Supported by EU projects

Open Data in Agriculture Hands-on with data infrastructures that can power your agricultural data products 12/12/2013 Athens, Greece Supported by EU projects

Tutorial on defining users’ clusters in agricultural sciences, using the VIVO tool Alberto Nogales Alcalá University (UAH)

The Problem I am a researcher and want to obtain some measurements in scientific productivity I know VIVO, that project used to store research information from institutions But I need some extra information that is not store in my VIVO instance And as a European researcher I want to expose that data using a European standard

The Standards • An open source web application. • Enables the discovery of researchers across institutions. • Based on local instances that can interconnect between them. • A standard for managing and exchanging research data. • Enables integrated research information environment. • Allows standardised exchange of information.

Our development in steps What information does not share VIVO and Google ScholarDetect which fields are useful. 2) Obtain new information with GS scraper using titles from OpenAGRIS and aggregate it to the VIVO instance. VIVO export/import  New information added 3) Use the VIVO-CERIF translator. Convert the CERIF instance into CERIF-LD. VIVO-CERIF translator  Obtain VIVO instance in a European standard.

Step 1 Title* Description (authors, journal…) URL References* Cites Google Scholar VIVO Authors Event Issue Date (year) Volume Start and end page DOI PMCID NIHMSID File Format Version Bibtex cite* Number of cites Ranking in GS

Step2 • Objective: Combine titles from OpenAGRISobtained with the scrapper with titles stored in VIVO instances. • Solution: • Combine information from scrapper database with VIVO information. Using titles. • Annotate information in VIVO instances. VIVO component– Export.

Step 3 Objective: Obtain a CERIF instance with the new information after combining GS and VIVO. Solution: XSLT transformation. • 1) It extracts RDF from a VIVO instance converting it to CERIF model in XML. VIVO-Cerif translator. • 2) The translation from one language to another is made using XSLT sheets. • 3) The equivalences between RDF and XML has been set by euroCRIS CERIF and VIVO members in a mapping document (v 0.2).

Workflow 1 2 VIVO.rdf Google Scholar GS scraper VIVO import/export 3 New Information VIVO++.rdf VIVO-CERIF Translator 5 CERIF-LD CERIF 4

Use case 1) We have a paper from OpenAGRIS which have some information stored in Google Scholar.

Use Case 2) We have also the paper stored in VIVO but there is only a few information about it. For example the references are not stored. 3) Looking at the VIVO ontology we know we can use a property to reference papers called “cites”

Use Case 4) Looking at the VIVO ontology we know we can use a property to reference papers called “cites”. 5) Using the VIVO import/export we can add new information from Google Scholar. 6) Using the VIVO-CERIF translator we can obtain the information in another format.

Benefits 1) We have increased the information in VIVO.

Benefits 2) We have transformed VIVO to an open standard from the EU  

Benefits 3) We can explore data given by VIVO relations

Obtain sources for hacking Use a public VIVO instance. http://datahub.io/es/dataset/vivo-cornell-university 2) Obtain a VIVO instance from SPARQL endpoint. Using the command CONSTRUCT. http://sparql.vivo.ufl.edu/ 3) Use a CERIF instance and translate it with the VIVOCerif translator. http://www.eurocris.org/Uploads/Web%20pages/CERIF-1.5/ (cfRMAS xml file)

Useful links VIVO project. http://www.vivoweb.org/ 2) VIVO ontology. http://vivoweb.org/files/vivo-core-public-1.5.owl 3) VIVO import/export. https://github.com/ieru/vivo-io 4) VIVOCerif translator. https://github.com/ieru/cerif2vivo 5) CERIF .xml to .sqlhttp://sourceforge.net/projects/ceriftgtoolbox/ 6) CERIF to CERIF-LD. https://code.google.com/p/cerif-linked-data/

Thank you! Alberto Nogales Alcalá University (UAH) alberto.nogales@uah.es

Supported by EU projects