Statistical metadata in knowledge discovery
Metadata represents the semantic schema of the data collected over the years by an organization in order to apply the business intelligence approach. However, the metadata normally collected are not enough to facilitate knowledge discovery processes because they are conceived, primarily, for the in...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Colombia |
| Institución: | Universidad Nacional de Colombia |
| Repositorio: | Repositorio UN |
| Idioma: | español |
| OAI Identifier: | oai:repositorio.unal.edu.co:unal/60358 |
| Acceso en línea: | https://repositorio.unal.edu.co/handle/unal/60358 http://bdigital.unal.edu.co/58690/ |
| Access Level: | acceso abierto |
| Palabra clave: | 62 Ingeniería y operaciones afines / Engineering statistical metadata knowledge discovery knowledge management data analytics metadatos estadísticos descubrimiento de conocimiento gestión de conocimiento analítica de datos |
| Sumario: | Metadata represents the semantic schema of the data collected over the years by an organization in order to apply the business intelligence approach. However, the metadata normally collected are not enough to facilitate knowledge discovery processes because they are conceived, primarily, for the interoperability between information systems. Research undertaken in this study confirmed the need to enrich data warehousing systems with structured meaningful metadata in order to increase the productivity and efficacy of any investigation, including data management and future business analytics. This need led us to adopt and extend the concept of “statistical metadata”. Thus, our proposed conceptual model of statistical metadata not only considers recognized standards, but also represents other additional properties. This means that our conceptual model allows increased levels of detail about the data and quality of the semantic contents. |
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