Human Time Data project

About the project

The Human Time Data project is initiated based on UIO's council for research infrastructure recommendation for Hub/Node-organisation of IT in research. Through building a Hub, relevant nodes (ie research communities) may connect benefitting from centralized competence, resources, tools and services.


Goal of HumanTimeData is to improve UIO's access to services and tools for researching human time series data. This includes quantitative data collected from human movement and physiology, such as from accelerometers, motion tracking systems, eye tracking cameras, physiological sensors (GSR, EMG, ECG) and brain metering (EEG, MR). Although such data comes from different types of sensor systems and covers different parts of human signals, the data has several similarities:

  •  The data is time series data with relatively high time and data resolution
  • The data takes a lot of space and is processed in several steps
  •  The data requires, in many cases, to be moved to and analyzed on mainframes
  • The data is often caught up with proprietary special systems that employ special formats that are more or less poorly standardized
  • The data often requires integration with other data sets (Sensor data, audio, video, and qualitative data) in order to be analyzed
  • The data is demanding to store due to space requirements, data complexity, privacy and copyright.

Currently there are numbers of communities that relate to this type of data at UIO, but there is relatively little joint competence available. The environments that use such data also have varying technology skills which often results in many custom-made ad-hoc solutions. The project has the following objectives:

  • Create a network of researchers and research support staff working with human time series data
  • Map and facilitate existing tools and services to better manage this type of data in existing infrastructures and servers
  • Develop new tools and services where there are currently "gaps" in the services offered
  • Develop best-practice data-handling routines including highest possible availability and linking to other relevant projects such as the eVIR, Open Science Cloud, and more


The project is based at the Department of Psychology in the RITMO offices cooperating with USIT as well as all potential nodes including research communitites within fields like:

  • fMRI and MRI
  • EEG/Ecog
  • MoCap
  • Eye tracking


Council for einfrastructure ("IT in research") 2017-2020

Tags: EEG, fMRI, MoCap, Ecog, Eyetracking, IT, research, einfrastructure, Hub/Node
Published Feb. 19, 2019 5:05 PM - Last modified Oct. 25, 2022 8:33 AM