Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics

Anita Graser; Melitta Dragaschnig

doi:10.1109/MDM61037.2024.00048

Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics

Anita Graser (Author and Speaker), Melitta Dragaschnig

Data Science & Artifical Intelligence

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

Abstract

This demo paper presents the conceptual foundations and the first steps towards implementation of a novel no-code solution for movement data analytics based on the open-source Python library MovingPandas and the open-source geo-graphic information system QGIS. The resulting Trajectools plugin is available open-source at https://github.com/movingpandas/qgis-processing-trajectory.

Original language	English
Title of host publication	Proceedings of Mobile Data Management (MDM) 2024
Pages	235 - 238
ISBN (Electronic)	979-8-3503-7455-1
DOIs	https://doi.org/10.1109/MDM61037.2024.00048
Publication status	Published - 2024
Event	25th IEEE International Conference on Mobile Data Management - Brussels, Belgium Duration: 24 Jun 2024 → 27 Jun 2024 https://mdm2024.github.io/

Conference

Conference	25th IEEE International Conference on Mobile Data Management
Abbreviated title	MDM 2024
Country/Territory	Belgium
City	Brussels
Period	24/06/24 → 27/06/24
Internet address	https://mdm2024.github.io/

Research Field

Multimodal Analytics

Access to Document

10.1109/MDM61037.2024.00048

Cite this

@inproceedings{b917ce2e43e249e8a10152c602c33eae,

title = "Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics",

abstract = "This demo paper presents the conceptual foundations and the first steps towards implementation of a novel no-code solution for movement data analytics based on the open-source Python library MovingPandas and the open-source geo-graphic information system QGIS. The resulting Trajectools plugin is available open-source at https://github.com/movingpandas/qgis-processing-trajectory.",

author = "Anita Graser and Melitta Dragaschnig",

year = "2024",

doi = "10.1109/MDM61037.2024.00048",

language = "English",

isbn = "979-8-3503-7456-8",

pages = "235 -- 238",

booktitle = "Proceedings of Mobile Data Management (MDM) 2024",

note = "25th IEEE International Conference on Mobile Data Management, MDM 2024 ; Conference date: 24-06-2024 Through 27-06-2024",

url = "https://mdm2024.github.io/",

}

TY - GEN

T1 - Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics

AU - Dragaschnig, Melitta

A2 - Graser, Anita

PY - 2024

Y1 - 2024

N2 - This demo paper presents the conceptual foundations and the first steps towards implementation of a novel no-code solution for movement data analytics based on the open-source Python library MovingPandas and the open-source geo-graphic information system QGIS. The resulting Trajectools plugin is available open-source at https://github.com/movingpandas/qgis-processing-trajectory.

AB - This demo paper presents the conceptual foundations and the first steps towards implementation of a novel no-code solution for movement data analytics based on the open-source Python library MovingPandas and the open-source geo-graphic information system QGIS. The resulting Trajectools plugin is available open-source at https://github.com/movingpandas/qgis-processing-trajectory.

U2 - 10.1109/MDM61037.2024.00048

DO - 10.1109/MDM61037.2024.00048

M3 - Conference Proceedings with Oral Presentation

SN - 979-8-3503-7456-8

SP - 235

EP - 238

BT - Proceedings of Mobile Data Management (MDM) 2024

T2 - 25th IEEE International Conference on Mobile Data Management

Y2 - 24 June 2024 through 27 June 2024

ER -

Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics

Abstract

Conference

Research Field

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Cite this