Abstract
The objective of the article is to show the algorithm of international relations geoinformation mapping. During the mapping we can mine unknown or hidden knowledge which can be understood from the spatial database and improve the ability of interpreting data. The algorithm of mapping can be divided into five phases described as follows: investigation of potential map user’s demands, spatial data analysis and selection (accuracy, consistency, fullness); scale, map projections and map composition choice (main meridian, map frame, map distortions), spatial data preprocessing (metadata description, data normalization, data generalization, data quality control, error detection, anomalies, duplication and noise detection, correction of errors, data deduplication), data mining (creation of classifications, cluster and factor analysis, decision trees, neural networks, self-organizing maps, association rules, quality assessment), map creation, knowledge representation and evaluation. The article arranges experience of international relations geoinformation mapping. The international relations maps of Ukraine potential users (state and region management, educational, cultural, advocacy, international marketing and advertising, media business), subjects (substance, energy and information flows) and indicators arrays are proposed. Main subjects of maps can be described as follows: military-political, economicpolitical, socio-political and ideological relations; migrations and refugees, international tourism, export and import of goods and services, information flows (flows of culture elements, artifacts and tangible cultural monuments, scientific knowledge, ideas, technologies, traditions, beliefs, ideology, etc.), transport and business infrastructure. The requirements for spatial data sources for international relations geoinformation mapping are defined. The algorithm of international relations static and interactive maps creation and analysis are founded. The flow chart of Ukraine international relations geoinformation mapping algorithm is presented.
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More From: Bulletin of Taras Shevchenko National University of Kyiv. Geography
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