What Is Trusted Data for AI and How Do You Get It?
Trusted data for AI has checked quality, defined meaning, traceable lineage, an owner and governed access. Here is how to get it, one use case…
Emily Winks is a data governance expert who came to data through library and information science. Over 18+ years she has moved from children's librarian to information architect at WeWork to Atlan's Founder's Office, bringing a cataloging discipline to how enterprises classify, govern, and trust their data. She writes on data governance, enterprise data management, and the context layer.
After graduating with a Master of Library and Information Science and a certificate in Records Management and Archives, Emily began her career as a children's librarian. After seven years in libraries she left to join the corporate workforce — she doesn't sing The Hokey Pokey (as often) anymore, but still puts her whole self in when it comes to navigating the ambiguities of data, making digital information clear, and empowering others to do the same.
She spent her library years at the Smithtown Special Library District and as a Senior Librarian at the New York Public Library before moving into information architecture. At WeWork she progressed from Information Architect to Senior Information Architect to Data Product Architect, building the classification and data structures behind a fast-scaling business.
Emily joined Atlan's Founder's Office in 2023, where she works at the intersection of data governance, enterprise data management, and the context layer — writing on how organizations classify, govern, and make their data trustworthy for both teams and AI agents.
Trusted data for AI has checked quality, defined meaning, traceable lineage, an owner and governed access. Here is how to get it, one use case…
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Emily is a member of the Atlan team. Articles published under her byline reflect her own analysis and expertise; Atlan's editorial team works with her on structure and clarity but does not author content attributed to her. She reviews and approves every piece published under her byline before publication.