Despite recent progresses in methods for processing data about the movement of objects in the geographic space, some fundamental issues remain unresolved. One of them is how to describe movement segments (e.g., semantic trajec- tories, episodes like stops and moves) and diverse movement patterns (e.g., moving clusters, hotel-restaurant-shop-hotel), with formal semantic descriptions. Another issue is how to arrange descriptive data and measures in a Movement Data Warehouse (MDW) for powerful information analyses and reasonable performance. This paper introduces general def- initions for movement segments, movement patterns, their categories and hierarchies. The proposed constructs are se- mantically enriched with references to concepts (categories) and/or instances of these concepts (objects) arranged in dis- tinct hierarchies. Based on these constructs, we propose a semantic multidimensional model for MDW. A case study illustrates the expressiveness of the proposal for analyzing movement data collected via social media and semantically enriched with Linked Open Data (LOD).

Despite recent progresses in methods for processing data about the movement of objects in the geographic space, some fundamental issues remain unresolved. One of them is how to describe movement segments (e.g., semantic trajectories, episodes like stops and moves) and diverse movement patterns (e.g., moving clusters, hotel-restaurant-shop-hotel), with formal semantic descriptions. Another issue is how to arrange descriptive data and measures in a Movement Data Warehouse (MDW) for powerful information analyses and reasonable performance. This paper introduces general definitions for movement segments, movement patterns, their categories and hierarchies. The proposed constructs are semantically enriched with references to concepts (categories) and/or instances of these concepts (objects) arranged in distinct hierarchies. Based on these constructs, we propose a semantic multidimensional model for MDW. A case study illustrates the expressiveness of the proposal for analyzing movement data collected via social media and semantically enriched with Linked Open Data (LOD).

A Semantic Model for Movement Data Warehouses

RAFFAETA', Alessandra;RONCATO, Alessandro;
2014-01-01

Abstract

Despite recent progresses in methods for processing data about the movement of objects in the geographic space, some fundamental issues remain unresolved. One of them is how to describe movement segments (e.g., semantic trajectories, episodes like stops and moves) and diverse movement patterns (e.g., moving clusters, hotel-restaurant-shop-hotel), with formal semantic descriptions. Another issue is how to arrange descriptive data and measures in a Movement Data Warehouse (MDW) for powerful information analyses and reasonable performance. This paper introduces general definitions for movement segments, movement patterns, their categories and hierarchies. The proposed constructs are semantically enriched with references to concepts (categories) and/or instances of these concepts (objects) arranged in distinct hierarchies. Based on these constructs, we propose a semantic multidimensional model for MDW. A case study illustrates the expressiveness of the proposal for analyzing movement data collected via social media and semantically enriched with Linked Open Data (LOD).
2014
Proceedings of the 17th International Workshop on Data Warehousing and OLAP - DOLAP '14
File in questo prodotto:
File Dimensione Formato  
MovDW_DOLAP2014_FINAL.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Licenza non definita
Dimensione 617.68 kB
Formato Adobe PDF
617.68 kB Adobe PDF   Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/43901
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 23
  • ???jsp.display-item.citation.isi??? ND
social impact