The effort to create, record, and store information to disseminate cultural knowledge is an unending one. In parallel, new technologies are being developed to organize and catalog information to be retrieved so that knowledge gathered across the ages is not lost.
When it comes to organizing information as concepts related to other concepts and facts related to other facts, knowledge graphs are extraordinary. Employing well-designed subject ontologies information becomes semantic, allowing knowledge graphs to encode and organize domain-specific information in a meaningful way. However, what is remarkable is that knowledge graphs can infer and communicate new facts, producing new knowledge.
Today, among academics and practitioners, there is a growing awareness that current taxonomies need to move beyond not only keywords and natural language processing. Primarily because of the need for thorough disambiguation of terms, metaphors, and colloquialisms, and relate ideas to one another.
Increasingly, knowledge graphs, because of their dynamic, non-linear nature, are also being used to manage all data types. Knowledge graphs can expand to include new information, and billions of data points can be connected and interconnected depending on what types of information are being queried and recalled.
Essentially, using knowledge graphs to organize and catalog information is like storing information in 3D. For instance, today's news can now be surfaced alongside a research article written 15 years ago because the concepts within the two are identified in the knowledge graph as relevant. By providing a framework, knowledge graphs can help publishers and academics view their content in the context of the current news, other titles in their collection, and the broader research ecosystem.
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