Releases: Aurora-Network-Global/sdg-queries
'improved' version 2021
(update: minor adjustments; corrected the placement of typo's based on user feedback)
In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Vanderfeesten, Maurice, Spielberg, Eike, & Gunes, Yassin. (2020) Survey data of "Mapping Research output to the SDGs" by Aurora Universities Network (AUR). We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goals”, Mendeley Data, v1. And thirdly we got inspiration from this controlled vocabulary containing closely related terms. Duran-Silva, Nicolau, Fuster, Enric, Massucci, Francesco Alessandro, & Quinquillà, Arnau. (2019). A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals (Version 1.2) [Data set]. Zenodo. |
'improved' version 2020
(update: minor adjustments; corrected the placement of quotation marks based on user feedback. )
In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Vanderfeesten, Maurice, Spielberg, Eike, & Gunes, Yassin. (2020) Survey data of "Mapping Research output to the SDGs" by Aurora Universities Network (AUR). We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goals”, Mendeley Data, v1. And thirdly we got inspiration from this controlled vocabulary containing closely related terms. Duran-Silva, Nicolau, Fuster, Enric, Massucci, Francesco Alessandro, & Quinquillà, Arnau. (2019). A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals (Version 1.2) [Data set]. Zenodo. |
'improved' version
(update: minor adjustment; replaced all quotation mark notations by straight quotations marks; for reducing syntax errors in Scopus API)
In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Vanderfeesten, Maurice, Spielberg, Eike, & Gunes, Yassin. (2020) Survey data of "Mapping Research output to the SDGs" by Aurora Universities Network (AUR). We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goals”, Mendeley Data, v1. And thirdly we got inspiration from this controlled vocabulary containing closely related terms. Duran-Silva, Nicolau, Fuster, Enric, Massucci, Francesco Alessandro, & Quinquillà, Arnau. (2019). A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals (Version 1.2) [Data set]. Zenodo. |
'improved' version
In order to better reflect academic representation of research output that relate to the SDG's, we have added more keyword combinations to the queries to increase the recall, to yield more research papers related to the SDG's, using academic terminology. We mainly used the input from the Vanderfeesten, Maurice, Spielberg, Eike, & Gunes, Yassin. (2020) Survey data of "Mapping Research output to the SDGs" by Aurora Universities Network (AUR). We ran several text analyses: Frequent term combination in title and abstracts from Suggested papers, and in selected (accepted) papers, suggested journals, etc. Secondly we got inspiration out of the Elsevier SDG queries Jayabalasingham, Bamini; Boverhof, Roy; Agnew, Kevin; Klein, Lisette (2019), “Identifying research supporting the United Nations Sustainable Development Goals”, Mendeley Data, v1. And thirdly we got inspiration from this controlled vocabulary containing closely related terms. Duran-Silva, Nicolau, Fuster, Enric, Massucci, Francesco Alessandro, & Quinquillà, Arnau. (2019). A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals (Version 1.2) [Data set]. Zenodo. |
uniform 'split' version
Over the course of the years, the UN changed and added Targets and indicators. In order to keep track of if we missed a target, we have split the queries to match the targets within the goals. This gives much more control in maintenance of the queries. Also in this version the use of brackets, quotation marks, etc. has been made uniform, so it also works with API's, and not only with GUI's. His version has been used to evaluate using a survey, to get baseline measurements for the precision and recall. Published here: Survey data of "Mapping Research output to the SDGs" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385
'echo chamber' version
We noticed that using strictly the terms that policy makers of the UN use in the targets and indicators, that much of the research that did not use that specific terms was left out in the result set. (eg. "mortality" vs "deaths") To increase the recall, without reducing precision of the papers in the results, we added keywords that were obvious synonyms and antonyms to the existing 'strict' keywords. This was done based on the keywords that appeared in papers in the result set of version 2. This creates an 'echo chamber', that results in more of the same papers.
Reviewed 'strict' version
Same as version 1, but now reviewed by peers. In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use keyword-combination searches as much as possible rather than single-keyword searches, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has been reviewed by peers.
Initial 'strict' version
In this version only the terms were used that appear in the SDG policy text of the targets and indicators defined by the UN. At this point we have been aware of the SDSN Compiled list of keywords, and used them as inspiration. Rule of thumb was to use keyword-combination searches as much as possible rather than single-keyword searches, to be more precise rather than to yield large amounts of false positive papers. Also we did not use the inverse or 'NOT' operator, to prevent removing true positives from the result set. This version has not been reviewed by peers.