Dataset- Bibliometric and Sociometric Study of Spanish University Scientific Production in SDG Topics (2019–2023)
Description
This dataset supports a bibliometric and sociometric analysis of Spanish universities' scientific production related to the United Nations Sustainable Development Goals (SDGs) for the period 2019 to 2023. This research is framed in the R+D+i Project "Spanish Universities in the Media" (MECU-ESP): Methodological Strategies and Web Tool for the Study and Classification of News Dissimination" PID2023-153339NA-I00 funded by the Ministry of Science, Innovation and Universities. Co-funded by the European Union. State Research Agency. University of Malaga, Spain.
The data were extracted from the InCites database and compiled into three Excel files. The dataset enables a comprehensive evaluation of the volume, impact, and interrelations of scientific output aligned with the SDG framework within the Spanish higher education system.
Contents:
The dataset includes the following five files:
-
Total Scientific Production (2019–2023) Spanish Universities:
This file includes bibliometric data on the total scientific output of Spanish universities during the period, with metadata on institutions, publication counts, and research areas. -
Average Normalized Impact per SDG (2019-2023) All Spanish Universities:
Contains data on the average normalized citation impact of publications, aggregated by university and SDG category, enabling comparisons of scientific influence across institutions and goals. -
SDG–University Relations Matrix:
This file presents the distribution and intensity of research output by Spanish universities across the 17 SDGs, facilitating sociometric analysis of institutional focus areas.
Format: Microsoft Excel (.xlsx)
Source: InCites (Clarivate Analytics)
Coverage: Spain | Time Period: 2019–2023
This dataset can serve as a resource for researchers, policymakers, and academic administrators interested in evaluating the contribution of Spanish universities to the global sustainability agenda through their scientific output.
Files
Files
(205.8 MB)
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