The Harmony team is working on Harmony Discovery, which will allow social scientists to find datasets about Autism Spectrum Disorder across data platforms. Harmony Discovery is due in 2025 and will extend the functionality of Harmony.
In the field of social sciences and mental health research, grounding study on concrete, longitudinal data is critical. For researchers focusing on Autism Spectrum Disorder (ASD), pinpointing relevant datasets might sometimes pose challenges. Harmony Discovery is a tool that streamlines this process, helping scholars trace these datasets with precision.
Harmony Discovery connects with multiple data sources including the UKLLC, Closer, the Catalogue of Mental Health Measures, HDR UK and ADR UK, to present researchers with datasets about longitudinal studies pertaining to various topics, including ASD. With the help of large language models, Harmony matches questionnaire items and variable names, ensuring that the shortlisted datasets align closely with the topic of research.
Datasets related to ASD obtainable from Harmony include:
Connected Bradford - Secondary Care: An active autism dataset used for secondary care in Bradford.
Special Treatment of Prediction Errors in Autism Spectrum Disorder, 2018-2021: This dataset analyses the assertion of the HIPPEA (High, Inflexible Precision of Prediction Errors in Autism), which suggests that neural processes in autism inflexibly place high precision on prediction errors.
Longitudinal studies allow for repeated observations of the same subjects over a period, enabling researchers to analyse changes at the individual level. Researchers specializing in ASD can benefit significantly from Harmony’s ability to efficiently zone in on appropriate ASD-related datasets.
In summary, Harmony Discovery optimizes the process of locating relevant datasets for researchers concentrating on Autism Spectrum Disorder, proving to be an invaluable tool in social sciences and mental health research.
