Universal Knowledge Discovery from Big Data: Towards a Paradigm Shift from 'Knowledge Discovery' to 'Wisdom Discovery'
Abstract
Many people hold a vision that big data will provide big insights and have a big impact in the future, and big-data-assisted scientific discovery is seen as an emerging and promising scientific paradigm. However, how to turn big data into deep insights with tremendous value still remains obscure. To meet the challenge, universal knowledge discovery from big data (UKD) is proposed. The new concept focuses on discovering universal knowledge, which exists in the statistical analyses of big data and provides valuable insights into big data. Universal knowledge comes in different forms, e.g., universal patterns, rules, correlations, models and mechanisms. To accelerate big data assisted universal knowledge discovery, a unified research paradigm should be built based on techniques and paradigms from related research domains, especially big data mining and complex systems science. Therefore, I propose an iBEST@SEE methodology. This study lays a solid foundation for the future development of universal knowledge discovery, and offers a pathway to the discovery of "treasure-trove" hidden in big data.
Keywords
Cite
@article{arxiv.1403.7570,
title = {Universal Knowledge Discovery from Big Data: Towards a Paradigm Shift from 'Knowledge Discovery' to 'Wisdom Discovery'},
author = {Bin Shen},
journal= {arXiv preprint arXiv:1403.7570},
year = {2014}
}
Comments
Significance: First, UKD is highlighted as a golden key to the "treasure-trove" hidden in big data. Second, it answers how to integrate the fourth paradigm with the previous three paradigms (i.e., experimental research, theoretical research and simulations) for scientific discovery. Third, an interdisciplinary research paradigm is proposed. Thus, a paradigm shift will be triggered in data mining