MHC '18 - International workshop on mobile human contributions: Opportunities and challenges

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  • Niels Van Berkel
  • Simo Hosio
  • Jorge Goncalves
  • Wac, Katarzyna
  • Vassilis Kostakos
  • Anna Cox

Ubicomp/HCI researchers are increasingly using smartphones to collect human-labelled data 'in the wild'. While this allows for the collection of a wide range of interesting data in authentic settings and surroundings, humans are notoriously inconsistent in the quality of their contributions. Improving the quality of data collected with mobile devices is a largely unexplored, but highly relevant field. The primary objective of this workshop is to share insights, ideas, and discoveries on the quality of mobile human contributions. The work presented in the International Workshop on Mobile Human Contributions (MHC '18) explores methods, tools, and novel approaches towards increasing the reliability of human data submissions with mobile devices.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
Number of pages4
PublisherAssociation for Computing Machinery, Inc.
Publication date2018
Pages590-593
ISBN (Electronic)9781450359665
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore
Duration: 8 Oct 201812 Oct 2018

Conference

Conference2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018
LandSingapore
BySingapore
Periode08/10/201812/10/2018
SponsorACM SIGCHI, ACM SIGMOBILE

    Research areas

  • Citizen science, Crowdsourcing, Data quality, Experience sampling, Human sensing, In situ, Mobile devices

ID: 217340102