Towards Developing Theories About Data: A Philosophical and Scientific Approach

Abstract

Similar to information and knowledge, data and especially big data are now known as one of the most vital elements in the 21st century since they provide multiple capabilities to individuals and organizations. However, in comparison to some theories about information and knowledge, there are no significant attempts in most scientific disciplines for building theories about data. This paper first reviews the different definitions provided about the concept of data in the works of scholars. It then identifies and explores the philosophical aspects as well as the multiple capabilities/features that can be derived from data. Finally, a starter list of some basic/general theories is developed based on the capabilities and features of data. Such new theories can be used as meta-theories to extend data theories for various scientific disciplines. The important notion supporting the development of theories about data is that, if data is so important and if data science is to continue flourishing in a variety of specialized fields and trends, then we need to build relevant theories about data for research and practical purposes in a multi-disciplinary context. Keywords: Data, big data, theory of data, philosophy of data.