Most organizations today face challenges as they accumulate volumes of data everywhere – on the premises and in the cloud. How do they begin to identify and locate what’s valuable, sensitive or relevant when the time comes, and in an expedited manner?
A custom taxonomy could be the answer. Taxonomies provide consistency in terms and categories to enable findability in content. This is true regardless of the subject.
Developing a classification system organized into conceptually similar categories can help users gain a better understanding of the taxonomy subject area. It is important to remember the value of a solid taxonomy and its role in the search and more importantly, findability process. How the content is classified impacts the findability of your data.
Content without access is relatively worthless. Enterprise search is how an organization helps people seek the information they need, in any format, from anywhere inside their company. Technology is almost always a good investment for organizations, especially if they are looking to justify information technology modernization.
Making the content findable is important to knowledge management. The goal of taxonomy is to make navigation easier and content findable.
Metadata makes digital content findable. However, findability works only when a proper taxonomy is in place. Proper indexing against a strong standards-based taxonomy increases the findability of data. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies.
Data governance policies and procedures are designed to create consistency and quality in the data you create, manage and store so at the end of the cycle, findability is simple and effective. All this requires strategy, and a good taxonomy to index the data.
Data Harmony is a fully customizable suite of software products designed to maximize precise, efficient information management and retrieval. Our suite includes tools for taxonomy and thesaurus construction, machine aided indexing, database management, information retrieval and explainable AI.
“Explainable AI” is used to describe an AI model, its expected impact and potential biases. Why is this important? Because the results can have an impact on data security or patient safety.
Melody K. Smith
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
