csun pse-006-presentation-2013 v2.1
DESCRIPTION
Although some projects and most LMS still rely on IEEE LOM, this standard is not yet an option. We suggest some lessons to learn.TRANSCRIPT
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
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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
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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.
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Rationale: why our (first) interest in IEEE LOM
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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
Methodology: on application profiles
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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
Methodology: on application profiles
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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
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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
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Data analysis: APs vs. base standard
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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
Data analysis: APs vs. base standard
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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
Data analysis: APs vs. base standard
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Number of simple data elements included in AP respect base schema
ABCore
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0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
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21
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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0
5
10
15
20
25
30
35
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Number of mandatory simple data elements stated by AP
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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
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Lear
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Eleone
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GLOBE M
etad
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Health
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LOM
ICOPER L
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Inte
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adat
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Rural-
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SREB-SCORE
TrAgL
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AP is conformant with base schema?
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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
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LRR follows mandatory conditions?
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ABCore
ANZ-LO
M
ARIADNE L
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BIO@
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COSMOS
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Lear
n
Eleone
t Met
adat
a
GLOBE M
etad
ata
Health
care
LOM
ICOPER L
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Inte
rgeo
Met
adat
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Kentu
cky
LRE
LOM-C
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LOM-D
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LOM-E
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LOM F
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MACE
ManUeL
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NORLOM
Normet
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Organ
ic.Edu
net
OSR
Rural-
eGov
SREB-SCORE
TrAgL
orVET
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LRR follows mandatory conditions?
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• 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 LO
MBEN
BIO@
GRO
COSMOS
DETLRM
eAcc
ess2
Lear
n
Eleone
t Meta
data
GLOBE M
etada
ta
Health
care
LOM
ICOPER LO
M
Inter
geo M
etada
ta
ISRA C
ore
Kentuc
ky
LRE
LOM
-CH
LOM
-DE
LOM
-ES
LOM
FR
MACE
Man
UeL
NL LOM
NORLOM
Norm
etic
OpenS
cout
Organ
ic.Edu
net
OSR
Rural-
eGov
SREB-SCORE
TrAgL
orVET
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LRR applies specified controlled vocabularies?
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• 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 LO
MBEN
BIO@
GRO
COSMOS
DETLRM
eAcc
ess2
Lear
n
Eleone
t Meta
data
GLOBE M
etada
ta
Health
care
LOM
ICOPER LO
M
Inter
geo M
etada
ta
ISRA C
ore
Kentuc
ky
LRE
LOM
-CH
LOM
-DE
LOM
-ES
LOM
FR
MACE
Man
UeL
NL LOM
NORLOM
Norm
etic
OpenS
cout
Organ
ic.Edu
net
OSR
Rural-
eGov
SREB-SCORE
TrAgL
orVET
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LRR applies data types and values restrictions?
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• 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
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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?
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Questions,
Opinions,
Suggestions…
Thanks for your attention!
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