annotations of the "Forrest Gump" movie stimulus

Christian Olaf Häusler 29dcce2b94 Merge pull request #11 from chrhaeusler/master 2 months ago
.datalad ba3e64506c [DATALAD] new dataset 3 years ago
code d5803afa10 add explanation of parameters 2 months ago
old 27a589535a Move all previous annotations aside for BIDS-style replacements 3 years ago
researchcut ab0e13c18e add (unsegmented) annotation of music 2 months ago
segments 6b30d084bb [DATALAD RUNCMD] segment annotation of music (input: audio-track) respecting timings of the movie 2 months ago
src 3cffef9c16 [DATALAD] Recorded changes 2 months ago
.gitattributes 6ad80d5b79 Put text files into git 3 years ago
.gitmodules 3cffef9c16 [DATALAD] Recorded changes 2 months ago
LICENSE f31675e212 Initial commit 5 years ago 2e139ec38a DOC: Add short DataLad intro as proposed in the handbook 1 year ago


Stimulus annotations for the movie Forrest Gump

This repository collects stimulus annotations for the research cut of the "Forrest Gump" movie used in the project. Annotations are collected from various contributors and publications.

Annotations are typically provided as plain text tables, using a tab-separated-value markup with a header row. Table usually contain a onset and a duration column to indicate the timing of an event. All other columns contain variables that describe properties of an event.

Repository content

  • code/

All code necessary to import and convert annotations from the formats they were originally provided in.

  • researchcut/

Annotation plain text tables with timing matching the entire "research cut" as one continuous piece.

  • segments/

Annotation plain text tables with timing matching individual movie segments used in the project.

  • src/

Datalad subdatasets referencing repositories with available annotations.

  • old/ (deprecated)

Previously provided, less uniformly structured, annotation. All of these will eventually be replaced by the format described above. This directory will be removed in the future

DataLad datasets and how to use them

This repository is a DataLad dataset dataset (id: 45b9ab26-07fc-11e8-8c71-f0d5bf7b55). It provides fine-grained data access down to the level of individual files, and allows for tracking future updates. In order to use this repository for data retrieval, DataLad is required. It is a free and open source command line tool, available for all major operating systems, and builds up on Git and git-annex to allow sharing, synchronizing, and version controlling collections of large files. You can find information on how to install DataLad at

Get the dataset

A DataLad dataset can be cloned by running

datalad clone <url>

Once a dataset is cloned, it is a light-weight directory on your local machine. At this point, it contains only small metadata and information on the identity of the files in the dataset, but not actual content of the (sometimes large) data files.

Retrieve dataset content

After cloning a dataset, you can retrieve file contents by running

datalad get <path/to/directory/or/file>`

This command will trigger a download of the files, directories, or subdatasets you have specified.

DataLad datasets can contain other datasets, so called subdatasets. If you clone the top-level dataset, subdatasets do not yet contain metadata and information on the identity of files, but appear to be empty directories. In order to retrieve file availability metadata in subdatasets, run

datalad get -n <path/to/subdataset>

Afterwards, you can browse the retrieved metadata to find out about subdataset contents, and retrieve individual files with datalad get. If you use datalad get <path/to/subdataset>, all contents of the subdataset will be downloaded at once.

Stay up-to-date

DataLad datasets can be updated. The command datalad update will fetch updates and store them on a different branch (by default remotes/origin/master). Running

datalad update --merge

will pull available updates and integrate them in one go.

More information

More information on DataLad and how to use it can be found in the DataLad Handbook at The chapter "DataLad datasets" can help you to familiarize yourself with the concept of a dataset.