The processes of generating innovative solutions mostly rely on skilled experts who are usually unavailable and their outcomes have uncertainty. Computer science and information technology are changing the innovation environment and accumulating Big Data from which a lot of knowledge is to be discovered. However, it is a rather nebulous area and there still remain several challenging problems to integrate the multi-information and rough knowledge effectively to support the process of innovation. Based on the new cross discipline Extenics, the authors have presented a collaborative innovation model in the context of Big Data. The model has two mutual paths, one to transform collected data into an information tree in a uniform basic-element format and another to discover knowledge by data mining, save the rules in a knowledge base, and then explore the innovation paths and solutions by a formularized model based on Extenics. Finally, all possible solutions are scored and selected by 3D-dependent function. The model which integrates different departments to put forward the innovation solutions is proved valuable for a user of the Big Data by a practical innovation case in management.

Individual innovation capability is a principal element in enterprise independent innovation and new state construction. College students are the major force of the future innovations. However it lacks feasible means and methods to promote college students’ innovation capability. In this paper, the functions and performances of Creativity theory and Extenics are analyzed, and the existing major innovation methods are compared from the perspective of capability promotion. Then we present a combined training model for promoting students’ innovation capability, in which the advantages of Creativity Study and Extenics are integrated and support each other. The effects of our model are proved by our teaching practice cases. This paper also provides a reference as a guidance to improve postgraduates’ innovation capability

Business intelligence (BI) has been becoming an important factor of the enterprise's core competence, especially in times of an economic downturn. The purpose of BI is get proper knowledge to make wise decisions on data and information; but most BI is partial or local, which lack of systematic information collection and processing. On the other hand, collect more information can lead to information and knowledge overload which make BI more and more difficult. A structured information collection method is designed based on extenics theory; it can collect proper data or information according to a information list cube integrating Web search technology and extenics, then process the information by data mining and extension transformation. Finally we store them in the element base which helps to get more solutions by intelligent knowledge management platform. It will accelerate the development of BI from a new direction.