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| Jeff Spitzner, Rescentris |
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Jeff Spitzner, Ph.D., is a Founder and Chief Science Officer of Rescentris, and Adjunct Assistant Professor of Biomedical Informatics, The Ohio State University. In 1997 he co-authored data standards for integrating and exchanging genome research information that resulted in the development of BSML as the pioneering XML technology in the life sciences, today a widely adopted XML data standard in the industry. He is recognized as a leader in areas of bioinformatics, knowledge management, and electronic laboratory notebook systems. His current activities are in business development, science, and as product visionary for Rescentris' development of its Collaborative Electronic Research Framework (CERF), which uses semantic research ontologies to integrate electronic lab notebooks, informatics and knowledge management in order to provide an electronic record-keeping solution that enhances collaboration and R&D productivity.
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Applying Knowledge Assessment Techniques to Improving Productivity in Life Science Research
Barry Hardy, Douglas Connect & Jeff Spitzner, Rescentris
This presentation will discuss steps to be taken in the Knowledge Assessment of an R&D organization. Such an assessment initially obtains an overview of the current state of knowledge management in the organization and an identification of existing problem areas where actions could bring performance improvement. Areas to be investigated include knowledge gaps, bottlenecks, absence or under-utilisation of knowledge, lack of communication or collaboration, lack of access to or re-use of existing knowledge, difficulty in storing or retrieving knowledge, organizational or cultural issues, and barriers to knowledge sharing and innovation. The initial assessment can be subsequently followed by the introduction of new processes and tools as required, and a subsequent repetition of the assessment at periodic intervals as part of an ongoing performance improvement and support program.
The objectives of such a knowledge assessment and continuous improvement exercise are:
a) to assess the organization’s current situation and performance in a number of areas relating to the management and use of scientific knowledge and technical know-how;
b) to identify and prioritise areas for improvement in knowledge discovery, knowledge use and transfer and innovation;
c) to evaluate the effect that Electronic Lab Notebooks, Collaboration Support Systems and other IT and Knowledge Management tools is having, or is expected to have, on improving knowledge and innovation processes.
The benefits of such an approach are to:
* Allign R&D activities and knowledge processes with business strategies
* Improve productivity of R&D individuals and organisation
* Improve efficiency and reduce waste in R&D through knowledge loss or under-utilisation
* Increase knowledge sharing and innovation of R&D organisation
* Increase valuation of organisation through improved management of intellectual property and knowledge workers
* Improve quality of information captured from R&D processes
* Improve access to information captured from R&D processes
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Knowledge Assessment in R&D – Impact on Project Management & Research Productivity
Barry Hardy, Douglas Connect & Jeff Spitzner, Rescentris
We will discuss Knowledge Assessment techniques and their impact on Project Management & Research Productivity from the following perspectives:
* Assessing organisational performance in the categories of Managing Records & Information, Finding Information, Finding Expertise, Organisational Development, Collaboration, Leadership, Knowledge Utilisation, Knowledge Transfer, Innovation, Project Management, Training, IT, and Support
* Methods for performing a knowledge assessment (e.g., surveying, interviews, knowledge mapping, benchmarking, organisational structure analysis, culture measurement, social network analysis, IT systems analysis, etc.)
* Measures for tracking performance improvement in organisational performance and innovation
* How to identify key areas of weakness, priority and importance identified for next improvement steps
* Processes, change, modifications, initiatives, training etc. required to implement improvement steps
* Selection of technologies, software systems, tools, ontologies, controlled vocabularies, etc., - and including both new approaches and modifications to existing systems - to enhance organisational performance, innovation and knowledge management
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