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    <abstract>Increased access to large datasets has driven progress in NLP. However, most computational studies of clinically-validated, patient-generated speech and language involve very few datapoints, as such data are difficult (and expensive) to collect. In this position paper, we argue that we must find ways to promote data sharing across research groups, in order to build datasets of a more appropriate size for NLP and machine learning analysis. We review the benefits and challenges of sharing clinical language data, and suggest several concrete actions by both clinical and NLP researchers to encourage multi-site and multi-disciplinary data sharing. We also propose the creation of a collaborative data sharing platform, to allow NLP researchers to take a more active responsibility for data transcription, annotation, and curation.</abstract>
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%0 Conference Proceedings
%T The importance of sharing patient-generated clinical speech and language data
%A Fraser, Kathleen C.
%A Linz, Nicklas
%A Lindsay, Hali
%A König, Alexandra
%Y Niederhoffer, Kate
%Y Hollingshead, Kristy
%Y Resnik, Philip
%Y Resnik, Rebecca
%Y Loveys, Kate
%S Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F fraser-etal-2019-importance
%X Increased access to large datasets has driven progress in NLP. However, most computational studies of clinically-validated, patient-generated speech and language involve very few datapoints, as such data are difficult (and expensive) to collect. In this position paper, we argue that we must find ways to promote data sharing across research groups, in order to build datasets of a more appropriate size for NLP and machine learning analysis. We review the benefits and challenges of sharing clinical language data, and suggest several concrete actions by both clinical and NLP researchers to encourage multi-site and multi-disciplinary data sharing. We also propose the creation of a collaborative data sharing platform, to allow NLP researchers to take a more active responsibility for data transcription, annotation, and curation.
%R 10.18653/v1/W19-3007
%U https://aclanthology.org/W19-3007
%U https://doi.org/10.18653/v1/W19-3007
%P 55-61

Markdown (Informal)

[The importance of sharing patient-generated clinical speech and language data](https://aclanthology.org/W19-3007) (Fraser et al., CLPsych 2019)

• The importance of sharing patient-generated clinical speech and language data (Fraser et al., CLPsych 2019)

ACL

• Kathleen C. Fraser, Nicklas Linz, Hali Lindsay, and Alexandra König. 2019. The importance of sharing patient-generated clinical speech and language data. In Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, pages 55–61, Minneapolis, Minnesota. Association for Computational Linguistics.