Data collection is an essential part of empirical research and can be done in many ways, by different methods and with the use of a variety of (digital) tools. The annotation, description or documentation of the collection process is of vast importance to at all times understand how a data source was created (i.e. describing a lab experiment), but also for the conversion of data to a format that allows analysis (i.e. the transcription of audio to text).
In this menu we have collected information on tooling available to UG researchers to help collect & annotate data, listing the technical specifications, functions and restrictions.

Data Management rules of thumb:

• Never KEEP your research data in collection systems, environments or devices. These are not intended or secure enough for (long term) storage.
  • After concluding the collection phase of (personal) data. The data should always be copied to a trusted, secure and accessible location from where you can continue your analysis.
  • After securing your collected data. Remove it from the primary source (collection system, environment or device).