Knowledge Organization is a branch of the library and information science, concerned with activities such as document description, indexing, and classification performed in libraries, databases, archives, etc. It is the process of creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieving organizational objectives by making the best use of knowledge. It focuses on activities carried out and tools used by people who work while accumulating information resources, for the use of human being. This is in favor of making resources findable, the process of finding resources is transitionally human-based, performed by librarians or archaists. Now they are facing a challenge of computational algorithm techniques like big data and data mining.
Divergent historical and theoretical approaches towards organizing knowledge are based on different views of knowledge, cognition, language and social organization. This richness leads itself to many complementary ways to consider knowledge organization. Therefore organizational objectives can be approached, the process includes improving performance, competitive advantage, innovation and sharing of lessons learned. These efforts overlap with organizational learning and may be distinguished from that by a greater focus on the management of knowledge as a strategic asset and on encouraging the share of knowledge
One of the most important aspects during the construction of Knowledge organization is Knowledge. The knowledge is expected to be professionally built-in advanced logic and format into computer systems in order to perform better human decision-making and high-level cognitive tasks. This requires a knowledge engineer to supply some or all of the knowledge that is eventually contributed to the technology. From human logic and knowledge to technology, transferring principle gives out the way to a more popular model, which involves the simulation of human knowledge instead of a direct transfer from human to machine.
Knowledge relies on several aspects like a big repository for data, a complex system of algorithms. In this case, human decision-making can be stimulated even on critical problems. The knowledge engineer is useful in decision support software projects, geographical information systems and other technologies that deal with data analytics.