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Enhancing Data Quality and Collaboration in Participatory Climate Data Crowdsensing
Ackermann, Leonie; Akcabay, Samet; Benabbas, Aboubakr; u. a. (2024): Enhancing Data Quality and Collaboration in Participatory Climate Data Crowdsensing, in: Bamberg: Otto-Friedrich-Universität, S. 1–6.
Faculty/Chair:
Publisher Information:
Year of publication:
2024
Pages:
Source/Other editions:
2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) - New York : IEEE, 2024 - DOI: 10.1109/percomworkshops59983.2024.10502897.
Year of first publication:
2024
Language:
English
Licence:
Abstract:
Based on a citizen-initiated climate data crowdsensing campaign, we showcase mechanisms for ensuring data quality and discuss requirements for collaborative curation of the collected information. Specifically, we delve into the challenges and opportunities citizen-led data collection with the Netatmo Smart Home Weather Station. Our study addresses the engagement of citizens in the scientific process, investigates innovative detection mechanisms for enhancing data quality in crowdsensed climate data, and introduces robust metrics for assessing data quality. Additionally, we propose a design for an application that gives citizens the opportunity to actively participate in data validation and curation, thus increasing the trustworthiness and usefulness of the collected data. These solutions actively contribute to the ongoing design and evolution of climate data crowdsensing, harnessing the potential of the urban knowledge society. In this way, they actively support the participation of the city community in overcoming social challenges associated with climate change adaptation.
GND Keywords: ; ; ; ;
Datensammlung
Integrität <Informatik>
Klima
Datenqualität
Bürgerbeteiligung
Keywords: ; ; ; ; ; ;
Crowdsensing
Data integrity
Urban areas
Data collection
Data quality
Citizen participation
Climate data
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Conferenceobject
Activation date:
January 16, 2025
Project(s):
Permalink
https://fis.uni-bamberg.de/handle/uniba/97462