Authors: Minjian Liu, Qing Wang
Tags: 2016, conceptual modeling
In recent years, data analytics has been studied in a broad range of areas, such as health-care, social sciences, and commerce. In order to accurately capture user requirements for enhancing communication between analysts, domain experts and users, conceptualising data analytics tasks to provide a high level of modelling abstraction becomes increasingly important. In this paper, we discuss the modelling of data analytics and how a conceptual framework for data analytics applications can be transformed into a logical framework that supports a simple yet expressive query language for specifying data analytics tasks. We have also implemented our modelling method into a unified data analytics platform, which allows to incorporate analytics algorithms as plug-ins in a flexible and open manner, We present case studies on three real-world data analytics applications and our experimental results on an unified data analytics platform.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-319-46397-1_32
