Crawling public massive data to solve air traffic data issues

Globalization brought a set of factors that led to the promotion of some geographical areas strategic to the growth and evolution of the global financial, economic and commercial systems. The study of Global Cities emerged as a key concept to identify and characterize cities as main agents in the performance of the world economy, i.e., World Cities (WC). There is consensus on how to identify market leader cities worldwide. Nevertheless, the classification criteria has been proven a difficult task. Similarly, there is criticism on the results obtained with these studies, especially due to the scarcity of data, compromising many published results. Missing data along consequent years justifies the lack of scientific publications about the evolution of World City Networks. Recent researches are also associated to 'lack of data'. This paper identifies these problems as the '7 deadly sins' of World Cities, and examines how these deficiencies may be corrected using a unique air traffic dataset, the POAT (Public Online Air Traffic) data. This research should propel the study of World Cities to more reliable and undisputed results through the use of sophisticated data analysis techniques.