Summary Metadata Its Functions in Knowledge Representation for

Summary Metadata: Its Functions in Knowledge Representation for Digital Collections 1

Review Understanding Metadata • Metadata types • Matching types with functions • Metadata standards • Metadata implementation – the workflows 2

Metadata Classes/Types CIC (Committee on Institutional Cooperation) 1999 (NISO): Understanding Metadata 2004 Gilland-Swetland Getty: Intro to Metadata 2000 Descriptive Administrative . Preservation. Rights management Preservation Structural Greenburg: A quantitative categorical analysis of. . . 2001 Technical Structural Discovery Administration Authentication Use 3

Matching types with functions The DCMI defines metadata as … … • data associated with either an information system or an information object for purposes of – description, – administration, – legal requirements, – technical functionality, – use and usage, and – preservation (DCMI Glossary, 2005) 4

Metadata Standards for data structures and semantics metadata element sets e. g. , Dublin Core Metadata Element Set (DCMES) Standards and Guides for data content created to guide the practices of metadata generation e. g. , CCO, Using Dublin Core Standards for data values value encoding schemes e. g. , DCMI Type Vocabulary | RFC 4646 Tags for Identifying Languages | LCSH 5

Change … We need 1. The Web: From the Web of Documents to the Web of Data 2. Our Work: From [bibliographic and authority] control to knowledge organization, resource discovery, and delivery 3. Our Data: From machine-readable to machine-processable and become Web resources (linked data) 6

Metadata = Cataloging ? Evolution of the Men

Metadata Workflow 1. Analyze & determine the functional requirements User interface; search, browsing functions User needs; Elements for search and browse; Links between records & data; Filtering fields Type of resources to include in DL e. g. , text, images, Web resources Accessibility Influence of external services Limitations or additional conditions 2. Decide a responsibility model Individual institution • Reuse existing records; • Harvest & reuse external metadata 3. Select metadata standards / Develop application profiles Standards for data structures e. g. , Dublin Core, MODS, CDWA, EAD, VRA Core, … Standards for data content e. g. , Best practice guidelines, AACR 2, CCO, DACS … Standards for data values e. g. , controlled term lists, classification schemes, thesauri, subject heading lists, name authority files … Standards for data exchange 4. Create metadata records/Control quality Data creation Data harvesting Use OAI Protocol for Metadata Harvesting Data conversion Use mapping tables/ crosswalks e. g. , MARC 21, UNIMARC, ISO 2709 format, XML, … Develop metadata application profiles e. g. , DC-LIB; NLM-MS Collaboration • Share • Reuse • Add values • Plan workflow & timing • Local • Regional • National • International projects 1) Select a “base” metadata namespace; select elements from the base schema Data integration 2) Select additional elements from other metadata name-spaces if needed 3) Specify the use of these elements: • obligations, • data value encoding rules & schemes, • best practices, • relationship with other elements 4) If needed, define more local Elements in a declarative document 5) Encode all elements in machineprocessable schemas Implement best practices; semi-auto when generating data Support search, browse, Results display, & delivery Distribute Expose Share & exchange Normalize Aggregate Ingest Control & improve quality Metadata storage: Databases, Repositories 5. Use in DLs Maintain Transfer Reuse & repurpose Maximize the usage Preserve Support linked data ©Lee, Zeng, and Hayes for IFLA GDL-WG, 2009