The notion of multiple aspect trajectory (MAT) has been recently introduced in the literature to represent movement data that is heavily semantically enriched with dimensions (aspects) representing various types of semantic information (e.g., stops, moves, weather, traffic, events, and points of interest). Aspects may be large in number, heterogeneous, or structurally complex. Although there is a growing volume of literature addressing the modelling and analysis of multiple aspect tra-jectories, the community suffers from a general lack of publicly available datasets. This is due to privacy concerns that make it difficult to publish such type of data, and to the lack of tools that are capable of linking raw spatio-temporal data to different types of semantic contextual data. In this work we aim to address this last issue by presenting MAT-BUILDER, a system that not only supports users during the whole semantic enrichment process, but also allows the use of a variety of external data sources. Furthermore, MAT-BUILDER has been designed with modularity and extensibility in mind, thus enabling practitioners to easily add new functionalities to the system and set up their own semantic enrichment process. The demonstration scenario, which will be showcased during the demo session, highlights how MAT-BUILDER's main features allow users to easily generate multiple aspect trajectories, hence benefiting the mobility data analysis community.
MAT-Builder: a system to build semantically enriched trajectories
Pugliese C;Lettich F;Renso C;
2022
Abstract
The notion of multiple aspect trajectory (MAT) has been recently introduced in the literature to represent movement data that is heavily semantically enriched with dimensions (aspects) representing various types of semantic information (e.g., stops, moves, weather, traffic, events, and points of interest). Aspects may be large in number, heterogeneous, or structurally complex. Although there is a growing volume of literature addressing the modelling and analysis of multiple aspect tra-jectories, the community suffers from a general lack of publicly available datasets. This is due to privacy concerns that make it difficult to publish such type of data, and to the lack of tools that are capable of linking raw spatio-temporal data to different types of semantic contextual data. In this work we aim to address this last issue by presenting MAT-BUILDER, a system that not only supports users during the whole semantic enrichment process, but also allows the use of a variety of external data sources. Furthermore, MAT-BUILDER has been designed with modularity and extensibility in mind, thus enabling practitioners to easily add new functionalities to the system and set up their own semantic enrichment process. The demonstration scenario, which will be showcased during the demo session, highlights how MAT-BUILDER's main features allow users to easily generate multiple aspect trajectories, hence benefiting the mobility data analysis community.File | Dimensione | Formato | |
---|---|---|---|
prod_471846-doc_191825.pdf
accesso aperto
Descrizione: preprint - MAT-Builder: a system to build semantically enriched trajectories
Tipologia:
Versione Editoriale (PDF)
Dimensione
658.15 kB
Formato
Adobe PDF
|
658.15 kB | Adobe PDF | Visualizza/Apri |
prod_471846-doc_191870.pdf
non disponibili
Descrizione: MAT-Builder: a system to build semantically enriched trajectories
Tipologia:
Versione Editoriale (PDF)
Dimensione
743.58 kB
Formato
Adobe PDF
|
743.58 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.