MAT-Builder: a System to Build Semantically Enriched Trajectories

Pugliese, Chiara; Lettich, Francesco; Renso, Chiara; Pinelli, Fabio

doi:10.1109/mdm55031.2022.00058

Cited by 5 publications

(2 citation statements)

References 10 publications

(18 reference statements)

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“…In this work, we propose a methodology for the semantic enrichment processing of movement data that is agnostic to the aspects and external semantic data sources that might be considered. Preliminary and limited parts of our system have already been introduced in a demo paper [19] and a poster paper [20]. In the demo paper, we first introduced an interactive tool designed to showcase the potential of a system, MAT-BUILDER, that facilitates the generation of datasets of MATs.…”

Section: Related Workmentioning

confidence: 99%

Semantic Enrichment of Mobility Data: A Comprehensive Methodology and the MAT-BUILDER System

Lettich,

Pugliese,

Renso

et al. 2023

IEEE Access

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The widespread adoption of personal location devices, the Internet of Mobile Things, and Location Based Social Networks, enables the collection of vast amounts of movement data. This data often needs to be enriched with a variety of semantic dimensions, or aspects, that provide contextual and heterogeneous information about the surrounding environment, resulting in the creation of multiple aspect trajectories (MATs). Common examples of aspects can be points of interest, user photos, transportation means, weather conditions, social media posts, and many more. However, the literature does not currently provide a consensus on how to semantically enrich mobility data with aspects, particularly in dynamic scenarios where semantic information is extracted from numerous and heterogeneous external data sources. In this work, we aim to address this issue by presenting a comprehensive methodology to facilitate end users in instantiating their semantic enrichment processes of movement data. The methodology is agnostic to semantic aspects and external semantic data sources. The vision behind our methodology rests on three pillars: (1) three design principles which we argue are necessary for designing systems capable of instantiating arbitrary semantic enrichment processes; (2) the MAT-BUILDER system, which embodies these principles; (3) the use of an RDF knowledge graph-based representation to store MATs datasets, thereby enabling uniform querying and analysis of enriched movement data. We qualitatively evaluate the methodology in two complementary example scenarios, where we show both the potential in generating interesting and useful semantically enriched mobility datasets, and the expressive power in querying the resulting RDF trajectories with SPARQL.

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Section: Related Workmentioning

confidence: 99%

Semantic Enrichment of Mobility Data: A Comprehensive Methodology and the MAT-BUILDER System

Lettich,

Pugliese,

Renso

et al. 2023

IEEE Access

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“…In this work, we consider an extended version of the MAT-Builder system [5] within the context of a general methodology that aims to overcome the above limitations. More specifically, we extended MAT-Builder to adopt three design principles which we believe are necessary to provide systems capable of instantiating arbitrary semantic enrichment processes.…”

mentioning

confidence: 99%

A general methodology for building multiple aspect trajectories

Lettich

Pugliese

Renso

et al. 2023

Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing

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The massive use of personal location devices, the Internet of Mobile Things, and Location Based Social Networks, enables the collection of vast amounts of movement data. Such data can be enriched with several semantic dimensions (or aspects), i.e., contextual and heterogeneous information captured in the surrounding environment, leading to the creation of multiple aspect trajectories (MATs). In this work, we present how the MAT-Builder system can be used for the semantic enrichment processing of movement data while being agnostic to aspects and external semantic data sources. This is achieved by integrating MAT-Builder into a methodology which encompasses three design principles and a uniform representation formalism for enriched data based on the Resource Description Framework (RDF) format. An example scenario involving the generation and querying of a dataset of MATs gives a glimpse of the possibilities that our methodology can open up.

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Challenges of spatio-temporal trajectory datasets

Arslan,

Cruz

2024

Journal of Location Based Services

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MAT-Builder: a System to Build Semantically Enriched Trajectories

Cited by 5 publications

References 10 publications

Semantic Enrichment of Mobility Data: A Comprehensive Methodology and the MAT-BUILDER System

Semantic Enrichment of Mobility Data: A Comprehensive Methodology and the MAT-BUILDER System

A general methodology for building multiple aspect trajectories

Challenges of spatio-temporal trajectory datasets

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