Csun pse-006-presentation-2013 v2.1

Ensenyament – Assignatura

Curs 20xx – 20xx

Docent: Nom Cognoms

IEEE LOM is not an option: lessons to learn

Miquel Centelles, Mireia Ribera, Marina Salse

Grup Adaptabit: Working group on digital accessibility for teaching, research and teaching innovation

Departament of Librarianship and Information Science

University of Barcelona

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Rationale Objectives Methodology Data analysis Discussion Further steps

Summary

228th Annual International Technology and Persons with Disabilities Conference

2/27/2013

A project on creating accessible teaching resources within the University of Barcelona.

We want to recommend teachers a metadata model covering accessibility aspects of resources and processes.

Rationale: context of the research


Rationale: why our (first) interest in IEEE LOM

Adoption of SCORM: Many Learning Management Systems support SCORM, and SCORM uses IEEE LOM metadata.

Adoption in LMS: LOM as a major development of eLearning systems (such as LMS) and is widely used in such systems, notably for example in Europe.

Adoption of profiles: LOM has been widely profiled for particular domains.

2/27/2013 28th Annual International Technology and Persons with Disabilities Conference 4

Rationale: why our (first) interest in IEEE LOM


Element 9.1 Classification. Purpose admits value “accessibility restrictions”

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Its abstract model is not aligned with basic standards for semantic interoperability, such as Resource Description Framework (RDF).

The adaptation of the standard to the web of data is suffering from delays in two key processes: The IEEE LOM mapping to Dublin Core (DCMI) abstract

model. The elaboration and publication of an official RDF

vocabulary.

Rationale: known IEEE LOM drawbacks


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1. Identification of application profiles based on IEEE LOM.

2. Descriptive review of IEEE LOM application profiles (AP).

3. Descriptive review of AP implementation on Learning Resource Repositories (LRR).

Objectivesof the research


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Application profiles gathering: Literature search through key actors,

European projects, and bibliographic databases.

Complement with questionnaires and interviews to AP holders.

Methodology: on application profiles


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Application profiles selection: It must be based (mostly) on IEEE LOM, of

course It must be currently active No restrictions on:

• the practice community• the scope of application profiles (topics…)• the country of origin



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Key data of findings: 32 different application profiles 3 have a world wide scope 11 are focused on Europe 4 are focused on USA the remaining 17 are focused on different,

specific countries



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One LRR is selected for each IEEE LOM application profile: It must offer openly accessible resources It could belong to one unique institution, or to

several If several LRRs, selection based on:

• University over lower studies• Broad content over specialized

Methodology: on LRRs


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10 samples of metadata records are obtained from each LRR: Search period: 29th August-8th October 2012. Search strategy (descending order):

• 1st Criteria: first learning resources published during 2012• 2nd Criteria: learning resources of the type “Lecture”• 3rd Criteria: keyword “education”

Finally, we got search results concerning 24 APs

Methodology: on LRRs


Methodology: 10 samples of records of each LRR


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APs versus base standard IEEE LOM

Metadata records versus APs

Data analysis: 2 different purposes


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Not all AP provides the same quantity and quality of evidences for the analysis. All of them: documentation about schema and data values Other evidences, depending on each AP:

• Full evidence level: records in XML binding.• Medium evidence level: records in some human readable format

(not XML).• Low evidence level: no metadata records (8 APs), mostly due to

LRR out of order during the test period.

Data analysis: different evidence levels


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# of simple data elements in AP versus 58 total in the base Standard

# of mandatory simple data elements in AP

# of non allowed modifications within AP:

Data analysis: APs vs. base standard




Element 9.1 Classification. Purpose admits value “accessibility restrictions”

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Non allowed modifications:1. Altering the relative location of an existing data element

(e.g. moving a parent element to a child one)

2. Creating a new element that mimics the semantic intent of an existing element

3. Changing the meaning of an existing element

4. Changing the name of an element

5. Extending a schema other than at a specified extension point



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Non allowed modifications (cont.):6. Extending cardinality of an element

7. Adding new items in a controlled vocabulary list

8. Modifying the value space and data type of data elements from the base schema.

9. Defining data types or value spaces for aggregate data elements in the base schema




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Number of simple data elements included in AP respect base schema

ABCore

ANZ-LOM

ARIADNE LOM

BEN

BIO@

GRO

COSMOS

DETLRM

eAcc

ess2

Learn

Eleone

t Meta

data

GLOBE M

etada

ta

Health

care

LOM

ICOPER LO

M

Interg

eo M

etada

ta

ISRA Core

Kentuc

ky

LRE

LOM-C

H

LOM-D

E

LOM-E

S

LOM FR

MACE

ManUeL

NL LOM

NORLOM

Normeti

c

OpenS

cout

Organic

.Edune

t OSR

Rural-e

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SREB-SCORE

TrAgL

orVET

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

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Number of simple data elements included in AP respect base schema

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14 APs include less than the 58 elements in the base standard (44%)

12 APs include all the 58 data elements in the base standard (37%)

6 APs include more than the 58 elements in the base standard (19%)

Number of mandatory simple data elements stated by AP

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ABCore

ANZ-LOM

ARIADNE LO

MBEN

BIO@

GRO

COSMOS

DETLRM

eAcc

ess2

Learn

Eleone

t Meta

data

GLOBE M

etada

ta

Health

care

LOM

ICOPER LO

M

Interg

eo M

etada

ta

ISRA C

ore

Kentuc

ky

LRE

LOM-C

H

LOM-D

E

LOM-E

S

LOM FR

MACE

ManUeL

NL LOM

NORLOM

Normeti

c

OpenS

cout

Organic

.Edu

net

OSR

Rural-e

Gov

SREB-SCORE

TrAgL

orVET

0

5

10

15

20

25

30

35


Number of mandatory simple data elements stated by AP

2/27/2013 2328th Annual International Technology and Persons with Disabilities Conference

25 APs state mandatory (simple) data elements (78%):

At top: Biosci Education Network (BEN) states 30 mandatory elements

At bottom: LOM-FR states 3 mandatory elements

7 APs don’t state any mandatory (simple) data elements (22%)

AP is conformant with base schema?

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ABCore

ANZ-LOM

ARIADNE LO

MBEN

BIO@

GRO

COSMOS

DETLRM

eAcc

ess2

Learn

Eleone

t Meta

data

GLOBE M

etada

ta

Health

care

LOM

ICOPER LO

M

Interg

eo M

etada

ta

ISRA C

ore

Kentuc

ky

LRE

LOM-C

H

LOM-D

E

LOM-E

S

LOM FR

MACE

ManUeL

NL LOM

NORLOM

Normeti

c

OpenS

cout

Organic

.Edu

net

OSR

Rural-e

Gov

SREB-SCORE

TrAgL

orVET


AP is conformant with base schema?


4 APs are fully conformant with the base schema (12%)

25 APs are not fully conformant with the base schema (78%) The less respected restriction: Adding new items in a

controlled vocabulary list (18/25) The most respected restriction: Defining data types or value

spaces for aggregate data elements in the base schema (2/25)

In 3 cases, solid conclusions can not be made based on available sources (9%)

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Our questions are: Metadata records respect mandatory conditions

of simple data elements in the AP? Metadata records in the LRR apply controlled

vocabularies established by the AP? Metadata records in the LRR respect requirement

related to value spaces and data types in the AP?

Data analysis: Metadata records versus APs


LRR follows mandatory conditions?

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ABCore

ANZ-LOM

ARIADNE LO

MBEN

BIO@

GRO

COSMOS

DETLRM

eAcc

ess2

Learn

Eleone

t Meta

data

GLOBE M

etada

ta

Health

care

LOM

ICOPER LO

M

Interg

eo M

etada

ta

ISRA C

ore

Kentuc

ky

LRE

LOM-C

H

LOM-D

E

LOM-E

S

LOM FR

MACE

ManUeL

NL LOM

NORLOM

Normeti

c

OpenS

cout

Organic

.Edu

net

OSR

Rural-e

Gov

SREB-SCORE

TrAgL

orVET


LRR follows mandatory conditions?


• Not applicable in 5 LRRs (21%)• Mandatory conditions are followed in 5

LRRs (21%)• Mandatory conditions are not followed in 11

LRRs (46%)• In 3 cases, solid conclusions can not be

made based on available sources (12%)

LRR applies specified controlled vocabulary?

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ABCore

ANZ-LOM

ARIADNE LOM

BEN

BIO@

GRO

COSMOS

DETLRM

eAcc

ess2

Learn

Eleone

t Meta

data

GLOBE M

etada

ta

Health

care

LOM

ICOPER LO

M

Interg

eo M

etada

ta

ISRA Core

Kentuc

ky

LRE

LOM-C

H

LOM-D

E

LOM-E

S

LOM FR

MACE

ManUeL

NL LOM

NORLOM

Normeti

c

OpenS

cout

Organic

.Edune

t OSR

Rural-e

Gov

SREB-SCORE

TrAgL

orVET


LRR applies specified controlled vocabularies?


• Specified controlled vocabularies are applied in 19 LRRs (79%)

• Specified controlled vocabularies are not applied in 1 LRR (4%)

• In 4 cases, solid conclusions can not be made based on available sources (17%)

LRR apply data types and values restrictions?

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ABCore

ANZ-LOM

ARIADNE LOM

BEN

BIO@

GRO

COSMOS

DETLRM

eAcc

ess2

Learn

Eleone

t Meta

data

GLOBE M

etada

ta

Health

care

LOM

ICOPER LO

M

Interg

eo M

etada

ta

ISRA Core

Kentuc

ky

LRE

LOM-C

H

LOM-D

E

LOM-E

S

LOM FR

MACE

ManUeL

NL LOM

NORLOM

Normeti

c

OpenS

cout

Organic

.Edune

t OSR

Rural-e

Gov

SREB-SCORE

TrAgL

orVET


LRR applies data types and values restrictions?


• Data types and values restrictions are applied in 11 LRRs (46%)

• Data types and values restrictions are not applied in 1 LRR (4%)

• In 12 cases, solid conclusions can not be made based on available sources (50%)

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Most AP are not conformant with IEEE LOM base standard.

Implementation of AP on LRR don’t even follow the application profile conditions.

Availability of interchange formats (XML, JSON... not to say RDF) for metadata records is not a broad practice.

Discussion: disappointing results


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Extension of controlled vocabularies with new words created adhoc.

Modifications in value spaces and data types of data elements.

Definition of data types or value spaces for aggregated data elements.

Discussion: main conformance black holes


Discussion: lessons learned

Keep them simple. Metadata is an “overhead” task which should be minimum and as automatic as possible.

Force conformance through XML schemas, semantic web vocabularies or other applied constraints

Set a standard for the display of records and their reusability.


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Based on those drawbacks, we have decided to move on new alternatives for metadata base schema: ISO/IEC 19788 Metadata for learning resources

(MLR) standard

…or… Learning Resources Metadata Initiative (LRMI), which

uses microdata and is led by significant companies.

Further steps: new standards in competition


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Nevertheless, we’ll keep on completing the map of IEEE LOM based AP.

In order to: Monitoring the evolution and adaptation of IEEE LOM APs to

the semantic web. Monitoring the solutions which LRRs adopt to manage

mentioned challenges. Monitoring the evolution of IEEE LOM standard in relation with

the raising of “new” learning resources metadata standards.

Further steps: we’ll keep monitoring


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We ask you to give us information about IEEE LOM APs and LRR using them, answering the questionnarie for this purpose available at:

Adaptabit http://bd.ub.edu/adaptabit/

We will offer you the publication of all the data about IEEE LOM APs as open data.

Further steps: collaborations?


http://bd.ub.edu/adaptabit/

2/27/2013

Questions,Opinions,

Suggestions…

[email protected]

Thanks for your attention!


Csun pse-006-presentation-2013 v2.1

Education

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