Observatorio de I+D+i UPM

Memorias de investigación
Artículos en revistas:
Guidelines for Linked Data generation and publication: An example in building energy consumption
Año:2015
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Linked Data is the key paradigm of the Semantic Web, a new generation of the World Wide Web that promises to bring meaning (semantics) to data. A large number of both public and private organizations have published their data following the Linked Data principles, or have done so with data from other organizations. To this extent, since the generation and publication of Linked Data are intensive engineering processes that require high attention in order to achieve high quality, and since experience has shown that existing general guidelines are not always sufficient to be applied to every domain, this paper presents a set of guidelines for generating and publishing Linked Data in the context of energy consumption in buildings (one aspect of Building Information Models). These guidelines offer a comprehensive description of the tasks to perform, including a list of steps, tools that help in achieving the task, various alternatives for performing the task, and best practices and recommendations. Furthermore, this paper presents a complete example on the generation and publication of Linked Data about energy consumption in buildings, following the presented guidelines, in which the energy consumption data of council sites (e.g., buildings and lights) belonging to the Leeds City Council jurisdiction have been generated and published as Linked Data.
Internacional
Si
JCR del ISI
Si
Título de la revista
Automation in Construction
ISSN
0926-5805
Factor de impacto JCR
1,822
Información de impacto
Datos JCR del año 2013
Volumen
57
DOI
Número de revista
Desde la página
178
Hasta la página
187
Mes
SEPTIEMBRE
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Filip Radulovic . (UPM)
  • Autor: Maria Poveda Villalon (UPM)
  • Autor: Daniel Vila Suero (UPM)
  • Autor: Victor Rodriguez Doncel (UPM)
  • Autor: Raul Garcia Castro (UPM)
  • Autor: Asuncion de Maria Gomez Perez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Inteligencia Artificial
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