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

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

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

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 1)An open source web application. 2)Enables the discovery of researchers across institutions. 3)Based on local instances that can interconnect between them. 1)A standard for managing and exchanging research data. 2)Enables integrated research information environment. 3)Allows standardised exchange of information.

Our development in steps 1)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 File Format Version Bibtex cite* Number of cites Ranking in GS Authors Event Issue Date (year) Volume Start and end page DOI PMCID NIHMSID

Step2 Objective: Combine titles from OpenAGRIS obtained with the scrapper with titles stored in VIVO instances. Solution: 1)Combine information from scrapper database with VIVO information. Using titles. 1)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 VIVO.rdf Google Scholar GS scraper New Information New Information VIVO import/export VIVO import/export VIVO++.rdf CERIF CERIF-LD VIVO-CERIF Translator VIVO-CERIF Translator

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 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. 4) Looking at the VIVO ontology we know we can use a property to reference papers called “cites”.

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 1)Use a public VIVO instance. 2) Obtain a VIVO instance from SPARQL endpoint. Using the command CONSTRUCT. 3) Use a CERIF instance and translate it with the VIVOCerif translator. RIF-1.5/ RIF-1.5/ (cfRMAS xml file)

Useful links 1)VIVO project. 2) VIVO ontology owl 3) VIVO import/export. 4) VIVOCerif translator. 5) CERIF.xml to.sqlhttp://sourceforge.net/projects/ceriftgtoolbox/ 6) CERIF to CERIF-LD. data/

Thank you! Alberto Nogales Alcalá University (UAH)