  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.
