Survey: integrating volunteer and AI-enriched metadata into collections systems

What happens to data enriched by crowdsourcing, machine learning/AI, or a combination of methods? 

We are conducting a study that explores projects' successes and challenges in incorporating enriched data into catalogues or other core digital collections platforms in libraries, museums and archives. We're gathering information on the types of data, tools and processes used by project teams, and the barriers and aids to ingesting and integrating enriched data.

Your insights and experiences are invaluable to this study, and we would be grateful if you could spare 10-15 minutes of your time to share your experiences. Please note that your participation in this survey is entirely voluntary, and you have the freedom to withdraw at any point during the survey without any consequences. Your responses will provide us with essential information that can help shape the future of enriched collections data.

The survey has been extended until April 30th, but we encourage you to complete it sooner:

Who can take this survey?

We're interested in the experiences of anyone who's worked on crowdsourcing or machine learning projects to enrich collections data, including former staff. We're particularly interested in hearing from projects in languages other than English, and at any stage from work-in-progress to abandoned. Please share to help us reach more projects!

This survey is designed so that more than one person can respond for any institution or project, especially for large or complex organisations. We also welcome responses from inactive projects, and past project teams. Please feel free to collaborate with colleagues, or provide individual responses. If you can't provide a comprehensive answer for a question, feel free to provide a partial response from your own perspective. If you have more than one significant project, you may wish to do the survey once for each project.

The survey is particularly designed for people working in collecting institutions (libraries, archives, museums, etc) with their own catalogues, but we also welcome responses from projects that create or enrich data through e.g. research or community projects working with data from GLAMs, or 'roundtripping' records to return enhanced data to a catalogue.

We've made a PDF version with all the questions on the survey, to make it easier for respondents to collect information in advance: Survey questions: Challenges for integrating volunteer and AI-enriched metadata into GLAM systems. The live survey is open at

Thank you for your participation! 

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