Knowledge and information management research is a vital field within Information systems that explores how data, information, and knowledge are effectively captured, organized, and utilized to drive decision-making and innovation. This research spans topics from knowledge creation to information storage and retrieval, addressing challenges in managing organizational knowledge assets. JoVE Visualize enhances this exploration by pairing PubMed articles with JoVE’s experiment videos, providing readers a deeper understanding of research methods and real-world applications critical to this dynamic discipline.
Established methods in this field often involve systematic frameworks for knowledge capture, classification, and dissemination, including knowledge mapping, ontology development, and information architecture design. Techniques such as qualitative case studies, metadata analysis, and database management are widely applied to understand knowledge flows and optimize information systems. These approaches support the development of effective knowledge bases and content management systems, addressing fundamental aspects like the difference between information management and knowledge management.
Recent advances incorporate artificial intelligence, machine learning, and semantic web technologies to enhance knowledge discovery and automate information processing. Innovative methods include the use of natural language processing to extract insights from unstructured data and blockchain for secure knowledge sharing. Research also explores the integration of cognitive computing with knowledge management systems to improve decision support. These emerging trends reflect the evolving landscape of knowledge and information management jobs and aim to bridge gaps between traditional practices and futuristic applications.
S Sengupta, P D Clayton, P Molholt, R V Sideli, J J Cimino, G Hripcsak, S B Johnson, B Allen, M McCormack, C Hill
D C Jones, G E McKay, F A Zacharewicz
A D Morris, D I Boyle, A D McMahon, S A Greene, T M MacDonald, R W Newton
M T Moss
S A Eisenstadt, M M Wagner, W R Hogan, M C Pankaskie, F C Tsui, W Wilbright
Xia Ning, Ziwei Fan, Evan Burgun, Zhiyun Ren, Titus Schleyer