Based on the principle ‘to measure is to know’, Aurora has developed the SDG Research Dashboard, SDG classification model based on a query language and the SDG classification model Machine Learning Multi-lingual Text Classifier.
The SDG Research Dashboard aims to provide insight into the scientific publications from European universities in the Aurora consortium that are related to the Sustainable Development Goals (SDGs) of the United Nations. The dashboard indicates whether the research is openly accessible and shows the extent to which policymakers reference a research paper.
The SDG classification model based on a query language has been created to match research papers within Aurora universities to the SDGs and can be used for reporting on SDGs within universities and strategy analysis by University leadership. This model uses keywords and advanced Boolean operators to search for research output that relates to each of the targets within the SDG’s. This has been done in consultation with the Aurora research community.
The SDG classification model Machine Learning Multi-lingual Text Classifier aims to classify research output written in multiple European languages, be independent of the use of query language specifics from research index databases, and get more relevant research papers that would have been left out using keywords.
The support centre is set up to answer questions of Aurora members and guest alliances on how to use services like the SDG classification model based on a query language and the SDG classification model Machine Learning Multi-lingual Text Classifier and the SDG Research Dashboard. Contact us for more information and support.
Aurora is a partnership of like-minded and closely collaborating research‑intensive European universities, who use their academic excellence to drive societal change.
Co-funded by the Erasmus+ Programme of the European Union
This project has received funding from the European Union´s Horizon 2020 research and innovation programme under grant agreement No 101035804
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