PMData: A Sports Logging Dataset

Vajira Thambawita, Steven Hicks, Hannah Borgli, Håkon Stensland, Debesh Jha, Martin Kristoffer Svensen, Svein Arne Pettersen, Dag Johansen, Hårvard Dagenborg Johansen, Susann Dahl Pettersen, Simon Nordvang, Sigurd Pedersen, Anders T. Gjerdum, Tor-Morten Grønli, Per Morten Fredriksen, Ragnhild Eg, Kjeld S. Hansen, Siri Fagernes, Christine Claudi, Christine ClaudiAndreas Biørn-Hansen, Duc Tien Nguyen, Tomas Kupka, Hugo Lewi Hammer, Ramesh C. Jain, Michael Riegler, Pål Halvorsen

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


In this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our dataset enables the development of novel data analysis and machine-learning applications where, for instance, additional sports data is used to predict and analyze everyday developments, like a person's weight and sleep patterns; and applications where traditional lifelog data is used in a sports context to predict athletes' performance. PMData combines input from Fitbit Versa 2 smartwatch wristbands, the PMSys sports logging smartphone application, and Google forms. Logging data has been collected from 16 persons for five months. Our initial experiments show that novel analyses are possible, but there is still room for improvement.
Original languageEnglish
Title of host publicationMMSys '20 : Proceedings of the 11th ACM Multimedia Systems Conference
EditorsLaura Toni, Ali C. Begen
Number of pages6
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Publication date27 May 2020
ISBN (Print)9781450368452
ISBN (Electronic)9781450368452
Publication statusPublished - 27 May 2020
Externally publishedYes
EventThe 11th ACM Multimedia Systems Online Conference - , WWW
Duration: 8 Jun 202011 Jun 2020
Conference number: 11


ConferenceThe 11th ACM Multimedia Systems Online Conference
Internet address


  • Multimedia dataset
  • Neural networks
  • Machine learning
  • Sports logging
  • Sensor data
  • Questionnaires
  • Food pictures

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