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DBpedia Global Economic and Research Classification
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About
Exploring global economic and academic landscapes through the lens of knowledge graphs provides a structured way to categorise national performance. This resource extracts specific data for 160 countries from DBpedia, a large-scale knowledge base derived from Wikipedia. By binarising complex metrics such as inflation and research output, the data facilitates machine learning experiments and semantic web research. The information represents a subset of the broader DBpedia graph, offering a focused look at how nations relate to their geographic and economic indicators.
Columns
- Country: The unique DBpedia URI representing each specific nation.
- Research Rating: A categorised metric of research output, labelled as either "high" or "low".
- Inflation Rating: A categorised metric of national inflation, labelled as either "high" or "low".
- Continent: The geographic classification of the country into one of five groups: Africa, Americas, Asia, Europe, or Oceania.
Distribution
The data is provided in a comma-separated values format titled
countries.csv, with a file size of approximately 7.99 kB. It contains 160 records, each with 100% validity across all four specified columns. This is a static release intended for research purposes without planned future updates.Usage
This resource is perfectly suited for multi-class and binary classification tasks within machine learning workflows. It can be used to train models to predict geographic location based on economic indicators or vice-versa. Additionally, it serves as a valuable tool for those exploring the integration of knowledge graphs into semantic web applications.
Coverage
The scope is global, encompassing 160 individual countries distributed across five major continents. The data was retrieved using the DBpedia SPARQL endpoint and represents a snapshot of the knowledge graph at the time of extraction, covering diverse regions including Africa, the Americas, Asia, Europe, and Oceania.
License
CC BY-NC-SA 4.0
Who Can Use It
Data science students can utilise these records to practice classification algorithms on a clean, structured dataset. Academic researchers focusing on the "Semantic Web for Machine Learning" may find the links to DBpedia URIs particularly useful for graph-based analysis. Furthermore, economists interested in simplified, binarised comparisons of global inflation and research trends can leverage this information for preliminary studies.
Dataset Name Suggestions
- DBpedia Global Economic and Research Classification
- 160 Countries: Academic and Inflation Knowledge Graph
- Semantic Web Country Information Snapshot
- Global Research Output and Inflation Indicators
- Knowledge Graph Geographic and Economic Indices
Attributes
Original Data Source: DBpedia Global Economic and Research Classification
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