AGRIS is an international database containing over 8 million bibliographic records related to agricultural science and technology. It was originally a bibliographic database but has been transformed into a linked open data application. This allows AGRIS to mine and index information from the wider web by crawling websites, indexing resources with an agricultural taxonomy, and linking relevant resources to records in AGRIS. This expands access to grey literature and unpublished research beyond just bibliographic metadata.

1. AGRIS
From a bibliographical database to a linked
open data application extending
knowledge mining to the world wide web
Fabrizio Celli and Johannes Keizer – 04/11/2015

2. fabrizio celli johannes keizerhttp://aims.fao.org
Outline
 What is AGRIS?
 (S)Mash-up!
 Mining and indexing the web
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3. WHAT IS AGRIS?

4. fabrizio celli johannes keizerhttp://aims.fao.org
AGRIS
 The International System for Agricultural
Science and Technology
 A collection of more than 8 million
multilingual bibliographic resources
 A network of more than 150 institutions
from 65 countries
 A Web portal (http://agris.fao.org/)
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5. fabrizio celli johannes keizerhttp://aims.fao.org 5

6. fabrizio celli johannes keizerhttp://aims.fao.org
AGRIS 2001

7. fabrizio celli johannes keizerhttp://aims.fao.org
AGRIS 2001
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8. johannes keizerhttp://aims.fao.org
AGRIS 2015

9. fabrizio celli johannes keizerhttp://aims.fao.org
AGRIS users
• Researchers, professors, graduated
students looking for bibliographies
• Librarians, cataloguers
• Small journal publishers, professional
associations, conference organizers
• Government officers asking for reports on a
specific topic
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10. fabrizio celli johannes keizerhttp://aims.fao.org
Impact
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It supports both developed and developing countries
Accessed from more than 200 countries and territories
Google Analytics
October 2015

11. fabrizio celli johannes keizerhttp://aims.fao.org
Statistics
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8,142,755 multilingual bibliographic records
~ 400,000 from Latin America
~ 150,000 from Africa
~ 760,000 from Asia + 400,000 links to CASDD
(China)
253,286,038 triples

12. (S)Mash-up!
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13. fabrizio celli johannes keizerhttp://aims.fao.org
LOD infrastructure
 Since December 2013 AGRIS moved to the
RDF world
 Generation of mashup pages
• users looking for specific topics can access a
publication from the AGRIS database, combined with
other related resources extracted from other
preselected datasets
• external resources are not only bibliographic
metadata, but also distribution maps, statistics,
germplasm accessions, and so on.
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14. fabrizio celli johannes keizerhttp://aims.fao.org
The RDF-ization process
 Translation of the AGRIS AP XML database
to RDF
• Selection of existing vocabularies
• Data cleaning and normalization
• Index all records with the AGROVOC thesaurus
• Run the conversion and publish RDF data!
 Selection of external datasets we want to
interlink to AGRIS
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15. fabrizio celli johannes keizerhttp://aims.fao.org
AGRIS RDF
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bibo:Article
bibo:abstract
bibo:doi
bibo:isbn
bibo:presentedAt ->
bibo:Conference -> dct:title
bibo:uri
dct:alternative
dct:creator ->
foaf:organization ->
foaf:name
dct:creator ->
foaf:Person -> foaf:name
dct:dateSubmitted
dct:description
dct:extent
dct:identifier
dct:language
dct:isPartOf
dct:issued
dct:publisher ->
foaf:Organization ->
foaf:name
dct:source
dct:subject
dct:title
dct:type
dct:rights

16. fabrizio celli johannes keizerhttp://aims.fao.org
AGROVOC
 The FAO multilingual vocabulary containing
around 32 000 concepts in up to 21
languages
 Backbone: the magic that allows the
interlinking to external datasets
 Two ways to implement the interlinking:
• Using AGROVOC formal aligments to other thesauri
• Querying external WebServices with scientific names
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17. johannes keizerhttp://aims.fao.org
Relationships, Relationships
http://aims.fao.org/aos/agrovoc/c_1474.html

18. johannes keizerhttp://aims.fao.org

19. johannes keizerhttp://aims.fao.org
http://agris.fao.org
http://agris.fao.org/agris-
search/search.do?recordID=PH2011000084
http://agris.fao.org/agris-
search/search.do?recordID=PL200300203
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20. Mashup
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21. fabrizio celli johannes keizerhttp://aims.fao.org
From AGRIS to DBPedia
AGRIS
URI
AGROV
OC URI
dcterms:subject
DBPedia
URI
skos:closeMatch
skos:exactMatch
DBPedia
Abstract
Wikipedia
URL
DBPedia
Picture
foaf:isPrimaryTopicOfdbpedia-owl:abstract
foaf:depiction
Entry
point!
AGROVOC
is the
backbone

22. fabrizio celli johannes keizerhttp://aims.fao.org
SPARQL in action!
1. From an AGRIS URI, get the list of the AGROVOC URIs
(dcterms:subject)
PREFIX dct: <http://purl.org/dc/terms/>
SELECT ?agr
WHERE {
<AGRIS_Uri> dct:subject ?agr .
}
2. For each AGROVOC URI
2.1. Get skos:closeMatch and skos:exactMatch (formal alignments to other
thesauri)
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
SELECT?em ?cm {
OPTIONAL { <AGROVOC_Uri> skos:exactMatch ?em } .
OPTIONAL { <AGROVOC_Uri> skos:closeMatch ?cm } .
}

23. fabrizio celli johannes keizerhttp://aims.fao.org
Get DBPedia
2.2. The JAVA code filters DBPedia URIs, to avoid adding a new FILTER in
the SPARQL query (it’s heavy…)
2.3. For each DBPedia URI, query the DBPedia SPARQL endpoint to get
information to display in an AGRIS widget
SELECT ?abs ?img ?wiki
WHERE {
OPTIONAL {<DBP_Uri> dbpedia-owl:abstract ?abs} .
OPTIONAL {<DBP_Uri> foaf:depiction ?img} .
OPTIONAL {<DBP_Uri> foaf:isPrimaryTopicOf ?wiki} .
FILTER ( (lang(?abs ) ="en") || (!bound(?abs)) )
}

24. fabrizio celli johannes keizerhttp://aims.fao.org
Bibliography
2
«Migrating bibliographic datasets to the Semantic Web:
The AGRIS case». Stefano Anibaldi, Yves Jaques,
Fabrizio Celli, Armando Stellato, Johannes Keizer.
Semantic Web journal
«OpenAGRIS: using bibliographical data for linking into the
agricultural knowledge web». Fabrizio Celli, Stefano
Anibaldi, Maria Folch, Yves Jaques, Johannes Keizer.
AOS 2011

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Mining and indexing the web

26. fabrizio celli johannes keizerhttp://aims.fao.org
The context
 Scientists and researchers publish their
results not only in journals or at conferences,
but also via web 2.0 tools and other media
 Corpora of ongoing research activities,
unpublished material, grey literature, quick
discussions, and experiments with negative
results and ideas
 This information is usually unstructured and
not exposed using web services
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27. fabrizio celli johannes keizerhttp://aims.fao.org
Goal
 Crawl the web (manually preselected
websites)
 Machine learning algorithms to index
discovered web resources using AGROVOC
 Select relevant resources using a
recommender system
 Interlink to AGRIS!
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28. fabrizio celli johannes keizerhttp://aims.fao.org
Crawling and indexing
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https://github.com/fcproj/agrotagger

29. fabrizio celli johannes keizerhttp://aims.fao.org
Recommender system
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• A JAVA component that computes meaningful
intersections between the Crawler Database
and the AGRIS database
• Offline process, recommendations are stored in
a triplestore

30. fabrizio celli johannes keizerhttp://aims.fao.org
Interlinking
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https://github.com/fcproj/recommender

31. fabrizio celli johannes keizerhttp://aims.fao.org 31

32. fabrizio celli johannes keizerhttp://aims.fao.org
Bibliography
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Discovering, Indexing and Interlinking Information
Resources Fabrizio Celli, Johannes Keizer, Yves
Jaques, Stasinos Konstantopoulos, Dušan Vudragović.
F1000 Research
Version 2 under revision