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Innovative knowledge-sharing tools elevate the modern workplace

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The most meaningful developments to the knowledge-sharing space—and, by extension, to that of knowledge management as a whole—do not pertain to specific tools, platforms, or technologies.

Instead, they pertain to the goals of knowledge sharing, which have been irrevocably shaped by numerous forces in the modern workplace to include everything from distributed paradigms for working remotely to increasingly low latency responses characteristic of the digital age in which we live.

As such, today’s knowledge-sharing tools are designed for collaboration, engagement, interactivity, and crowdsourcing. The tools themselves have changed little over the past couple of years and still involve facets of data catalogs, taxonomies, search, text analytics, data discovery, and data governance.

What’s evolved, however, is their features, which have been updated for the sort of real-time interactions that make knowledge more accessible, reliable, and utilitarian than ever before.

The result is a range of options providing “rich knowledge assets that are interrelated,” said John Wills, field CTO of Alation. “They relate contextual knowledge, data assets, and experts, so users can find and understand what exists and collaborate with colleagues.”

Data catalogs

The boundaries between the various knowledge-sharing instruments are disappearing. Data catalogs involve taxonomies, which are useful for search and informing text analytics, too. These mechanisms are no longer respective. Data catalogs represent the epicenter of knowledge sharing in that they include metadata, tags, and classifications that form the basis of subsequent searches about enterprise knowledge-like documents, for example. These descriptions include “referential and contextual documents such as terms, KPIs, business processes, roles, and metrics,” Wills said. Catalogs also bolster knowledge sharing via:

Metadata management: Intelligent solutions automate the population of metadata about assets. This metadata describes assets and their users, their uses, data provenance, and more. According to Talya Heller Greenberger, director of product marketing at Bloomfire, it’s not uncommon for platforms to “auto-tag everything you upload, so you don’t have to.”

Recommendations: The point of cataloging enterprise knowledge is to provide a central place to steer users to information relevant to their particular needs. “If you have a metadata graph that links the domain objects in your enterprise to the data catalog, then you can start doing recommendations,” said Jans Aasman, CEO of Franz. “Like, here’s all the databases that are used the most for when people want to do something like this.”

Collaboration and sharing: The centralized nature of data catalogs is primed for user interactions about the value of knowledge assets. Engagement features include constructs for commenting, voting, and “the threaded conversation capability to ask questions and have a running dialogue with experts,” Wills noted. “These become part of the centralized, historical record where users learn from one another.”

Search: The ubiquitous search function redoubles the value of data catalogs as a locus to quickly find enterprise knowledge for specific use cases, such as identifying a subject matter expert’s response to a nagging HR problem.


As the specific terms, definitions, and hierarchies of terminology that are germane to individual organizations and their departments, taxonomies are quintessential enterprise knowledge. Often, taxonomies form an integral aspect of what Rigvinath Chevala, CTO of Evalueserve, called “domain-specific models,” which are also useful for representing and searching enterprise knowledge.

Chevala described a pharmaceutical use case in which, by training machine learning models on taxonomies when users “are searching for, say, a particular molecule, it’s recognized as an entity and is already in the trained model.” Top knowledge management solutions have domain models that encompass taxonomies for respective verticals. Others create these models interactively with organizations in a process in which experts ask the former “guided questions about their knowledge and how they use it and who needs access to what,” Greenberger explained. “They’ll work with them to figure out the structure of the categories.” Taxonomies also furnish three invaluable qualities for knowledge management:

♦ Uniformity: They ensure “the same concept has the same name,” Aasman said, and this is essential for sharing knowledge across departments.

♦ Synonyms: Taxonomies also provide an often exhaustive list of synonyms.

♦ Knowledge harmonization: Finally, they can harmonize knowledge in organizations. Aasman cited a healthcare example in which a taxonomy rectified differences in terms between medical codes with myriad ways to refer to the same concept. The result was improved clarity and faster processing times.

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