Enhancing Survey Operations through Software Solutions: from questionnaire design to data curation |
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| Coordinator 1 | Dr Vilma Agalioti-Sgompou (Centre for Longitudinal Studies, UCL Social Research Institute) |
| Coordinator 2 | Dr Aida Sanchez-Galvez (Centre for Longitudinal Studies, UCL Social Research Institute) |
Survey operations increasingly rely on the use and/or development of software or code solutions across the survey lifecycle. These solutions support the survey from questionnaire design and survey operations during fieldwork, to data curation, metadata generation and sharing.
In this session we invite colleagues to share and discuss their experience and ideas on designing, developing and using software solutions or code to support and enhance survey operations, including challenges experienced, limitations, lessons learnt, and advice on better practices. These technical solutions can be in the current process of design, development, test phase, or planned for further enhancements.
We welcome presentations on software solutions and code that support survey operations, such as:
• Technical setup of questionnaire design, facilitating from the outset a smooth post-survey data processing and generation of metadata.
• Automated data curation processes, for example, technical protocols or bespoke scripts for processing and checking of survey data, paradata, and metadata, data quality assurance, validation techniques and programmatic identification of data inconsistencies or errors.
• Implementation of ETL (extract, transform and load) streamlined data workflows.
• Use of databases to store and manage data and metadata, public sharing of data management syntax sharing.
• Automated generation of documentation and versioning of data products.
Finally, we invite the presentation of solutions written in a variety of languages, such as, programming in statistical software (e.g. SPSS, Stata, SAS) or scripting languages (R, Python), or any other language/framework used, e.g. .NET), as well as long-term storage in databases (e.g. MS SQL Server, PostgreSQL, MySQL, MongoDB).