The Harmony team is working on Harmony Discovery, which will allow social scientists to find datasets about Smoking across data platforms. Harmony Discovery is due in 2025 and will extend the functionality of Harmony.
A wealth of data for research lies in longitudinal studies. These rich veins of information provide revealing insights about behaviours, conditions, and attitudes over time, allowing researchers to assess individual and societal change. If you’re interested in studying smoking patterns, then Harmony Discovery is an indispensable tool for you.
Harmony Discovery is a cutting-edge tool, explicitly designed to assist social science researchers in finding datasets pertaining to specific topics, including longitudinal studies related to smoking. Harmony employs sophisticated language models, adept at identifying questionnaire items and variable names that match the researcher’s topic of interest - in this case, ‘smoking’.
Harmony is connected to a range of prominent sources of valuable data. Sources like the UKLLC (UK Longitudinal Linkage Collaboration), HDR UK (Health Data Research UK), ADR UK (Administrative Data Research UK) and Closer provide granular as well as broad-ranging data for diverse research needs.
For those working on mental health related themes, the Catalogue of Mental Health Measures (CMHM) is a valuable resource. Owing to the established link between smoking and mental health, exploring this resource can be particularly useful for a well-rounded study into smoking behaviours.
One of the key features of our computational tool is its ability to process time-specific data. For example, one can access databases containing surveys on smoking conducted during specific periods. An illustrious example being the surveys on smoking conducted in 1976, meticulously categorised by the exact range of dates in July and June.
These datasets could provide a wealth of insights into the prevailing attitudes, consumption patterns, and public consciousness around smoking during that era. It’s a treasure trove for researchers focusing on the temporal aspects of societal behaviour and shifts around smoking.
In conclusion, Harmony Discovery comes as a massive boon for researchers studying longitudinal smoking patterns. With its intuitive interface, extensive connectivity, and linguistic prowess, this tool simplifies the process of discovering relevant datasets, thereby accelerating and enhancing the research process. Tap into the power of Harmony Discovery and illuminate your research into smoking with data-driven insights.
