IO Data Science (IO for Input/Output) is a homogenised access to metadata descriptions of datasets via a single point of access. The scientists can build, host and declare their datasets as open data or for restricted usage within the university. Scientists' machines can use SPARQL technology to read the metadata of available datasets and query some data using the sample queries available in this service.
Why homogenised access to metadata descriptions of datasets?300 laboratories constitute the research potential of the University Paris-Saclay. They cover all scientific disciplines that mobilise some 15,000 scientists, researchers and PhD teachers. These researchers produce more and more data during their works and on the other side, some scientists search new data for their research.
The service IO Data Science serve to build, host, link, discover and reuse the datasets between the producers and the consumers of data for creating new synergies between the laboratories.
List of publications :
- 2019 - Linked Data at university : the LinkedWiki platform (Paper version)
- 2018 - Designing scientific SPARQL queries using autocompletion by snippets
- 2017 - Une autocomplétion générique de SPARQL
- 2016 - Search Engine for Local Experts
- 2015 - A platform for scientific data sharing
- 2015 - Certifying the interoperability
- 2015 - Towards reproducible research
- 2014 - TFT, Tests For Triplestores