste", based on a total of 15metadata and among them, 10 are shared by the others. For the purpose of comparison, the LOM standard has 11 outof 58 metadata in common with the other standards. This means that only 18.96% of its metadata would be useful, if selected. By listing the use of these standards among all researched, it can be realized that Dublin Core is the onethat gives a better usage of its metadata. Only 5 of its metadata do not belong to the predominant metadata, whileother standards show a very high number of missing metadata out of this group.

Considering that this work is also searching for the smaller standard that fits all, it is concluded that the DublinCore is in compliance with the expectations of this work by providing a metadata that facilitate the task of the userto fill a small and accurate data needed for cataloging LOs. Thus, through the proposed methodology, the DublinCore standard was chosen to the ROAI repository.


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Figure 2: A comparison of metadata standards

The original purpose of the Dublin Core is to define a minimum set of elements capable of describing digitalartifacts available on the Internet [8]. This set aims to be as simple as possible for better understanding and to beeasily used by a lot of authors and providers who contribute on the Internet.

4.5 Essential Metadata

By obtaining the predominant metadata, one acquires a minimal amount of metadata which enables to propose a

minimal set of metadata for a given repository. These essential metadata presented in this article are results of themethodology applied, based on standards and repositories analyzed. Below follows the structure in mental map(Figure 3) for the metadata obtained.

Figura 3: Mental map of the Essential Metadata of ROAI


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5. DISCUSSIONS

The importance of using metadata Standards raises several issues that need to be addressed. Some authors

criticize the use of a minimal amount of metadata because of the limited amount of information about the document(file) available that you want in the repositories. However, there are studies in the literature that aim to specify aminimum amount of metadata that a repository needs to have.

There is, for example, the ISO 19115, which sets a minimum amount of metadata (core metadata) for cataloginginformation [20]. This standard proposes seven mandatory and 14 optional metadata [21]. Besides, the Dublin Coreitself is based in the ISO 15836-2003 [21]. Another work that need to be highlighted is [19] which proposes a set of metadata for functional LO (software) in which these relate to digital artifacts whose functionality enable theinteraction between entities, among them artifacts stand out software and software components.

6. CONCLUSION

This paper surveyed metadata standards and repositories and proposed a methodology that takes this information

and composes a minimal set of metadata items to a specific type of repository. By applying the methodology, it ispossible to reach a satisfactory amount of metadata that does not compromise the search or even interoperabilityissues. This methodology seeks to provide procedures for the selection of metadata, based on the most frequentlymetadata used among all repositories and standards. It can be applicable when there is a need for integrationbetween repositories that work, for example, using federated search engines. In this case, it is possible to make acomparative evaluation among the repositories which are going to work together in order to find a minimal amountof metadata that is the intersection of all the metadata repositories involved. The methodology proposed in this paperwould help find a suitable essential metadata to be used.

ACKNOWLEDGMENTS

The authors would like to thank the Universidade do Estado de Santa Catarina for the financial support, in the

form of a Scientific Initiation Grant, which enabled this work.

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A methodology for defining essential metadata to catalog learning objects in repositories