All you need to do is to provide OpenAIRE with a ‘very limited’ set of metadata fields from your database and we will take it up from there.
Using text mining (topic modeling) on the full texts we can discover hidden structures and identify useful patterns, similarities, correlations trends and communities.
Our tech team would be happy to work with new use cases as this is the real value of using open science for transparent decision policy making. Our services have already been successfully applied for the evaluation of parts of FP7, and we are continuing with the rest.
AKA - Academy of Finland
SFI - Science Foundation Ireland
NWO - Netherlands Organisation for Scientific Research
FCT - Fundação para a Ciência e a Tecnologia
MESTD - Ministry of Education, Science and Technological Development of Republic of Serbia
SNSF - Swiss National Science Foundation
Tubitak - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
RCUK - Research Council
WT - Wellcome Trust
Apply cleaning, transformation, disambiguation processes to identify relationships among all research entities:publications, data, funding, researchers, organisations and data sources
Identify grant ids in publications-data-software acknowledgement sections and make the appropriate links
Link research results to funding information, specifically programme information
Create online reports and statistics based on the OpenAIRE scholarly communication graph
Combine the OpenAIRE data with other types of data and provide custom research analytics