In 2015 the United Nations and all its member states adopted the 2030 Agenda for Sustainable Development in order to, in the words of the UN, “provide a shared blueprint for peace and prosperity for people and the planet, now and into the future”. The core of this agenda was represented by the 17 Sustainable Development Goals (SDGs), which represented a call to action to all signatories to achieve major global challenges by 2030. Since their inception, the SDGs have provided a lightning rod for many researchers and institutions for impactful research to be carried out in order to meet the impending deadline.
Classifying the SDGs
In 2020, seeing the need to support the research ecosystem in this endeavour while recognizing increasing activity around the SDGs, the Dimensions team – in association with Springer Nature and the Digital Science Consultancy – worked together to build a classification system of research associated with the (SDGs) from the Dimensions publications database. This work uses machine learning and semi-automatically generated training data.
In the first phase of the project, an automated approach was used to categorize scholarly articles into five of the SDGs employing supervised machine learning whereby curated training data fed machine learning algorithms to automatically build a classification model that was then used to categorise new articles without human involvement.The second phase saw the project widened to include all 17 SDGs. The Springer Nature, Consultancy and Dimensions teams collaborated in this phase and Springer Nature subject matter experts assisted by manually assessing keywords for the training sets and identifying any false positives. The same automated approach was used for the research classification in Dimensions, the results of which has led to the next iteration in Dimensions which automatically assigns an SDG category to publications and grants when they are added to the Dimensions database.
How to use SDGs in research
Research in those areas related to SDGs is, of course, crucial in helping to redirect the world towards a more sustainable trajectory. Each SDG includes a list of targets and measures, and Dimensions enables researchers to filter this research by content type. This SDG classifier allows for specific analyses at the interface of numerous areas, such as research or policy. The SDG tags allow for links between environmental, social, economic and other SDG-related areas to be made, which means that new research areas and gap analysis can be developed independent of established disciplines.
An example of this can be seen in the blog post on Zoonotic diseases by Dr Briony Fane, Ann Campbell and Dr Juergen Wastl, which looked at analysis of Dimensions data that revealed disparities in funding towards the impacts of climate change on health using zoonotic diseases (where diseases are transferred from animals to humans) as an example. Accessing this data in the context of the SDGs is simple for any researcher. As you can see from the picture where the search term ‘zoonotic’ is used with the filter of SDG #13 (climate action) and results ranked by Altmetric influence score. The results cross several existing disciplines as seen in the Analytical Views section, showing that influence of SDG-related research is not limited to the anticipated disciplines.
Towards 2030
In 2023, the world is already past the halfway point from adoption of the SDGs in 2015 and the end goals in 2030. Never has it been more important for academic research to help the world become a more sustainable place, and as such using SDGs as part of that research process is becoming more and more crucial.
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