Objective of the project
TI Food & Nutrition aims to perform first class food research, leading to industrial innovation. Presently, the extent to which research information is stored highly depends on the individual attitude, skills and commitment of researchers. A great opportunity exists within TI Food & Nutrition to advance its organisational memory by establishing a common knowledge management platform. The contribution of the proposed project is to establish a sound knowledge management platform at TI Food & Nutrition. In recent years Tiffany has evolved into a mature system for maintaining research-related information within TI Food and Nutrition from research questions via materials, methods and data to final publications. The development of Tiffany is largely based on feedback from its users, combined with a long term vision on how information technology will affect research practice. The latter is embedded in national and international research in e-science. Interfacing with the other TI Food & Nutrition platforms and other existing knowledge repositories is crucial. Moreover, the exploitation by industrial experts can still be extended.
Presently, face-to-face contact between researchers and industrial experts is the prevailing way to share knowledge and to define and control research. Electronic infrastructures are mostly used.
locally, supporting individual researchers or project teams. New information technology would hugely benefit food researchers, but is at present often looked at with some mistrust. Although internet resources are in principle available they are not fully exploited yet. At the same time, the sheer volume of data produced by experiments grows exponentially. The quality of the information shared is not yet always optimal. For example, data cannot always be interpreted unambiguously given the format in which it is provided. With Tiffany we have already made important progress. However, to keep a competitive edge in this area further steps are needed. In particular the following long term perspectives are promising
Improved learning from past lessons and mistakes. Automated detection of related work. Smart spreadsheets and automated annotation. Dossier generation descriptions of materials, methods and results can be assembled to generate a dossier for a patents, publication, presentations, etc. Integration in industrial research process if the standards developed in this project are shared with the industrial partners, knowledge may diffuse more effectively.
Activities
2011 Q2 Tiffany established as default platform and part of TIFN- IT infrastructure
2011 Q4 Collaboration with other institutes established
2012 Q2 Personalized views for of industrial experts implemented
2012 Q4 Semantic data enrichment implemented
2013 Q4 Data integration between several data repositories realized, inside or outside TIFN.
2014 Q4 Electronic lab notes implemented across TI Food & Nutrition and integrated with Tiffany.
Output
Operation. A default knowledge access platform is established as part of the running IT infrastructure, based on Tiffany. This means that first line support and maintenance is transferred to TI Food & Nutrition IT support staff and outsourced where necessary. It also implies integration specific data repositories, e.g. for genomics related data and clinical trials.
Innovation. The core activity of this project will be to develop and apply new solutions in the area of e-science. This will incrementally strengthen the knowledge management platform, based on interaction with all stakeholders. We expect developments in particular along the following lines.
- User-centred views on food research output. Personalized and company-specific interfaces and alerts are ways to enhance involvement of industrial experts in TIFN research.
- Integrated electronic lab notes. True capturing of scientific knowledge starts in the lab. It has major impact on IPR, patenting and knowledge claims, but also on the efficiency of the individual researcher. The fast introduction of iPAD and other tablets will also have great impact.
- Data integration tools, enabling combination of data from different sources, systems and formats. Enriching research information with multimedia and semantics are interesting alternatives to the traditional publication.
- Collaboration. More advanced and experimental developments in e-science should be explored in collaboration with other (top) institutes. This activity will establish a cooperative effort (and funding) in this direction, which in turn will result in an improved KM platform for TIFN. |
