Knowledge Management (KM) is the term used to describe a set of practices used to capture, organize, store and distribute the collective knowledge of an organization typically found in documents, processes and people, individuals or groups. Typical KM programs attempt to appropriately represent, store and facilitate access and use of knowledge. Currently, several computational technologies are available addressing aspects of the KM problem. Examples of these technologies are expert systems, rule-bases, knowledge-bases and knowledge-repositories.

The evolution of the KM field is closely related to the advances in knowledge extraction from large amounts of data: Unless data and information are regularly being processed and knowledge is extracted there is no pressing need for a knowledge management process. Nonetheless, some aspects of KM have always existed in one form or another. Among them Knowledge Transfer has always attracted substantial attention and so formal apprenticeship, professional training and mentoring programs as well as corporate libraries have been introduced. However, with the increased volumes of more complex data and the advances in the knowledge extraction field efforts for knowledge transfer, as well as knowledge management in general, need to be further organized to match the challenges.

In the field of chemoinformatics, the increase in the size and complexity of the data generated during the drug discovery process have resulted initially in efforts on the capture and storage of data. Later, knowledge extraction techniques have been applied to produce knowledge to support decision-making at various steps of the drug discovery process. Typically, the generated knowledge has been project-specific and as such it has been exploited systematically only for the purposes of that project. Knowledge storage reflected this line of thinking and as a result several independent, non-communicating "islands" of knowledge were generated. This lack of organization lead to a fragmented environment which impedes knowledge distribution and re-use.

At Noesis we believe that the abundance of data and subsequent generated knowledge has to be fully exploited through an integrated knowledge management system. Accordingly, there need to be methods in place to capture the knowledge produced, represent it in a standard form, organize and store it in a unified knowledge-warehouse and make it available through a user-friendly environment. Noesis' software is designed so that it can integrate structured databases and use knowledge-bases to guide internal search and optimization processes. Our software is also designed to export the knowledge it produces in a standard form so that it can be preserved and shared within an interactive knowledge management system. Noesis also offers consulting services on KM system requirement gathering, specifications and design as well as customization services to extend its software to accomodate customers' individual needs.