Advanced Visual Analytical Reasoning for Technology and Innovation Management (AVARTIM)

In view of increasing competition requirements and high market dynamics, the early recognition of technological trends and the targeted handling of market and technology signals are becoming increasingly important for companies. As part of the project, “AVARTIM” is to be used to develop a software-supported process for recognizing and evaluating trends, market and technology signals in order to sustainably support the process of innovation and technology management. As part of the project, an infrastructure will be set up at Darmstadt University of Applied Sciences, which is modular and thus able to react quickly to technological changes. The infrastructure to be developed here serves as preliminary research and initial technology both for industrial use by and with the SME partners as well as for the application for joint projects. First of all, participation in the LOEWE funding line 3 of the state of Hessen and subsequently in the tender for LEIT-ICT / Big Data technologies of the EU is aimed at.

By integrating a holistic data transformation from heterogeneous raw data to visual-interactive analysis, AVARTIM gets its innovative character tools that empower people to understand complex issues, infer conclusions, and make decisions. As part of this project, the focus will be on those trends and signals that appear very early in the technological life cycle. This information can be obtained primarily from conference papers, journals and primary literature sources (WTI Frankfurt, Springer, CrossRef, etc.).

The potential of these early trends is often not good enough to assess to introduce them to the market. This is exactly where AVARTIM comes in and enables the automatic extraction of “phrases” and “topics” (text mining) to recognize similarities to other successful technologies and to create hypotheses in the visual analysis process.

The technological unique feature of AVARTIM lies in the interaction of humans and computers, in which the disadvantages of machine learning methods for information extraction, in particular text mining, are compensated by simple visual-interactive solutions and thus by humans themselves. The starting point for the scientific data is the TEMA database of the cooperation partner WTI-Frankfurt as well as open access data from various data providers, such as Springer or CrossRef. C21-Consulting GmbH and dk & company GmbH as experts in the area of strategy consulting will test and validate the use of the developed technologies with different clients. The results then flow back into the development process, creating an iterative process of research, validation and development.

The project is funded by the funding program “Forschung für die Praxis” of the Hessian Ministry of Science and Art.