Valeria Pesce, GFAR, at RDA 5th Plenary Meeting, IG Agriculture Data Interoperability Session in San Diego (CA, US) on the 9th of March 2015

1. The CIARD RING
What is new
Imma Subirats
Food and Agriculture Organization of the United Nations
Valeria Pesce
Global Forum on Agricultural Research (GFAR)
Research Data Alliance 5th Plenary Meeting
9-11 March 2015, San Diego
Joint session:
IG Agriculture Data Interoperability
& WG Wheat Data Interoperability

2. The CIARD RING
http://ring.ciard.net
The CIARD RING is a project implemented within the
CIARD initiative and is led by the Global Forum on
Agricultural Research (GFAR).
The CIARD RING is
a global directory of web-based information
services and datasets for agriculture

3. Numbers and map
• 499 data providers
• 1038 information services, of which
– 281 exposed datasets

4. The RING user interface

5. Dataset page

6. The RING machine interface – SPARQL
An RDF store is a way of storing data using a machine-
readable "grammar" (the Resource Description Framework)
and documented semantics (RDF vocabularies).
URIs
The URI for each service / dataset is built as follows:
RING-domain/node/service-ID.
For example: http://ring.ciard.net/node/2417
The RING database is also an accessible RDF store.
SPARQL endpoint
http://ring.ciard.net/sparql1

7. SPARQL how to: vocabularies
The vocabularies used in the RDF store are:
• RDF: http://www.w3.org/1999/02/22-rdf-syntax-ns#
• RDFS: http://www.w3.org/2000/01/rdf-schema#
• DC: http://purl.org/dc/terms/
• DCAT: http://www.w3.org/ns/dcat#
• ADMS: http://www.w3.org/ns/adms#
• FOAF: http://xmlns.com/foaf/0.1/
• DOAP: http://usefulinc.com/ns/doap#
• SKOS: http://www.w3.org/2004/02/skos/core#
• VCARD: http://www.w3.org/2006/vcard/ns#
The data model chosen to describe datasets is the
W3C Data Catalog Vocabulary (DCAT)
designed to describe datasets
and the forms in which they are exposed, their "distributions"

8. The RING Linked Data
“CIARD RING” record from LOD Live: http://en.lodlive.it/?http://ring.ciard.net/node/19435

9. The RING machine interface – Why (1)
• Datasets registered in the RING have to be found by
applications
• Applications have to be able to read all the metadata about
datasets and filter datasets according to their needs
• Applications have to find enough technical metadata in the
RING to:
– Identify datasets with a specific coverage (type of data, thematic
coverage, geographic coverage)
– Identify datasets that comply with certain technical specifications
(format, protocol etc.)
– Access the dataset and get the data
 This machine-readable layer can support the data
aggregation workflows of external services

10. The RING machine interface – Why (2)
• Additional information that applications may want to get
about datasets:
– Are there other software applications or APIs that can
process this dataset?
 A new feature of the RING is the addition of a
directory of dataset processing software tools
and web services
Datasets can be associated with software tools and APIs that
can process them in different ways (convert, analyze, combine
with other data etc.)

11. Linking datasets and software required two new RDF
vocabularies:
• DCAT-EXT: http://vocabularies.aginfra.eu/dcatext#
an extension of the DCAT vocabulary with a few additional
properties
• WS: http://vocabularies.aginfra.eu/ws#
an RDF vocabulary to describe methods and related parameters
of web services
Search software
and APIs:
humans
Search software
and APIs:
machines!
Software in the RING
http://ring.ciard.net/
software-all

12. Example of API page

13. Interoperability assessment in the RING
The technical metadata registered in the RING for
each dataset provide enough information to give a
good idea of the level of “interoperability” of that
dataset.
“Interoperability is a feature of datasets— and of information
services that give access to datasets— whereby data can easily
be retrieved, processed, re-used, and re-packaged (“operated”)
by other systems. The less pre-coordination required to achieve
this, the more “interoperable” the dataset.”
[from: Interim Proceedings of International Expert Consultation
on “Building the CIARD Framework for Data and Information
Sharing”, Beijing 20-23 June 2011. 2011.]

14. Metadata Type Interoperability points Tim Berner Lee’s stars
For the service/dataset in general
1
Global coverage Select list 4 if not empty
2
Regional coverage (FAO) Select list 4 if not empty
3
Regional coverage (GFAR) Select list 4 if not empty
4
National coverage Select list 4 if not empty
5
Specific topic (AGROVOC) Autocomplete multiple
(authority: AGROVOC)
8 if not empty
6
Type of content/data managed Autocomplete multiple 4 if not empty
7
KOSs used Select list multiple
(authority: VEST Registry)
10 for each KOS used 5 IF you already have 4
8
Special instructions for getting
data from this service
Text 3 if not empty
9
Examples Text multiple 2 for each example
For each distribution of the
dataset
10
URL / target / endpoint Text 30 if not empty 1
11
File upload Upload 10 if not empty 1
12
Access / licensing Autocomplete 4 if half-open; 6 if free / open; 8 if
formally open (OA, CC)
0.5 if half-open; 1 if open; 1.5 if
open and known license e.g. CC
13
License URL Text: URL 7 if not empty 0.5
14
Protocol Select list 10 ftp/download; 20 OAI-PMH or
web service; 30 if SPARQL
1 if ftp/download; 3 if OAI-PMH or
RSS; 4 if SPARQL
15
Format / serialization / notation Select list
(authority: subset of IANA
types)
5 Excel; 10 CSV, XML; 12 JSON; 15
RDFXML; 20 JsonLD, ntriples-n3-
turtle)
2 if Excel; 3 if CSV, XML, JSON; 4 if
JsonLD, RDFXML, ntriples-n3-turtle
16
Metadata set(s) used Select list
(authority: VEST Registry)
6 for each metadata set 2.5
17
Does the dataset use URIs? Yes/No 20 if yes; OR: multiply 15 by n. 10 4 (OR: 4 IF you already have 3)
18

15. Example of
interoperability
assessment in the
RING

16. The Open AGRIgate challenge
The challenge rewards the institution that registers the
best datasets in the RING, judged especially in terms of
interoperability, with two unique prizes:
• the opportunity to work together with data
scientists building applications based on your data;
• having your dataset featured at the next meeting of
the Agricultural Data Interoperability Interest Group
at the Research Data Alliance.
This challenge aims at encouraging small institutions
and institutions in developing countries to open their
data, so the competition is limited to:
• institutions in countries classified by the World Bank
as "low-income", "lower-middle-income" and
"upper-middle-income“;
• institutions with less than 1000 employees in any
country.
The
interoperability
assessment is
used to rank
datasets in the
competition
http://ring.ciard.net/
participate-open-
agrigate-challenge

17. Final results of the Open AGRIgate challenge

18. Thank you
Thank you for your attention