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Success of AI in academic libraries depends on underlying data

CILIP

Success of AI in academic libraries depends on good underlying data. nder, scientific information specialist: Success of AI in academic libraries depends on good underlying data. Why do we hear so little in this respect from libraries on this side of the Atlantic? Q&A with Stephan Holl?nder,

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Do I Need a Data Catalog?

erwin

The data catalog is a searchable asset that enables all data – including even formerly siloed tribal knowledge – to be cataloged and more quickly exposed to users for analysis. Three Types of Metadata in a Data Catalog. Another classic example is the online or card catalog at a library. Technical Metadata.

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Five benefits of a data catalog

IBM Big Data Hub

Imagine walking into the largest library you’ve ever seen. Fortunately, the library has a computer at the front desk you can use to search its entire inventory by title, author, genre, and more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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The Information Management Umbrella

Brandeis Records Manager

Your industry may dictate your relationship with your library people, if you even have a relationship with them. In academia, records management tends (not exclusively) to be grouped organizationally with library and archival units. In one sense, we are the Charlie Brown of an academic library department.

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Part 2: OMG! Not another digital transformation article! Is it about the evolution from RIM to Content Services?

ARMA International

IA overlaps many areas of design, such as navigation, user experience, user interface, security model, taxonomy, and metadata. In the past, DM mostly focused on “save, search, and share,” version control, metadata, and permissions. Therefore, the two are “connected” when dealing with large volumes of structured and unstructured data.