short-paper

Understanding Movement in Context with Heterogeneous Data

Authors:

Wouter Meulemans,

Marcel Roeloffzen,

Kevin VerbeekAuthors Info & Claims

MOVE'19: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data

Article No.: 1, Pages 1 - 4

https://doi.org/10.1145/3356392.3365222

Published: 05 November 2019 Publication History

Abstract

Movement data, as captured by myriad sensors, has been growing exponentially. Hence, multidisciplinary approaches for analyzing movement has become feasible. Though, movement pertains to a large variety of domains and applications, the focus of this position paper is understanding human movement (mobility) in various forms. We position maps as heterogeneous, multidimensional and digital representation of reality and advocate their role in contextualizing movement. We overview the main problems for analyzing human mobility with special attention to movement in context, leveraging heterogeneous data. We review the state-of-the-art in solving these problems and describe remaining open problems and challenges for future work. Finally, we offer a view of existing as well as future mapping and location services that could enable these.

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Cited By

van Kreveld MSpeckmann BStroila MTrajcevski G(2020)The 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data (MOVE++ 2019)SIGSPATIAL Special10.1145/3383653.338365611:3(9-11)Online publication date: 13-Feb-2020
https://dl.acm.org/doi/10.1145/3383653.3383656

Index Terms

Understanding Movement in Context with Heterogeneous Data
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems

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Published In

cover image ACM Conferences

MOVE'19: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data

November 2019

25 pages

ISBN:9781450369510

DOI:10.1145/3356392

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2019

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Short-paper
Research
Refereed limited

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Nederlandse Organisatie voor Wetenschappelijk Onderzoek
HERE Technologies

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SIGSPATIAL '19

Sponsor:

SIGSPATIAL

SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5, 2019

IL, Chicago, USA

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MOVE'19 Paper Acceptance Rate 5 of 8 submissions, 63%;

Overall Acceptance Rate 5 of 8 submissions, 63%

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Cited By

van Kreveld MSpeckmann BStroila MTrajcevski G(2020)The 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data (MOVE++ 2019)SIGSPATIAL Special10.1145/3383653.338365611:3(9-11)Online publication date: 13-Feb-2020
https://dl.acm.org/doi/10.1145/3383653.3383656

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