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

2/27/2013

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”

2/27/2013

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


2/27/2013

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



2/27/2013

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



2/27/2013

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


2/27/2013

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


2/27/2013

APs versus base standard IEEE LOM

Metadata records versus APs

Data analysis: 2 different purposes


2/27/2013

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


2/27/2013

# 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”

2/27/2013

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



2/27/2013

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




20

Number of simple data elements included in AP respect base schema

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2/27/2013


21

Number of simple data elements included in AP respect base schema

2/27/2013

14 APs include less than the 58 elements in

the base standard (44%)

12 APs include all the 58 data elements in


6 APs include more than the 58 elements in


Number of mandatory simple data elements stated by AP

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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?

2/27/2013 24

ABCore

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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%)

2/27/2013

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?

2/27/2013 27

ABCore

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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?

2/27/2013 29

ABCore

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LRR applies specified controlled vocabularies?


• Specified controlled vocabularies are

applied in 19 LRRs (79%)

• Specified controlled vocabularies are not

applied in 1 LRR (4%)



LRR apply data types and values restrictions?

2/27/2013 31

ABCore

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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%)



2/27/2013

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


2/27/2013

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.


2/27/2013

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


2/27/2013

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


2/27/2013

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

disabilities conference

ieee lom metadata

ieee lom mapping

different application

adoption of profiles

known ieee lom drawbacks

ieee lomadoption of

learning resources