In parallel with the developing and widespread use of information and communication technologies, the amount of data produced daily is increasing. The Journal of Data Applications aims to contribute to the development of applied data science studies, which aim to obtain meaningful information from data and reveal hidden patterns and patterns in data, thus contributing to the development of studies in this field.

Journal of Data Applications accepts computational and applied scientific studies such as original research and review on the field of data collection, storage, transmission, preprocessing, analysis, visualization, and interpretation of data, especially statistics, artificial intelligence, machine learning, deep learning, and data mining applications. In this context, the Journal of Data Applications has no discipline and application restrictions.

Scope of the Journal of Data Applications collapses from all disciplines in various fields such as information retrieval and extraction, clustering, predicting and forecasting applications, decision support systems, recommendation systems, image, sound and pattern recognition, and processing, natural language processing, signal processing, computer vision, big data processing, time series analysis includes various application studies from all disciplines in areas such as sentiment analysis, social media analysis, fraud, and anomaly detection.

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