Knowledge Organization
Libraries would be of little use if they were unable to organize and catalog books. The same is true for business data. Business information is of very little value to an organization unless it is organized into a logical framework that enables its retrieval or analysis. More than a structure to organize content, it is also capable of representing domain-specific tacit knowledge in such a way that it becomes itself a source of knowledge and resource for further AI applications alongside the content it categorizes.
Creating a taxonomy based on a standard like SKOS is a efficient way to make accumulated knowledge more accessible and reusable. It helps companies find and make sense of the right information when it is needed in the shortest time possible.
Business challenges that taxonomy management addresses
In today’s fast paced environment, organizations who rely on convoluted spreadsheets and document sharing systems only will not be able to compete with companies who use intelligent methods of organizing their data.
Ineffective tooling
Spreadsheet software like Excel is popularly used for taxonomy management along with some freely available open source tools. Regularly, users quickly find out that these approaches do not scale for various reasons and are only suitable for small taxonomies.
Unclassified content
The lack of a clear classification scheme means that elaborately produced but poorly indexed content disappears undiscoverable.
Inconsistent vocabularies
The naming of things in companies often varies according to the department, the use or the jargon. Often there are two company vocabularies that (have to) come together through a merger. That is why modern knowledge management cannot do without synonym management, mapping and linking.
Disconnected delivery
Knowledge management can no longer be thought of as manual librarianship. Metadata management can only exist if it is fully connected to operational processes. Therefore, machine readability and standardization are now a must and the basis for all downsteam realized value.
Gartner predicts that by 2025, graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision making across the organization.
Graphwise’s taxonomy management opens up new possibilities
Automated taxonomy creation
We introduced the Taxonomy Advisor, our large lanaguage model (LLM)-based suggestion tool that streamlines the process of creating taxonomies. The Taxonomy Advisor promises the following:
Less time researching:
The user still has the ability to refine or reject the Taxonomy Advisor’s suggestions, but spends less time having to outline new terms from scratch
Adding concepts:
Users can select and edit from suggested narrower and related concepts
Generated concept definitions: Users can add/edit auto-generated definitions that are suggested by the Advisor
Streamlined editing: Users can add suggestions in bulk operations or singularly, depending on their preference
Controlled vocabularies
Many organizations waste time and effort searching for data due to mislabeling or different terminology across departments. With Graphwise’s collaborative interface, departments can bundle synonymous terms under one concept and relate it to other concepts to reduce confusion while searching for information. This is especially pertinent to international companies that use different foreign languages in different offices – PoolParty’s multilingual capabilities allow you to create a cross-border language for your company.
Agile metadata
Organizations need to be able to pivot and shift based on growing trends within the market. Agile taxonomy management means that you can reuse and add data for other types of data models. The flexibility to continuously revise and update taxonomies by key stakeholders ensures that organizations stay relevant and up-to-date with consumer and industry demands alike.
Intelligent content
Taxonomies help connect the dots to understand how your information is structured, and build a strong foundation for search platforms that can retrieve results based on these connected dots. Having a structured taxonomy in combination with text mining capabilities, helps machines understand connections and hierarchies between all of your data – which can then suggest further information relevant to the user’s search.
Unlocked Semantic AI
Taxonomy Management is the first step on the way to structured knowledge and data management based on a semantic layer that enables intelligent search platforms, recommendation programs, virtual assistants or even enterprise-wide content and knowledge hubs. The enterprise knowledge stored in the taxonomy can also serve as the foundation for advanced machine learning solutions such as Generative AI, Composite AI, Causal AI, and Explainable AI to shorten learning and focus domain truth.
Useful Resources
Guide
Check out the ultimate guide to taxonomies in business.
Webinar
Taxonomies, Knowledge Graphs, and AI
Taxonomies, knowledge graphs and AI allow for capturing the context and meaning to provide accurate results in search and recommendations.
Blog
Graphwise Customer Success Stories – Taxonomies, Ontologies & Knowledge Graphs in Practice
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