Hi, I’m Marc and I’d like to present
how the DGS Corpus implements ethical open data practices
such as the CARE and FAIR principles.
My co-author for this presentation is Thomas Hanke,
but the work I describe has been contributed to by many people over the years,
so credit should go to the entire DGS-Korpus project team.
A quick note for those who are not familiar with signed languages,
DGS stands for “Deutsche Gebärdensprache”,
meaning German Sign Language,
which is a signed language that is primarily used in Germany and Luxembourg.
As is the case for basically all signed languages,
DGS is severely under-resourced
and very little data for corpus-driven research exists.
To address this lack of data,
the DGS Corpus was created as part of a 15 year project
that was started in 2009.
It is an annotated reference corpus of German Sign Language,
consisting of 560 hours of conversations.
It includes both sign by sign annotations
and translations into German and English.
50 hours of that reference corpus are also publicly available
as the Public DGS Corpus.
While small when compared to many corpora of well-resourced spoken languages,
the DGS Corpus and its public subset
are both amongst the largest sign language corpora of their kind.
One reason for this is that signed languages
have no commonly used written forms
and phonetic transcription is very complex.
Annotating signed utterances properly is a very time-consuming process.
One hour of recording needs about
800 to 1000 hours of work before publication
setting hard constraints for how much of the reference corpus
could be included in the public corpus.
Publishing 50 hours of data
allows us to present a cross-section of the overall corpus,
giving a good impression of the different kinds of contents that it covers.
During the creation and publication of the corpus,
the team followed established best practices
for ethical research relating to deaf populations.
These practices are in line with the recently introduced
CARE principles of open data ethics.
To see how exactly the DGS Corpus implements CARE,
let’s start at the beginning.
The primary stakeholders in the DGS language community
are members of the deaf community in Germany.
Following the principle “nothing about us without us”,
the corpus project has always included deaf team members.
In addition, a focus group of deaf users was formed
to guide project decisions
and assist us in connecting with the deaf community
as well as keeping it informed about the project.
To ensure collective benefit,
the corpus was designed so that it would be
both a source for linguistic research and a record of deaf culture,
covering general life experience,
deaf-specific experiences,
perception of historical events,
but also things like telling jokes.
The goal was to create a resource
that would be entertaining, informative,
and that would support the identity of the community.
The project recorded 330 participants from all across Germany
whose primary language of daily life was DGS.
Following the authority to control principle,
informed consent was requested from all participants.
This involved providing information in both DGS and German
regarding the goals of the project,
uses of the data,
and what the rights of the participants are.
These rights include restricting for what purposes the data may be shared
and also reviewing the recordings to give or withhold their approval
for either entire recordings or individual moments.
Let’s fast forward a few years.
After a lot of work annotating and translating recordings,
the first full release of the public corpus was published in 2018.
We also release updated versions on a regular basis
to add more data, make corrections,
and to react to feedback.
As I mentioned before,
the DGS Corpus is both a linguistic resource
and a record of deaf culture.
So to maximise its collective benefit
we released its data on two separate portals.
The first one is My DGS,
a community portal for deaf people
and others interested in DGS and deaf culture.
It provides all recordings with optional German subtitles
and its design focusses on making it easy
to find and watch interesting content.
Here is a little example.
The second portal is My DGS – annotated,
a research portal that provides the same recordings
with full sign annotations and translations in German and English.
All data is available to download,
but can also be viewed in an online transcript viewer.
Here is the video from before
Here is the video from before as seen through the research portal.
The research portal also provides a type index
of all unique signs occurring in the corpus.
For each sign you receive an overview of its corpus occurrences,
grouped by sign sense,
and where possible a studio recording and phonetic transcription of its citation form
as well as links to other lexical resources.
The publication of the portals is also
where FAIR joins CARE in our considerations.
To make them reliably findable,
each portal is treated as a separate but related dataset
and given separate DOIs.
For a simpler dataset, a single DOI would be sufficient,
but for a complex dataset like the Public DGS Corpus
we find it advisable to also have identifiers for individual parts.
So we create DOIs for each individual transcript
as well as for each type in the type index.
That way researchers can clearly specify
which transcripts or signs they refer to in their research.
On top of that, whenever we release an updated version of the corpus,
every component that has changed also receives a new DOI,
so it is always clear which version of the corpus is being referred to.
All of these DOIs are then given qualified references
to clarify how they are related to each other.
Each DOI also comes with a set of machine-readable metadata
covering general dataset information
like its name, authors, release date,
and all those qualified references I just mentioned.
For information that is more specific to language data
we also provide a CMDI file for each transcript.
In there we specify metadata about the participants,
elicitation tasks,
the languages of the primary and secondary data,
and so on.
Apart from this metadata, the corpus has a wealth of documentation.
In addition to peer-reviewed articles,
there are over thirty project notes documenting various aspects of the project.
This includes a Data Statement,
a document type specifically designed to help researchers
understand the background of a dataset
and anticipate its inherent biases.
Of course, all project notes have their own version-controlled DOIs.
Another challenge for the project
was the long term archival of its original recordings.
At over one thousand hours of raw recording time,
captured from several perspectives
by 7 different high definition or stereoscopic cameras,
the original data collection resulted in 730,000 gigabytes of video files.
An additional 250,000 gigabytes of data
have so far been produced through secondary data collections,
studio recordings made for the presentation of the corpus,
and recordings made for a corpus-based dictionary
that is also part of the project.
That leaves us with a whole petabyte of data
that needs to be securely backed up and archived,
ideally following FAIR principles.
Luckily, the Research Data Repository of Hamburg University
provides a decentralised redundant server structure
capable of handling large data collections like ours.
The archive is run using Invenio RDM,
the same repository software as Zenodo,
which enables persistent storage, fast access,
associated metadata, and clear versioning.
While the original recordings themselves are not publicly accessible,
their identity and metadata are,
allowing us to also link each of them explicitly
with the transcripts of the public corpus that originate from them.
And that brings me to the end of my presentation.
Of course, I only skimmed the surface
and even skipped a few aspects,
such as usage licences and anonymisation,
so if you have any questions now or later, I’d be happy to answer them.
And of course please go and check out the corpus itself
and the many stories it contains.
Thank you!