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Higher Education Performance Global Data
Education & Learning Analytics
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About
This dataset, titled "Ultimate University Ranking," offers a centralised collection of global university rankings. It measures the calibre of universities worldwide, drawing on key indicators such as research output, academic standing, student satisfaction, and international engagement. This data is invaluable for individuals considering higher education, academics seeking teaching opportunities, and investors making informed decisions. Furthermore, universities can leverage this resource to evaluate their performance and pinpoint areas for development. The dataset amalgamates information from various established ranking sources over several years, with data directly collected from web pages when direct export options are unavailable.
Columns
The dataset includes the following columns, which are instrumental in evaluating university performance:
- World Rank: The global position of the university.
- Institution: The name of the university.
- Location: The country where the university is situated.
- National Rank: The university's rank within its own country.
- Quality of Education: A metric assessing the standard of education provided.
- Alumni Employment: Indicating the employability of graduates.
- Quality of Faculty: Reflecting the calibre of the academic staff.
- Publications: Measuring research output through published works.
- Influence: Pertaining to the university's impact on research and scholarship.
- Citations: The number of times a university's research has been cited.
- Patents: Reflecting innovation through patent registrations.
- Score: An overall aggregated score for the university's performance.
Distribution
The data files are typically presented in CSV format. The dataset is structured as an aggregation of different university ranking systems, with separate files often provided for various years and ranking bodies. For instance, the Center for World University Rankings (CWUR) data is divided into 11 distinct CSV files, each corresponding to an academic year from 2012-2013 up to 2022-2023. The total size for version 1 of the dataset is 24.43 MB. Specific row or record counts for individual files are not explicitly stated.
Usage
This dataset is ideal for a variety of analytical and strategic applications, including:
- Performance Tracking: Analysing the performance trajectory of specific universities across different metrics over time.
- Cross-Country Comparisons: Facilitating comparisons between universities in various countries or even continents.
- Factor Correlation Analysis: Investigating how different ranking factors correlate and influence a university's overall standing.
- Pattern Identification: Discovering common characteristics among universities within a particular category or uncovering underlying patterns in their performance factors.
Coverage
The dataset offers a global geographic scope, encompassing universities from around the world. Examples of countries with featured institutions include the USA, United Kingdom, Japan, Switzerland, and Israel. The time range for the aggregated data spans multiple years, varying by the original ranking source:
- Center for World University University Rankings (CWUR): 2012 to 2023
- UI GreenMetric World University Ranking: 2016 to 2022
- CWTS Leiden Ranking: 2018 to 2022
- Nature Index: 2015 to 2022
- QS World University Rankings: 2022 to 2023
- Times Higher Education (THE): 2011 to 2023
- University Ranking by Academic Performance (URAP): 2018 to 2023
- Webometrics Ranking of World Universities: 2012 to 2022
The dataset's focus is on institutional metrics rather than specific demographics.
License
CC0: Public Domain
Who Can Use It
This dataset serves a diverse group of users, including:
- Prospective Students: To assist in making informed decisions about which university to attend.
- Educators and Researchers: For those seeking academic positions or conducting studies on higher education trends.
- Investors: To guide investment decisions related to the education sector.
- University Administrators: To assess their institution's competitive standing and identify areas for strategic improvement.
- Data Scientists and Analysts: For conducting in-depth research, developing predictive models, or creating data stories related to global higher education.
Dataset Name Suggestions
- Global University Insights Dataset
- Academic World Rankings Compendium
- Higher Education Performance Global Data
- Multi-Ranking University Data Hub
- University Excellence Metrics
Attributes
Original Data Source: Higher Education Performance Global Data
QUALITY