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Curating knowledge to foster accessibility, efficiency, and trust at KMWorld 2022

Knowledge management necessitates human curation; AI evolution, regardless of its progress, will need a human curator to sustain and leverage it effectively. The three main pillars of knowledge curation—knowledge capture and transfer; governance, including roles and responsibilities, vetting and assurance, performance monitoring, and incentives; and architecture, including tools, platforms, and processes—guide the expectations of how knowledge curation can transform the way knowledge is refined and organized.

At KMWorld 2022, Art Murray, CEO, Applied Knowledge Sciences, Inc. and  director, Enterprise of the Future Program, International Institute for Knowledge and Innovation, discussed best practices for knowledge curation in his workshop, “Building & Curating E-Bodies Of Knowledge.”

KMWorld returned in-person to the J.W. Marriott in Washington D.C. on November 7-10, with pre-conference workshops held on November 7.

KMWorld 2022 is a part of a unique program of five co-located conferences, which also includes Enterprise Search & Discovery, Office 365 Symposium, Taxonomy Boot Camp, and Text Analytics Forum.

According to Murray, everyone needs to be a knowledge curator to some extent. Murray provided a definition for context, explaining that knowledge curation is facilitating the capture, classification, organization, transfer, and management of individual, organizational, or community knowledge. He further elaborated on its relevance by stating that knowledge generation is at an all-time high and continues to grow; various trends like the Five V’s (volume, velocity, variety, veracity, and value), decision consequences, tacit knowledge acquisition, and AI-based automation directly impact knowledge curation.

According to Murray, Knowledge curation best practices include:

  • Deciding which knowledge is worth curating and in what form
  • Reconciling different world views, mental models, and learning modalities, especially among mentors and mentees
  • Determining which tools and approaches are appropriate for different types of knowledge
  • Integrating the various tools and approaches into a single system
  • Vetting knowledge, keeping it up-to-date, and making it flow and grow from a single individual to an entire community of experts and practitioners

Murray divided up these strategies into a comprehensive, 7-step knowledge curation plan that best leverages knowledge to its fullest extent within an organization, titled the “Knowledge Map.” 

The first step is making an initial assessment to determine a starting point. Investigative questions about how well your organization makes knowledge accessible, organized, structured, and curated informs the beginning steps necessary for employing effective knowledge curation. These key questions position where your organization must internally target to better foster knowledge processes and curation, and better underpin the knowledge workers that handle those processes.

Murray said the second step is deducing what knowledge should be curated for your enterprise. Knowing which knowledge is critical, assessing critical risk, knowing where critical knowledge resides, and knowing where knowledge needs to reside are vital towards building an effective knowledge network. Drawing tacit knowledge from workers can determine which knowledge is critical, accomplished by investigating the people, decisions, observations, analyses, decision-making, and actions that generate and handle knowledge. Knowledge risk is calculated through an equation, noted as Knowledge Risk=Pcondition x consequences, which fuels assessment of risk.

The third step focuses on the importance of format for your knowledge, dictating how effectively knowledge can be accessed, organization-wide. Modeling the baseline for which knowledge is shared with various sources can be a rather difficult process, yet a necessary one. Once the baseline is modeled, you must be able to describe the problem or challenge to yield any positive outcomes. Identifying the root causes and conditions is vital towards solving any challenges within the model, allowing you to model the solution and operate from predetermined building blocks.

Capturing and transferring modalities, the fourth step, consists of identifying the ways in which knowledge can be optimally shared for your organization, whether by human or machine. Murray urged his attendees to consider the preferred method of the knowledge source (human and machine) for imparting knowledge, as well as the preferred method of the knowledge recipient (human and machine) for receiving that knowledge. You must also determine how to “bridge the gap” between knowledge source and seeker, as well as determine the factors that impact information sharing, such as generational or learning/communication style differences.

In terms of best knowledge transfer methods, people can benefit from master classes, storytelling, job shadowing, case studies, flow diagrams, or demonstrating by those with expertise. Machines can transfer knowledge through simulation and gaming, fostering transfer through informative programs.

This abundance of knowledge must now be organized, making it the fifth step of Murray’s plan.. Ontologies can be built in two different ways to achieve efficient and effective communication and knowledge flows: manually and automatically. A manual system can look like an index card system, where the cards are used to capture and sort how people talk about the work they do, the lexicon they use, and what it means through categorization. In an automatic fashion, an AI/text analysis program would employ an out-of-the-box ontology that uses terms/synonyms entered by its implementor, without needing to build an ontology from scratch.

Murray’s sixth step toward empowering knowledge curation includes knowledge governance, which further breaks down into eight attributes of good governance:

  • Rule of law
  • Transparent
  • Responsive
  • Consensus-oriented
  • Equitable and inclusive
  • Effective and efficient
  • Accountable
  • Participatory

These attributes are achieved through on-going discourse attempting to capture all considerations involved, which then assures stakeholder interest, further being addressed, and reflected in policy initiatives.

The final step is infrastructure, involving architecture type, tools, and platforms for knowledge curation. You must decide whether your knowledge curation will be centralized, or in a common repository, or decentralized, at the source. Ultimately, it’s critical to ensure that the variety of tools and platforms that are being employed in the enterprise are aligned with the architecture, as well as its methods and practices.

Knowledge curation requires dependable, consistent, and supportive attitudes that foster careful listening, respect, patience, and sincerity to encourage knowledge sharing and achievement of goals. Murray warned to not criticize, attempt to rectify insurmountable problems, or confuse curation with management; ultimately, the purpose of curation is not to “fix” problems, but to enable better knowledge flows to the problem solvers.

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