7 - Mechanisms for the management of University-Business relationships
7.1 - Promoting the creation of databases to facilitate information management
Introduction
Databases are one of the most widely used tools when trying to enhance research and production processes, and market new goods and services. They are also of great significance in the process of collaboration between business and universities since they allow automation of the management of relevant information, a more efficient analysis of available supply and demand, improved methods of searching for compatible partners, and, in general, a simplification of the process of knowledge transfer between universities and companies. Many internationally renowned universities and technological centres (MIT, KIT, Imperial College, University of Uppsala, etc.), have created their own system of information management, so that both Companies and Universities are able to improve the monitoring of their patents, licences, publications and active lines of research. We would underline two critical aspects of the design of these databases: the volume of information to be managed and the need for regular updating. There are also numerous examples of business groups which have developed databases to manage their members’ information in terms of scientific and technical demand.
Apart from creating constantly updated databases with information on scientific-technical supply and demand requirements between Companies and Universities, another approach, called matchmaking, involves the development of a support system which correlates supply and demand and leads to the automatic generation of “couples” in specific fields. The development of these systems is extremely complex, since it is necessary to compile and organise a great deal of information, but they deliver results in a flexible and highly user-friendly manner. In order for them to operate successfully it is necessary to ensure that both “buyers” and “sellers” provide the most comprehensive and well-structured information possible, although efforts must be made to prevent the process from being so complex and laborious that it discourages potential users.
Examples
Research Data Base (Zurich, Switzerland)
A Virtual Web platform which offers updated information on the progress of research work at Zürich’s ETH. This specific and systematic information is accessible to anyone interested in the institution’s research initiatives. Additionally, the platform offers users the possibility of finding contacts or cooperation partners through the use of integrated communication functions, which also offer assistance when seeking research funds.
One of the main objectives of the system is to ensure that the specific information generated by researchers only needs to be incorporated into the ETH Zürich central registration system once, thus saving them a significant amount of administrative work. Subsequently, the information can only be updated by those who are formally registered in the system.
The ETH Zürich data management system (RDB) includes: a patent database from the Swiss Patent Office (Switt); a research projects database (via the ETH Research database), and various publications and citations (via the E-citations platform).
Dialogue (Scotland)
The Dialogue Programme, developed in Scotland between 2002 and 2006 with €707,500 of financial support from the EU’s ERDF fund, provided assistance to numerous companies in order to exploit existing intellectual assets and research projects in an advanced stage of development. The project team was responsible for developing a series of online resources to help companies find the initiatives which best matched their specific interests.
INNOSCOPE (France)
In 2002, Nord France Innovation Développement (NFID) developed an analysis tool which identified innovative companies through financial information compiled by an evaluation system structured into five specific sections. Of the more than 100,000 companies registered in Nord-Pas de Calais, 15,000 are on the INNOSCOPE database, with 3,000 of them having been classified as being of significant importance in terms of creativity and innovation.
Implementation process
Agents required for implementation
The setting up and implementation of an efficient database such as Mail Alert Technology and an automatic Match Database system requires close collaboration between Universities and Companies.
The implementation process could be speeded up if companies were to jointly provide technology and resources and collaborate in defining the requirements for the creation of the databases.
Sources
- Presentation of INNOSCOPE by NFID (Nord France Innovation Development). Visit to Nord-Pas de Calais.
- Interview with Mr. Berti. Research and Technology Transfer Office, University of Padua.
- Interview with Mr. Pereira (NIFD) and Mr. Pruvot, Director of NFID (Nord France Innovation Developpement).
- http://www.gla.ac.uk/innovationnetwork/ - Dialogue Proyect.
- http://www.jinnove.com/ - Nord France Innovation Developpement.
- http://www.imperialinnovations.co.uk/?q=technologies - Licence database of Imperial College (Imperial Innovations).
- https://www.rdb.ethz.ch/search/ - ETH Zurich Research Database.
- http://www.uu.se/ - Uppsala University Research.
- http://web.mit.edu/tlo/www/industry/PAL.html - MIT Technology Liaison Office (TLO) Patents available for Licensing (PAL).