CAVA users are expected to acknowledge the repository and cite CAVA data sets in any research publications and other outputs drawing on CAVA data.

Acknowledgement

An acknowledgement is a general statement giving credit to the source and distributor and includes copyright information. It can be given at the start of, or within, the text, or at the end of an article before the bibliographic references/citations. Recommended wording for acknowledgement to the BSL Corpus Project is below. In your acknowledgement, please include:

• The project title and ID
• The research funder
• The name of the CAVA repository and its web address (/cava )
• A short copyright statement

Recommended wording for acknowledgement which includes all elements above:

“The data in this article were collected for the British Sign Language Corpus Project (BSLCP) at University College London, funded by the Economic and Social Research Council UK (RES-620-28-6001), and supplied by the CAVA repository. The data are copyright.”

Citation: video data only

A citation is more formal than an acknowledgement. It follows a standard format and should include enough information so that the exact version of the data being cited can be located. The recommended citation for the digital video data corpus deposited in 2011 is:

Schembri, Adam, Jordan Fenlon, Ramas Rentelis, & Kearsy Cormier. (2011). British Sign Language Corpus Project: A corpus of digital video data of British Sign Language 2008-2011 (First Edition). London: University College London. (https://www.bslcorpusproject.org)

Citation: video data + annotations

The recommended citation for the BSL Corpus annotations deposited in 2014 is:

Schembri, Adam, Jordan Fenlon, Ramas Rentelis, & Kearsy Cormier. (2014). British Sign Language Corpus Project: A corpus of digital video data and annotations of British Sign Language 2008-2014 (Second Edition). London: University College London. (https://www.bslcorpusproject.org)

The recommended citation for the BSL Corpus annotations (including translations) deposited in 2017 is:

Schembri, Adam, Jordan Fenlon, Ramas Rentelis, & Kearsy Cormier. (2017). British Sign Language Corpus Project: A corpus of digital video data and annotations of British Sign Language 2008-2017 (Third Edition). London: University College London. (https://www.bslcorpusproject.org)