Initial Situation

Nowadays, an advance in knowledge and information is an increasingly important factor of competition. The challenge is to partition the growing quantity of information, knowledge and data and to process it in order to make an easy, but comprehensive, research possible.

Numerous internal and external information sources have to be browsed one by one for searching for information in the research field of healthcare. Thereby, the different kinds of research in the different systems make the work of scientists much more difficult. The available solutions cannot provide a comprehensive view on a topic, detect coherences between the different types of information or simplify the information research. Therefore, potentials of research can not - or not fast enough - be detected. Furthermore, the complex information research wastes a lot of time and money.

Our Solution: QuePort

Therefore, an intelligent content management software such as QuePort is required which can control the rising flood of information and detect relevant knowledge. QuePort helps to guarantee that the employees are comprehensively provided with all the relevant information concerning a certain topic. All the information that the employees are allowed to access is provided within a uniform research tool. In addition, the costs and the time effort for the practical training and information research can be reduced due to the easy operation.

What is unique about QuePort?

A platform for the aggregation of information and for research can be installed by the help of the intelligent content management software QuePort which networks information from internal (e.g. knowledge and document management systems) and external sources of knowledge (e.g. Pubmed) in a content-related way. Therefore, metadata contained in the information and relevant keywords are automatically extracted. The networked data are made available for the employees via a uniform research portal. Subsequently, the results are processed visually and can be compared to each other, e.g. using crosslinks or the visualisation of relationships in cross-classified tables. Furthermore, graphic filters and possibilities of navigation and comparison, which are individually adaptable to the corresponding research, are provided for the illustration of information. In addition, the contents are automatically expanded by information from external systems e.g. genetic databases.

In order to reduce the costs and effort of system management, certain topic pages can be defined and automatically filled up with current contents.