Australian Data Archive using Harmony for questionnaire harmonisation

Harmony case study

The Australian Data Archive (ADA) is a national service for the collection and preservation of digital research data, similar to the UK Data Archive (UKDA).

The ADA provides data access through the ADA Dataverse. The collection includes polls on housing conditions in Australian states, political views over time across the country, questions about employment or health, and other datasets that the ADA has collected over the years (such as the Australian election study).

In 2023, the ADA embarked on a project to harmonise a vast collection of survey questions, seeking a solution that could effectively identify and group similar items across different studies. Researchers at the ADA found Harmony, a data harmonisation tool powered by natural language processing (NLP), and the ADA recognised its potential to streamline this process.


The ADA faces several challenges in managing its extensive questionnaire data:

  1. Effort-intensive manual harmonisation: The manual comparison and grouping of questionnaire items is a time-consuming and labour-intensive task.
  2. Lack of consistency and standardisation: Harmonisation without automated tools can lead to inconsistencies and variations in the categorisation of items.

Integrating Harmony into the ADA’s workflow

The ADA may integrate Harmony into its processes, using its powerful NLP capabilities to address the challenges and expedite questionnaire harmonisation:

  1. Automated item comparison: Harmony’s NLP algorithms automatically compared and grouped questionnaire items based on their semantic similarity, eliminating the need for manual effort.
  2. Enhanced consistency: Harmony’s intelligent approach ensured consistent categorisation of questionnaire items, reducing inconsistencies and improving data integrity.

Impact of Harmony on ADA’s Operations

Harmony has the potential to bring significant benefits to the ADA’s data harmonisation processes:

  1. Reduced harmonisation time: Harmony could significantly reduce the time required for questionnaire harmonisation, enabling the ADA to manage its extensive data more efficiently.
  2. Improved data quality: Harmony could enhance the quality of the ADA’s questionnaire data by ensuring consistent categorization and reducing inconsistencies.
  3. Enhanced data interoperability: Harmony could facilitate the interoperability of questionnaire data across different studies, enabling researchers to compare and analyse data more effectively.


The Australian Data Archive aims to enhance the efficiency of its data management tasks. Harmony’s capacity to automatically compare, group, and categorise questionnaire items can be instrumental in streamlining the ADA’s harmonisation processes. This approach can not only reduce operational effort but also elevate data quality and foster greater data interoperability. As the ADA expands its repository of social science research data in the future, Harmony has the potential to play a crucial role in preserving the integrity and accessibility of this valuable resource.

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