A companion title to the International Journal of Information Management, IJIM Data Insights is a peer reviewed gold open access journal focusing on empirical evidences for information management using emerging data science methods.Data science is an emerging research methodology that contributes to information management through the influence of data analysis methods borrowed from disciplines like computer science, operations research and statistics. It attempts to extract knowledge and generate inferences by using a variety of methods, processes, algorithms and perspectives to provide actionable insights into a context or problem. The empirical evidences could be extracted from structured, semi-structured or unstructured data and contribute to information management and data driven decision making literature.IJIM Data Insights is interested in publishing state-of-the-art articles which address one or more the following themes and contexts:Empirical studies which use a data-driven approach for contributing towards information management literature.Data science and big data studies surrounding unstructured data analysis like opinion mining, sentiment analysis, text mining, image mining, video analytics and network science generated by individuals, groups, communities and firms.Studies which adopt emerging methods like machine learning and artificial intelligence algorithms for improving decision making and information management are welcome if they provide novel empirical evidences.Case studies on information management which demonstrate theoretical insights based on empirical evidences in an organizational or national setting.Studies in related disciplines in management and social sciences can be published if they contribute to information management and data-based decision making literature adequately.The journal publishes studies that validate theoretical models based on cross-sectional and longitudinal data, experiments, and even qualitative research. However, strength of data analysis for demonstrating findings objectively would be very critical for these studies to get published.Studies surrounding emerging technologies like blockchain, IoT and others which use machine learning and data science are welcome, if they are connected with information management and data driven decision making.Case studies which demonstrate a practical application of the methods and practices of projects using data science and information management would also be welcome.
