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Search Queries for "Mapping Research Output to the Sustainable Development Goals (SDGs)" v3.0
No full textThis package contains machine readable (xml) search queries, for the Scopus publication database, to find domain specific research output that are related to the 17 Sustainable Development Goals (SDGs).
Sustainable Development Goals are the 17 global challenges set by the United Nations. Within each of the goals specific targets and indicators are mentioned to monitor the progress of reaching those goals by 2030. In an effort to capture how research is contributing to move the needle on those challenges, we earlier have made an initial classification model than enables to quickly identify what research output is related to what SDG. (This Aurora SDG dashboard is the initial outcome as proof of practice.)
The initiative started from the Aurora Universities Network in 2017, in the working group "Societal Impact and Relevance of Research", to investigate and to make visible 1. what research is done that are relevant to topics or challenges that live in society (for the proof of practice this has been scoped down to the SDGs), and 2. what the effect or impact is of implementing those research outcomes to those societal challenges (this also have been scoped down to research output being cited in policy documents from national and local governments an NGO's).
The classification model we have used are 17 different search queries on the Scopus database. The search queries are elegant constructions with keyword combinations and boolean operators, in the syntax specific to the Scopus Query Language. We have used Scopus because it covers more research area's that are relevant to the SDG's, and we could filter much easier the Aurora Institutions.
Versions
Different versions of the search queries have been made over the past years to improve the precision (soundness) and recall (completeness) of the results. The queries have been made in a team effort by several bibliometric experts from the Aurora Universities. Each one did two or 3 SDG's, and than reviewed each other's work.
v1.0 January 2018 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.
Download from: GitHub / Zenodo
v2.0 March 2018 Reviewed 'strict' version. Same as version 1, but now reviewed by peers.
Download from: GitHub / Zenodo
v3.0 May 2019 '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.
Download from: GitHub / Zenodo
v4.0 August 2019 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.
Download from: GitHub / Zenodo
v5.0 June 2020 '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 Survey data of "Mapping Research output to the SDGs" by Aurora Universities Network (AUR) doi:10.5281/zenodo.3798385. 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 https://dx.doi.org/10.17632/87txkw7khs.1.
Download from: GitHub / Zenodo
Contribute and improve the SDG Search Queries
We welcome you to join the Github community and to fork, improve and make a pull request to add your improvements to the new version of the SDG queries. https://github.com/Aurora-Network-Global/sdg-querie
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Annex 2020
Get PDFRapporten ger en översiktlig bild av Göteborgs universitets publiceringsverksamhet under perioden 2014-2018 på institutionsnivå
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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