Schengen Visa Statistics

Dataset Overview

Context

While the general application process and fees for Schengen visas are standardized, the implementation of these rules varies by country. Obtaining a long-term multiple-entry visa is advantageous as it requires the same effort but can be used for multiple trips, saving both time and money. Visa-shopping, where applicants select specific consulates to increase their chances of obtaining a visa or a higher-tier visa, is a common practice. To evaluate the validity of this practice, an analysis of real data is essential. This dataset provides the necessary information.

Content

This dataset contains comprehensive visa statistics for all States fully applying the Schengen acquis and their consulates in third countries. Data is presented in bulk, but filters on the top row allow for refined searches. For instance, users can filter data by Member State/Associated country, specific third countries, or specific locations (cities) in third countries.

Types of Visas

• Airport Transit Visas (ATVs): Allow transit through the international transit area of airports in Member States without entering the territory. These visas can be for single or multiple transits.

• Short Stay Visas:

  • Uniform Short Stay Visas: Valid for stays up to 90 days within a 180-day period across all Member States. These visas can be issued for single or multiple entries.
  • Limited Territorial Validity Visas (LTV): Valid only in the territory of specific Member States.

Acknowledgements

This data was provided by the European Commission in accordance with the Visa Code, Article 46, and Annex XII. The data for Bulgaria, Croatia, and Romania pertains to national visas.

Inspired by Schengen Visa Stats 2017/2018 by ma7555

Inspiration for Analysis

• Identify which consulates in each country are more generous.
• Determine which Schengen States are generally more generous.
• Find the strictest consulate.
• Explore many other insights possible with this dataset.

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This version aims to be more concise and clearer, making it easier to understand the context, content, and potential uses of the dataset.