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...

Full description

Autores:
Jiménez Ramírez, Claudia
Burke, Maria Edith
Rodríguez Flores, Ivonne
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
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/
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
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary: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.