The project “Visual Analytics for Corporate Foresight” (VSights) aims to develop a core technology for corporate foresight. The open-access datasets of the major scientific publishers, such as Springer, ACM, IEEE, etc., will be extracted and normalized by a transformation process of natural language processing and machine learning. The automatically extracted terms are recognized as technologies using learning-based named-entity recognition methods and extracted as time series that can lead to prediction. The prediction will be realized with different neural networks, and the whole results will be visualized interactively with a web-based visual analytics system in order to actively involve humans in the whole process of analysis. In addition, an industry model is to be created in order to be able to model an assignment of the technologies to potential markets. In addition to industry information and industry-specific technologies, this model should contain possible characteristic values for energy and emissions. Furthermore, the industry model will be used for market potential analysis. In this way, possible markets for the identified technologies can be “discovered” anew. The result of the project is a holistic system for strategic foresight for companies.

This project is funded by the Ministry of Science and the Arts (HMWK) within the framework of the academic mid-level program.