Publishing Linked Open Data about University Scientific Outputs using the VIVO Ontologypptx.pdf. (8.51 MB)

Publishing Linked Open Data about University Scientific Outputs using the VIVO Ontology

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Version 2 2015-10-01, 02:44
Version 1 2015-08-18, 16:24
posted on 2015-10-01, 02:44 authored by Roberto Garcia, Jordi Virgili-Gomá, Rosa Gil
Initiatives promoting that institutions open their data are starting to have impact and slowly but consistently, as reported for instance by the World Wide Web Foundation in its Open Data Barometer . This is also reaching universities, especially public universities, which under budgetary constraints must transparently show where resources are spent and what results are being obtained. 
In many cases, as in the one reported here, all the data is already available but scattered across different information systems and databases controlled by different institution units and using different vocabularies and custom terms. Therefore, the first step in order to provide an integrated view of all this data is to define a reference vocabulary. 
Universitat de Lleida, a Spanish university, is currently undergoing this Linked Open Data publishing process of all its the research outputs. This includes papers, research projects, patents, grants, PhD thesis, etc. Given the broad range of entities under consideration, many of the evaluated reference vocabularies failed short in their coverage and required the combination of many different vocabularies, with the consequent integration burdens at the conceptual level. 
However, the VIVO Ontology, part of the VIVO project, showed the right coverage as it included all the required entities and a wide range of properties that cover their interrelationships. Moreover, it is built on top of well know and already commonly used ontologies like the Bibliographic Ontology (BIBO), which facilitates its adoption. 
This document reports about the experience mapping existing institutional databases at Universitat de Lleida, containing information about scientific outputs, their impacts, involved researchers, their organization into research groups, etc. All these data is then published in an integrated and semantic form, as Linked Data, using a semantic data exploration tool called Rhizomer . 
The aim is to facilitate the exploration and visualization of all the available data about scientific production, also facilitating the automation of the generation of reports like annual research reports at the department, research center or at the level of the whole university.