Study on user customized data service model for improving data service reliability

New value was extracted through managing and analyzing huge volume of data in Big Data paradigm. With the paradigm, data environment such as Public Data and Data Market was built to collect and provide data for data users. Some issues to realize data-centric economy were naturally arisen. The Public Data or Data Market focused on an environment that data providers provide data to data customers. In other words, "Delivery" was focused. They had less consideration on "Use." For this reason, formats of provided data were different in each providers and ways of using data were also different. It was hard for data customers to use data. Data without applying data user's requirements occurred additional time and resource cost to use data. It was one factor to hinder the growth of data-centric economy. Therefore, a reference model and an algorithm were proposed in this paper. The reference model included the aspect of "Use" by considering data user's requirement. In order to consider data user's requirement, the algorithm considering relationship between data volume and limited time was surely necessary. The algorithm would support to maximize data availability and usability. The algorithm was used inside of the reference model to support in-time factor to guarantee service reliability satisfying various user's requirements. The concept and details of reference model and algorithm would be explained in the main body of this paper. Consequently, this paper could contribute for data customers to reduce additional computing and network resource usage because of providing data that is suitable for user's requirements. It might decrease battery and network consumption of mobile devices. In addition, Big Data analysis using this model might reduce processes of data collecting and preprocessing, and guarantee maximum data volume in limited time.