HED (Hierarchical Event Descriptors) is a framework for annotating event data. This site hosts HED documentation and some examples of annotation.
A simple workflow for annotation is to create a spreadsheet containing events and their corresponding HED annotations. Researchers can then use an online validator to validate their annotations without installing other tools. The CTagger tool provides a graphical user interface for doing annotation. HED validators are also available in Python and JavaScript.
Event annotation typically two forms: code-specific and event-specific. In code-specific annotation, researchers identify a small number of event classes or categories and annotate the categories with HED tags. Downstream tools then map the HED tags to event instances during analysis. In event-specific annotation, researchers tag individual event instances. One can combine these approaches, using code-specific annotation to describe common properties, for example that events with this code represent visual target events. An additional event-specific layer might be provided to label the location of the target in each individual event. Researchers can choose the layers of interest during downstream analysis. HED also supports data feature annotations.
HED annotation is integrated into EEGLAB, a MATLAB toolbox for processing EEG brain imaging data. There are two ways to install the HEDTools EEGLAB plug-in:
Check out the Quick guide to start tagging your EEG data.
Follow the instructions on the HED validator page to prepare your event-HED tag spreadsheet and to validate it with the HED validator.
Once you are familiar HED basics, check out the HED Tagging Strategy Guide for some practical annotation strategies.
hedtags.org is the home page for HED tag users.
hed-standard is the HED community organization repository for HED development.