This document discusses how e-infrastructure can help link germplasm data. It describes the need for e-infrastructure to overcome issues like data silos and lack of interoperability. The agINFRA approach provides services like metadata aggregation, vocabulary publishing, and APIs that can transform and expose germplasm descriptions as linked data. This will help link germplasm databases and make the data more discoverable. Next steps include developing recommendations for publishing germplasm data and deploying transformers and APIs on the agINFRA platform.

1. How
e-­‐infrastructure
can
contribute
to
Linked
Germplasm
data
Giannis
Stoitsis,
Agro-­‐Know
stoitsis@agroknow.gr
e-­‐conference
on
Germplasm
Data
Interoperability

2. Contents
Why
we
need
e-­‐infrastructure
What
e-­‐infrastructure
can
provide
The
agINFRA
approach
agINFRA
powered
services
for
Germplasm
data
• What
is
next
•
•
•
•

3. WHY
WE
NEED
E-­‐INFRASTRUCTURE

4. agricultural
data
• publicaKons,
thesis,
reports,
other
grey
literature
• educaKonal
material
and
content,
courseware
• primary
data,
such
as
measurements
&
observaKons
– structured,
e.g.
datasets
as
tables
– digiKzed,
e.g.
images,
videos
• secondary
data,
such
as
processed
elaboraKons
– e.g.
dendrograms,
pie
charts,
models
• provenance
informaKon,
incl.
authors,
their
organizaKons
and
projects
• experimental
protocols
&
methods
• social
data,
tags,
raKngs,
etc.
• …

5. • stats
• gene
banks
• gis
data
• blogs,
• journals
• open
archives
• raw
data
• technologies
• learning
objects
• ………..
educators’
view

6. • stats
• gene
banks
• gis
data
• blogs,
• journals
• open
archives
• raw
data
researchers’
• technologies
view
• learning
objects
• ………..

7. • stats
• gene
banks
• gis
data
• blogs,
• journals
• open
archives
• raw
data
• technologies
• learning
objects
• ………..
practioners’
view

8. • stats
• gene
banks
• gis
data
• blogs,
• journals
• open
archives
• raw
data
• technologies
• learning
objects
• ………..

9. LD for educational data/resource sharing
Overview
we
sKll
have
data
silos
Approaches for LD in educational data sharing
• Many
metadata
standards
(e.g.
DC,
IEEE
APIs and data (http://www.meducator.net)
 On the-fly/automated integration of heterogeneous LOM,
Dw,
local
schemas)
• Diversity
of
web
interfaces
(e.g.
REST,
OAI-­‐PMH,
SOAP,
SPI,
SQI)
• Different
exchange
format
(e.g.
XML,
RDF,
JSON)
• Fragmented
use
of
t cataloging (http://linkedup-project.eu)
 Dataset (transformation and)exonomies
… and not here …
We are still here …
?

10. we
need
ontologies
published
online
and
aligned
•
•
•
•
•
•
•
stats
gene
banks
blogs,
journals
open
archives
raw
data
learning
objects

11. we
need
tools
to
share
data

12. we
need
tools
to
semanKcally
annotate
data

13. and
for
all
this
we
need

15. data
infrastructure
for
agriculture
• aim
is:
promo&ng
data
sharing
and
consump&on
related
to
any
research
ac&vity
aimed
at
improving
produc&vity
and
quality
of
crops
ICT
for
compu&ng,
connec&vity,
storage,
instrumenta&on

16. what
researchers
need
in
agINFRA
…
only
a
browser
and
internet
connecKon

17. typical
problem:
compuKng

18. typical
problem:
hosKng

19. what
can
be
hosted
and
executed
on
agINFRA
• Data
storage
&
management
tools
– APIs
for
content
disseminaKon
in
large
networks
• Processing
&
visualisaKon
tools
• Metadata
aggregaKon
infra
• Search
engines
and
apps
for
insKtuKons
or
communiKes
• Environments
for
running
experiments
e.g.
comparing
different
content
recommendaKon
algorithms

20. h[p://aginfra.eu/en/our-­‐soluKon/api

21. HOW
AGINFRA
CAN
SOLVE
DATA
INTEROPERABILITY
PROBLEMS

22. WORKFLOW
FOR
METADATA
AGGREGATION

23. metadata
aggregaKons
• concerns
viewing
merged
collecAons
of
metadata
records
from
different
sources
• useful:
when
access
to
specific
supersets
or
subsets
of
networked
collecAons
– records
actually
stored
at
aggregator
– or
queries
distributed
at
virtually
aggregated
collecKons
23

24. typically
look
like
this
24
Ternier et al., 2010

25. metadata
aggregaKon
tools
More
than
a
harvester:
q Valida&on
Service
q Repository
So4ware
q Registry
Service
q Harvester
Powered by
25

26. a
metadata
aggregaKon
workflow
that
can
be
ported
on
agINFRA
HarvesKng
ValidaKng
Transforming
OAI
target
-­‐
XMLs
Storing
and
indexing
TriplificaKon

27. TOOLS
FOR
PUBLISHING
AND
LINKING
VOCABULARIES

29. AGRICULTURAL
DATA
DISCOVERY
SERVICE/PORTAL
OVER
THE
CLOUD

30. agricultural
data
discovery
modules
for
open
source
CMS
hIp://www.youtube.com/watch?v=OYlxWlyag04&feature=youtu.be

31. LINKING
GERMPLASM
DATABASES
AND
EXPOSING
DESCRIPTIONS
AS
LINKED
DATA

32. agINFRA
contribuKon
in
germplasm
data
interoperability
• Define
recommendaKons
for
describing
germplasm
data
• Define
mappings
between
different
metadata
formats
• Provide
APIs
for
transformaKon
– triplificaKon
of
germplasm
descripKons

33. mapping
between
different
metadata
formats
powered
by
agINFRA

34. publishing
germplasm
data
as
linked
data
in
agINFRA
services

35. next
steps
in
the
context
of
agINFRA
• Develop
the
recommendaKons
for
publishing
germplasm
data
• Deploy
transformers
and
make
them
available
in
agINFRA
• Deploy
API
for
triplificaKon

36.
thank
you!
stoitsis@agroknow.gr
www.agroknow.gr
www.aginfra.eu