The Road to Discovery is Paved with Standards
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1 The Road to Discovery is Paved with Standards Metadata Standards & Applications for Digital Resources Middle East Librarians Association November 17, 2017 Washington, D.C. by Claudia Horning Director, Metadata Services UCLA Library Cataloging & Metadata Center
2 Goals for today s session This workshop will introduce the concept of bibliographic control for digital resources, with a particular focus on visual resources such as photographs and posters. The workshop will explore the following topics: Importance of standards Standards for and types of metadata Metadata application profiles Metadata interoperability and quality issues Principles, best practices, and tools Metadata as data
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4 Standards are like toothbrushes. Everybody wants one but nobody wants to use anybody else s. Generally attributed to Connie Morella, 2006 ANSI World Standards Day
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6 Types of Metadata Standards Data structure standards (i.e. metadata schemas) Data value standards (e.g. controlled vocabularies, thesauri, pick lists, etc.) Data content standards (i.e. cataloging rules) Data exchange standards
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8 Types of Metadata Descriptive Administrative Technical Digital provenance Rights/Terms and conditions Structural Preservation Meta-metadata
9 Functions of Metadata DISCOVER RESOURCES MANAGE DOCUMENTS CONTROL IP RIGHTS IDENTIFY VERSIONS CERTIFY AUTHENTICITY INDICATE STATUS MARK CONTENT STRUCTURE SITUATE GEOSPATIALLY DESCRIBE PROCESSES
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11 Levels of Description Minimal: Allows users to cite the resource More useful: Allows users to perform basic searches and filtering Advanced: Allows users to browse and group search results More advanced: Allows users to perform more precise searches & evaluate resources
12 Example: minimal level description
13 Movie information freely available from AFI Film Catalog
14 Metadata Application Profiles MAPs describe the set of metadata elements, policies and guidelines defined for a particular project or object type MAPs are useful during the life of a project, and also after the fact Include information on schemas, controlled vocabularies, policies, required elements, etc.
15 Challenges for Visual Resources Determining title Ofness Isness Aboutness
16 What is the title? What is this of? What is this? What is this about?
17 What is the title? What is this of? What is this? What is this about?
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19 What is the title? What is this of? What is this? What is this about?
20 What is the title? What is this of? What is this? What is this about?
21 What is the title? What is this of? What is this? What is this about?
22 Questions to Ask What type of material(s)? How rich/structured does metadata need to be? Is there an existing community of practice for this resource type? What information is already available? What is the audience? How will they use the resources? Does your metadata need to interact with metadata from other institutions/in other databases?
23 Questions to Ask (cont.) What are your core research questions & goals, and what metadata is needed to support them? Do you need a data model and if so, what would it look like? What metadata already exists, and what will you need to create? How will you manage/store your metadata? How will you document your metadata? What resources are available?
24 Challenges and Risks Time Expertise Resources (funding & staff) Presentation of results Audience Finalizing
25 Metadata as Data Rich, structured metadata can be used for Textual analysis Image analysis Spatial analysis Network analysis
26 What languages do UCLA Library collections speak? How many languages are represented in the UCLA Library? What is their relative size?
27 Linked Open Data (LOD) Data that is structured and published so that it can be both interlinked with other LOD datasets and made openly accessible, shareable, and re-usable on the Semantic Web, with no/few restrictions
28 Ontology Structured/formal machine-readable specification with entities/ attributes/ interrelationships explicitly defined. Representing a particular domain of knowledge. Identifying existing ontology/ies or developing one is necessary first step to turn data sets into LOD.
29 To Learn More The Getty s Introduction to Metadata Stanford s Data Best Practices NISO s Understanding Metadata:
30 Questions? Claudia Horning
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