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How can we build an open and
scalable learning infrastructure
for food safety
Nikos Manouselis
nikosm@agroknow.gr
http://wiki.agroknow.gr

“meaningful services
around high-quality
agricultural data”
“…why do I
care??”
?
?
!
How can I provide
safe food?
How can I
produce safe
food?
?
Multi-Donor Trust Fund (MDTF) being
established to raise at least $45,000,000 for
implementation of a Roadmap and 5-year
workplan
aim: train small food producers, around the
world, using blended approaches
global food safety capacity building
is it a…

?
reflecting on complexity
#3
Program Facilitation

Open & Scalable
Open & Scalable
Learning Infrastructure
Learning Infrastructure
Includes : :
Includes
- -OER data pool
OER data pool
- -Course registry
Course registry
- -Curriculum Development
Curriculum Development
-Curricula Alignment
-Curricula Alignment
evolving the concept
• may aim higher than a single GFSP learning
platform – cannot generalize something that
requires a focused, regional approach
• rather develop a GFSP Learning Infrastructure
including (among others)
– Educational Offerings Aggregator Services
– Curriculum Support, Registry & Alignment Services
– GFSP Learning Portal (main front end)
– GFSP Learning Widgets/apps (to be integrated in web
sites, offered through smartphones/tablets, etc)
could look like this
Educational Offerings Aggregator
• back end technology infrastructure
– ingest, harvest, aggregate course and OER
metadata from existing or new (e.g. legacy)
learning platforms and OER collections
– tools to allow course and OER providers to
align/map their metadata & classifications to
the GFSP ones
Curriculum Registry & Alignment
• representation of GFSP curriculum in
interoperable format (using learning outcomes,
competences)
– tools to allow other course providers to register and
express/map their curricula to the GFSP curriculum
– tools to facilitate the generation of multilingual
versions of the curricula descriptions
– generation of transformable curricula representations
to allow users to browse using preferred curicullum
format
GFSP Learning Portal
• main front-end to present project and allow
users to find information in the aggregated
sources
– various modalities (visual, device, thematic,
geographical, industry, …) for search &
discovery of courses and OER
– multilingual interfaces and metadata facilitated
by automatic translation engines
GFSP Learning Widgets/Apps
• search/discovery interfaces and mechanisms that
can be embedded in other web sites and portals
(widget-like or search pages in sites)
• mobile apps for various operational systems (iOS,
Android, Windows 8)
• back-end engine to allow straightforward
generation of adaptable versions of both
(thematic, industry, geographical, linguistic, …)
important distinction
• such a learning infrastructure is heavily
dependent on the back-end layers
• it is important to be able to power existing
applications and services
• the centralised portal mainly serves as
demonstrator
• will really change something if it provides a
wealth of resources around each topic
a case study
• regional meat producer in Paraguay
– example scenario: exploring how their company
can start selling packaged cooked ham to an
international food distribution company

• product of high quality one, made from pure
pork ham
– let us assume that they would like to find out
more about the food safety standards of cooked
ham
this is why
#3
Program Facilitation

Open & Scalable
Open & Scalable
Learning Infrastructure
Learning Infrastructure
Includes : :
Includes
- -OER data pool
OER data pool
- -Course registry
Course registry
- -Curriculum Development
Curriculum Development
-Curricula Alignment
-Curricula Alignment
what’s really happening behind
CONTENT PROVIDER
WITH UNORGANISED
COLLECTION
(e.g. Listed at Web
site or in DVD-ROM)

Chooses compliant tool

Metadata export in
Ingestion in
proprietary format & compliant tool
provides mapping
CONTENT PROVIDER
WITH CMS THAT DOES
NOT SUPPORT OAIPMH (e.g. Proprietary
DB)

CONTENT PROVIDER
WITH CMS THAT
SUPPORTS OAI-PMH
(e.g. FSKN compliant,
ePrints, DSPACE,...)
DOMAIN EXPERTS

publish & evolve
vocabularies &
ontologies
Exposes metadata
through OAI-PMH

Exposes metadata
through OAI-PMH

Indexed & available in
back-end

METADATA
AGGREGATOR

Exposes metadata
through OAI-PMH
typical problems
a.
b.
c.
d.
e.

metadata authoring/creation
metadata assurance/validation
metadata values/vocabularies
metadata multilinguality
…lots more

36
a. authoring/creation
• metadata creation is a painful and
costly process
– automatic generation can help
– high quality/accuracy/relevance
descriptions require human intervention

37
a. authoring/creation

38
b. assurance/validation
• good online services demand high
quality (or at least not poor quality)
description of content
– someone needs to take the final decision
before something is published
– especially relevant when content
development has been costly/labourous
39
b. assurance/validation

40
c. values/vocabularies
• mappings and crosswalks among
values and vocabularies of different
collections are crucial
– usually manually defined and maintained
– difficult to ensure that all applications
will publish and link their vocabularies
– vocabulary bank management tend to
become too complex for the purpose
that they serve
41
c. values/vocabularies

42
d. multilinguality
• for multilingual contexts, everything
needs to become (and be maintained)
multilingual
– metadata values and labels
– interface labels for various systems

• automatic translation helps but usually
produces rather rough/poor
translations
43
d. multilinguality

44
challenges in semantics
describing course offerings
• what I am describing is different to what
you are describing…
– …but there are so many similar things!
Africa Lead course database
Provider: University of
Pretoria
CerOrganic portal
CerOrganic Schema
Africa Lead Schema

Missing
competencies description
• what I would like to learn is what you
need me to know…
– …but what is really needed is connecting a
job profile to the relevant course offerings!
GFSI Competency
Framework
AGRICOM

job profile description

Job description or
single task description

Required competences
GFSI Competency
Framework

AGRICOM Competence
Framework / Job task
Job / task title
Job profile /
task description
Competence Title
Competence description
Course title
expected learning outcomes
• what I am going to learn should be what I
am expected to know for my job…
– …but sometimes it’s not very clear what
this is going to be!
CerOrganic Curriculum description

DICLA training center

Capabilities: When completing this course you will
be able to perform basic routine operations in a
defined hydroponic context under close supervision.
more issues…
• old-fashioned legacy systems still used in such
traditional settings
– terms like “OER” and “MOOC” sound like science fiction

• novel technologies such as semantic stores and
ontology editing/managing environments are not
user-friendly and proven
– especially for such technology-ignorant users

• very rich semantics to be represented, handled and
exploited; but we are not there yet
wrap up
targeted domain
• rich in data-oriented problems and
cases
• focused on “real” users
• inter-disciplinary work
• results related to societal
goals/challenges
increase use & reuse
• digital sources and collections
material to be used (and
potentially re-used) in several
contexts
– even different than originally
expected/thought of
thank you!
info@agroknow.gr
http://wiki.agroknow.gr

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How can we build an open and scalable learning infrastructure for food safety?

  • 1. How can we build an open and scalable learning infrastructure for food safety Nikos Manouselis nikosm@agroknow.gr
  • 4. ?
  • 5. ?
  • 6. !
  • 7. How can I provide safe food?
  • 8. How can I produce safe food?
  • 9.
  • 10. ?
  • 11. Multi-Donor Trust Fund (MDTF) being established to raise at least $45,000,000 for implementation of a Roadmap and 5-year workplan aim: train small food producers, around the world, using blended approaches
  • 12. global food safety capacity building
  • 13.
  • 14.
  • 15.
  • 17. reflecting on complexity #3 Program Facilitation Open & Scalable Open & Scalable Learning Infrastructure Learning Infrastructure Includes : : Includes - -OER data pool OER data pool - -Course registry Course registry - -Curriculum Development Curriculum Development -Curricula Alignment -Curricula Alignment
  • 18. evolving the concept • may aim higher than a single GFSP learning platform – cannot generalize something that requires a focused, regional approach • rather develop a GFSP Learning Infrastructure including (among others) – Educational Offerings Aggregator Services – Curriculum Support, Registry & Alignment Services – GFSP Learning Portal (main front end) – GFSP Learning Widgets/apps (to be integrated in web sites, offered through smartphones/tablets, etc)
  • 20. Educational Offerings Aggregator • back end technology infrastructure – ingest, harvest, aggregate course and OER metadata from existing or new (e.g. legacy) learning platforms and OER collections – tools to allow course and OER providers to align/map their metadata & classifications to the GFSP ones
  • 21. Curriculum Registry & Alignment • representation of GFSP curriculum in interoperable format (using learning outcomes, competences) – tools to allow other course providers to register and express/map their curricula to the GFSP curriculum – tools to facilitate the generation of multilingual versions of the curricula descriptions – generation of transformable curricula representations to allow users to browse using preferred curicullum format
  • 22. GFSP Learning Portal • main front-end to present project and allow users to find information in the aggregated sources – various modalities (visual, device, thematic, geographical, industry, …) for search & discovery of courses and OER – multilingual interfaces and metadata facilitated by automatic translation engines
  • 23. GFSP Learning Widgets/Apps • search/discovery interfaces and mechanisms that can be embedded in other web sites and portals (widget-like or search pages in sites) • mobile apps for various operational systems (iOS, Android, Windows 8) • back-end engine to allow straightforward generation of adaptable versions of both (thematic, industry, geographical, linguistic, …)
  • 24. important distinction • such a learning infrastructure is heavily dependent on the back-end layers • it is important to be able to power existing applications and services • the centralised portal mainly serves as demonstrator • will really change something if it provides a wealth of resources around each topic
  • 25.
  • 26. a case study • regional meat producer in Paraguay – example scenario: exploring how their company can start selling packaged cooked ham to an international food distribution company • product of high quality one, made from pure pork ham – let us assume that they would like to find out more about the food safety standards of cooked ham
  • 27.
  • 28.
  • 29.
  • 30.
  • 31. this is why #3 Program Facilitation Open & Scalable Open & Scalable Learning Infrastructure Learning Infrastructure Includes : : Includes - -OER data pool OER data pool - -Course registry Course registry - -Curriculum Development Curriculum Development -Curricula Alignment -Curricula Alignment
  • 33. CONTENT PROVIDER WITH UNORGANISED COLLECTION (e.g. Listed at Web site or in DVD-ROM) Chooses compliant tool Metadata export in Ingestion in proprietary format & compliant tool provides mapping CONTENT PROVIDER WITH CMS THAT DOES NOT SUPPORT OAIPMH (e.g. Proprietary DB) CONTENT PROVIDER WITH CMS THAT SUPPORTS OAI-PMH (e.g. FSKN compliant, ePrints, DSPACE,...) DOMAIN EXPERTS publish & evolve vocabularies & ontologies
  • 34. Exposes metadata through OAI-PMH Exposes metadata through OAI-PMH Indexed & available in back-end METADATA AGGREGATOR Exposes metadata through OAI-PMH
  • 35.
  • 36. typical problems a. b. c. d. e. metadata authoring/creation metadata assurance/validation metadata values/vocabularies metadata multilinguality …lots more 36
  • 37. a. authoring/creation • metadata creation is a painful and costly process – automatic generation can help – high quality/accuracy/relevance descriptions require human intervention 37
  • 39. b. assurance/validation • good online services demand high quality (or at least not poor quality) description of content – someone needs to take the final decision before something is published – especially relevant when content development has been costly/labourous 39
  • 41. c. values/vocabularies • mappings and crosswalks among values and vocabularies of different collections are crucial – usually manually defined and maintained – difficult to ensure that all applications will publish and link their vocabularies – vocabulary bank management tend to become too complex for the purpose that they serve 41
  • 43. d. multilinguality • for multilingual contexts, everything needs to become (and be maintained) multilingual – metadata values and labels – interface labels for various systems • automatic translation helps but usually produces rather rough/poor translations 43
  • 46. describing course offerings • what I am describing is different to what you are describing… – …but there are so many similar things!
  • 47. Africa Lead course database Provider: University of Pretoria
  • 50. competencies description • what I would like to learn is what you need me to know… – …but what is really needed is connecting a job profile to the relevant course offerings!
  • 52. AGRICOM job profile description Job description or single task description Required competences
  • 53. GFSI Competency Framework AGRICOM Competence Framework / Job task Job / task title Job profile / task description Competence Title Competence description Course title
  • 54. expected learning outcomes • what I am going to learn should be what I am expected to know for my job… – …but sometimes it’s not very clear what this is going to be!
  • 55. CerOrganic Curriculum description DICLA training center Capabilities: When completing this course you will be able to perform basic routine operations in a defined hydroponic context under close supervision.
  • 56. more issues… • old-fashioned legacy systems still used in such traditional settings – terms like “OER” and “MOOC” sound like science fiction • novel technologies such as semantic stores and ontology editing/managing environments are not user-friendly and proven – especially for such technology-ignorant users • very rich semantics to be represented, handled and exploited; but we are not there yet
  • 58. targeted domain • rich in data-oriented problems and cases • focused on “real” users • inter-disciplinary work • results related to societal goals/challenges
  • 59. increase use & reuse • digital sources and collections material to be used (and potentially re-used) in several contexts – even different than originally expected/thought of