Document management is not often handled appropriately by organisations, if at all. Despite that, and despite the lack of structure in documents, organisations must face regulations that require owning a document collection with semantic content. The technique based on taxonomies and folksonomies can easily produce an adequate semantic classification for documents. It requires an adequate setup among the domain experts that apply it. The approach we propose uses Lean Kanban to coordinate the phases of definition, validation and implementation of taxonomies and folksonomies. It helps organisations to create a semantic classification of existing document resources, making them ready to be used in ways that were not possible before. At the same time, it helps to improve the quality of work of the organisation itself, adding speed to document search.

A Kanban-Based Methodology to Define Taxonomies and Folksonomies in KMS

PANI, FILIPPO EROS;
2015-01-01

Abstract

Document management is not often handled appropriately by organisations, if at all. Despite that, and despite the lack of structure in documents, organisations must face regulations that require owning a document collection with semantic content. The technique based on taxonomies and folksonomies can easily produce an adequate semantic classification for documents. It requires an adequate setup among the domain experts that apply it. The approach we propose uses Lean Kanban to coordinate the phases of definition, validation and implementation of taxonomies and folksonomies. It helps organisations to create a semantic classification of existing document resources, making them ready to be used in ways that were not possible before. At the same time, it helps to improve the quality of work of the organisation itself, adding speed to document search.
2015
978-3-662-45401-5
Lean Kanban, taxonomy, folksonomy, knowledge base, Knowledge Management System
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/78322
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