Metadata standards overview

Metadata standards and ontologies
IntroductionIntroductionIntroductionIntroduction totototo DigitalDigitalDigitalDigital HumanitiesHumanitiesHumanitiesHumanities ((((BBBB----KULKULKULKUL----G0R03A)G0R03A)G0R03A)G0R03A)
Roxanne Wyns
Roxanne.Wyns@libis.kuleuven.be

2
Short intro
Introduction to DH - Metadata standards and ontologies

3
On the agenda
I. Introduction to standards
II. The standards landscape in DCH
III. Ontologies
IV. Standards in research
V. Best practices
Source: dilbert.com

5
What is a standard?
“Put at its simplest, a standard is an agreed, repeatable way of doing
something. It is a published document that contains a technical
specification or other precise criteria designed to be used consistently
as a rule, guideline, or definition. Standards help to make life
simpler and to increase the reliability and the effectiveness of many
goods and services we use. Standards are created by bringing
together the experience and expertise of all interested parties such
as the producers, sellers, buyers, users and regulators of a particular
material, product, process or service.”
Definition according to ‘The British Standards Institution’ (BSI),
the world’s oldest standards setting organisation (1901)

6
What is a standard? & What does it do?
WHAT
• Agreed
• Rule, guideline, definition
• Documented
• Repeatable
• Material, product, process,
service
• Involved
• Knowledge
• …
WHY
• Simplicity
• Consistency
• Reliability
• Interpretable
• Interoperability
• Effective
• Innovation
• Productivity
• …

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Standards are everywhere

8
A world without standards…

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A standardized world?
Source: https://xkcd.com/927/

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Types of standards
• Standards not formally recognized by a
standards setting body, but widely used and
recognized by the sector
• Standards formally recognized by a standards
setting body (e.g. ISO)
• In-house
• Community
• National
• International, nearly always approved by an
international standards setting body (e.g. ISO
8601)
• Open standards

11
Standards development process
1. Open meeting
2. Consensus
3. Due process
4. Open IPR
5. One World
6. Open change
7. Open documents
8. Open interface
9. Open access
10.Ongoing support
A transparent and democratic process
Kenneth Krechmer, Open Standards Requirements, “The international
Journal of IT Standards and Standardisation Research”

12
Selecting a standard
Open IPR
Open access
On-going support

II. The standards landscape in DCH

14
GLAM infrastructure overview
Coll.MS CMS
DAM/
LTP
Collection management system
- Metadata creation and management
(master files)
- Closed system (access rights)
- Metadata is pushed to public portal
DAM / LTP
- Ingest of files + metadata
- PID
- Visualisation view
er
Admin
UI
Admin
UI
Front
- end
Admin
UI
Front
- end
Public Access portal / CMS
Additional content such as
news, story's, …
Metadata
for publication
Descriptive &
administrative metadata
Physical & Digital born items

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A shortlist of common standards
FORMATS
• Text/Data: Word, XML,
HTML, PDF, ODT, JSON …
• Syntax: RDF, XSD …
• Image: TIFF, JPEG,
JPEG2000 …
• Audio: MP3, WAV, …
• Video: AVI, MP4, MPG-1
…
• Virtual R: VRML97, X3D,
Quicktime VR …
TECHNICAL/PROTOCOL
• Search & retrieval: OAI-
MPH, SQL, Z39.50, HTTP,
FTP, RESTful, SOAP…
• Character encoding:
Unicode (UTF8) …
• PID: Handle, URI-URN,
DOI …
• AAI: SAML, XACML,
OAuth, OpenID …
• Image: IIIF …
DESCRIPTIVE
• Library: MARC, FRBR /
MARCXML, METS, MODS
…
• Museum: SPECTRUM,
CDWA, Object ID / LIDO …
• Archive: ISAD(G), ISAAR /
EAD …
• Other: MIDAS …
• General: DUBLIN CORE,
VRA, EDM …
• Document encoding: TEI
…

16
Heron infrastructureA standard approach
LIAS ingester
Lias
Uploader
Pawtucket
FTP
API
PNX
DC
API
API
DC
IIIF
SPECTRUM
TIFF
JPEG
…
LIDO
XSLT
EDM
API

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What is metadata

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Metadata @ libraries, archives and museums
• Domain specific description and export standards
• Often with (small) adaptations to fit specific needs
• Different standards according to it’s use environment
• Exports in different formats

Collection Management Environment

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Collection management system
Coll.MS CMS
DAM/
LTP view
er
Admin
UI
Admin
UI
Front
- end
Admin
UI
Front
- end
Descriptive &
Metadata
for publication

21
Libraries

22
Libraries

23
Archives

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Museums
http://collectionstrust.org.uk/spectrum/spectrum-resources/

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Other

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LIBIS Collection management layer
• Alma for libraries
• MARC standard
• CollectiveAccess
• Flexible data model
• Standard of choice
• Museum standard:
SPECTRUM
• Scope for archives
• Archival standards such as
ISAD(G), ISAAR…
• …

27
Use of standards
• Most organizations use in-house or adaptations of standards to fit
their specific needs
• Risk of losing interoperability
• Appoint an information manager
• Document changes and provide a mapping to the standard

29
Content management system
Coll.MS CMS
DAM/
LTP view
er
Admin
UI
Admin
UI
Front
- end
Admin
UI
Front
- end
Descriptive &
Metadata
for publication

30
Service environment
• Meaningful access for users
• Metadata describing an object, usually includes a digital surrogate
• Subset of the metadata
• Cross-domain, usable quality for specific service, IPR information

32
Discovery environment
Coll.MS CMS
DAM/
LTP view
er
Admin
UI
Admin
UI
Front
- end
Admin
UI
Front
- end
Descriptive &
Metadata
for publication

33
Resource discovery standards
Moving from the local to the global level
• For data interoperability: harvesting, aggregation, publishing,
indexing
• Access to metadata of many objects, often from many domains
• Result set with reference to digital representation
• Maximum relevance of results
• Limited metadata
• Dublin Core (DC) (or a variant of) is the most commonly used
metadata schema in de service and discovery environment
Formats, Shema’s, Mapping, Standards, Protocols, Semantics,…

34
Data aggregation in DCH
The Europeana example
• Using aggregators
• Source > [Intermediate] > Target
• Protocols, tools and formats
• XML (or CSV)
• HTTP or FTP upload
• OAI-PMH, API
• Ingestion and mapping tools

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Dublin Core (DC)
http://dublincore.org/
Dublin Core Metadata Element Set:
1. Title
2. Creator
3. Subject
4. Description
5. Publisher
6. Contributor
7. Date
8. Type
9. Format
10. Identifier
11. Source
12. Language
13. Relation
14. Coverage
15. Rights

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Dublin Core Metadata Initiative (DCMI)
http://dublincore.org/ ; http://dublincore.org/documents/dcmi-terms/

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Dublin Core Metadata Initiative (DCMI)
http://dublincore.org/ ; http://dublincore.org/schemas/xmls/qdc/dcterms.xsd

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MARC XML
Example of a MARC XML record

39
MARC XML
http://www.loc.gov/marc/

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MARC XML
http://www.loc.gov/marc/bibliographic/

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EAD
http://www.loc.gov/ead/

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EAD
eadheader

43
EAD
archdesc

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EAD
archdesc

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EAD
http://www.loc.gov/ead/ ; http://www.loc.gov/ead/EAD3taglib/index.html
RLG Best Practice Guidelines for Encoded Archival Description, 2002

46
LIDO
• Validated as an official standard by ICOM/CIDOC Data Harvesting
and Interchange Working Group
• XML harvesting schema
• Documentation available on: www.lido-schema.org
Lightweight Information Describing Objects

47
LIDO
Main components

48
LIDO
• Events based on CIDOC-CRM (ISO 21127)
• An object is described according to a series of event that took place
in its lifetime
Event based structure

49
LIDO
Example record

50
LIDO
Example record

51
EDM
• Cross-domain model for bring together diverse collections in
Europeana
• Distinguish “provided objects” (painting, book, movie, etc.) from their
digital representations
• Distinguish object from its metadata record
• Allow multiple records for the same object, containing potentially
contradictory statements about it
• Support for objects that are composed of other objects
• Support for contextual resources, including concepts from controlled
vocabularies
Europeana Data Model
https://pro.europeana.eu/resources/standardization-tools/edm-documentation

52
EDM
Europeana Data Model

54
Ontology (information science)

55
Simply put
• Ontologies are rules to describe:
• Context
• Relationships
• Ex. What is an author? How does it relate to an editor/work ...
But what are they used for?

56
Context - The Semantic Web
• Gives structure/meaning to documents
• Extension to the current web
• URI
• HTTP
• RDF
https://open.hpi.de/courses/semanticweb2016

57
Moving from documents to data
DOCUMENTS
• Human readable
• Connected through links
• Links (relations) in 1 direction
• Findable through search engine (indexing)
• Difficult to interpret by software (no context)
DATA
• Machine readable
• Decentralized
• Exists of links
• Easy for machines to follow
• Relations in 2 directions (graph)
• Findable with own Query language (SPARQL)
Browser
Search
Engine
Agents
Search
Engine
VS

58
(hyper)LINKS
• Highlighted text on web page
• One directional
• Accessed by clicking it
• References documents
• Opens a new window, download
• Jumps to a location in the document
• Stored in a HTML document and rendered by a web browser

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Linked Data
The link in linked data is a statement. It states a fact. We can tell a story by putting these
statements together. Computers can be made to understand these stories/graphs

60
Describing data on the Web
• RDF forms the basis of Semantic web technologies
• Universal language to describe the characteristics of a resource on
the web
• Using XML for syntax and URIs for naming
• Uses a directed graph to describe resources
• Makes statements about resources in the form of subject-predicate-
object triplets
• RDF triples provides a labelled connection using URIs to make it
possible to link data with one another
• In this way a machine is able to find the semantic relations between
data
RDF ~ Resource Description Framework

61
RDF triplets

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Triplets identified by an URI
Uniform Resource Identifier = global unique identifier

63
Ontologies
• Ontologies are rules to describe:
• Context (classes)
• Relationships (properties)
• Ex. What is an author? How does it relate to an editor/work ...

64
Ontologies ≠ Taxonomies/Thesauri/…
• Taxonomies, Vocabularies, Thesauri, Classifications…
• Function on a different level then ontologies
• Important role in the Semantic Web and Linked Data world
• Help with the interpretation and integration of data between different datasets
• May lead to the discovery of new relationships between information
expressed in a different natural language

65
Thesaurus = concept, labels …

66
Ontology = Formal knowledge
representation scheme

67
Another example ~ GeoNames authority
file

68
Another example ~ GeoNames ontology
http://www.geonames.org/ontology/ontology_v3.1.rdf

69
SKOS format
• Solution for converting a “classic” thesaurus or vocabulary into a
semantically interoperable format
• Based on the RDF specification, enables migration to OWL
• Not a formal knowledge representation / ontology
• Structured according to the ISO 25964 norm dedicated to thesauri
and interoperability with other vocabularies
• Components
Concepts Documented
URIs Semantically related (BT, NT, RT)
Labelled Concept schemes
Simple Knowledge Organisation System

70
SKOS format
Simple Knowledge Organisation System

Ontologies in Cultural Heritage

72
BIBFRAME
• Library of Congress
• To replace MARC
• Ongoing process
• From one record to data statements
• Integration with other standards
• Findability on the web
• New types of materials and metadata
Bibliographic Framework Initiative

73
CIDOC-CRM
• CIDOC object-oriented Conceptual Reference Model (CRM)
• Domain ontology for concepts and information in cultural heritage
and museum documentation
• International standard (ISO 21127:2014) for the controlled exchange
of cultural heritage information
• Extensible semantic framework
• Object oriented model

74
CIDOC-CRM
• CIDOC object-oriented Conceptual Reference Model (CRM)
• Domain ontology for concepts and information in cultural heritage
and museum documentation
• International standard (ISO 21127:2014) for the controlled exchange
of cultural heritage information
• Extensible semantic framework
• Object oriented model
Source: http://www.cidoc-crm.org/Resources/rdf-file-for-crm-core

75
FRBRoo
• Joint effort of the CIDOC-CRM and Functional Requirements for
Bibliographic Records (FRBR) international working groups
• FRBR-object oriented
• Formal ontology intended to capture and represent the underlying
semantics of bibliographic information
• Facilitate the integration, mediation, and interchange of bibliographic
and museum information
Functional Requirements for Bibliographic Records - object oriented

76
FRBRoo
Functional Requirements for Bibliographic Records - object oriented
Source: http://83.212.168.219/FRBR_Tutorial/graph-exercises

78
Schema.org
• A vocabulary (ontology) for structured data on the Internet, on web
pages, in email messages, ...
• By Google, Microsoft, Yahoo and Yandex
• Embeddable in html by:
• Microdata
• RDFa
Source: http://schema.org/docs/full.html

79
LD to provides context to search engines

80
Representation of Limo object in Schema.org
[{
"@context": "http://schema.org",
"@type": "Book",
"@id":
"http://resolver.libis.be/IE5307748",
"name": "Physica",
"editor": {
"name": "Verheyden, Engelbertus",
"jobTitle": "Professor (1737-1804)"
},
"author": {
"@type": "Person",
"name": "Barjon, Caefarius",
"jobTitle": "Student"
}
}]

81
Representation of Limo object in Schema.org

83
Why important for you?
Research Data Lifecycle
UK Data Archive
JISC
University of Virginia Library

84
Creating data
Creating data
• Design research
• Plan data management (formats, storage
etc.)
• Plan consent for sharing
• Locate existing data
• Collect data (experiment, observe, measure,
simulate)
• Capture and create metadata
UK Data Archive

85
Processing data
Processing data
• Enter data, digitize, transcribe, translate
• Check, validate, clean data
• Anonymize data where necessary
• Describe data
• Manage and store data
UK Data Archive

86
Analyzing data
Analyzing data
• Interpret data
• Derive data
• Produce research outputs
• Author publications
• Prepare data for preservation
UK Data Archive

87
Preserving data
Preserving data
• Migrate data to best format
• Migrate data to suitable medium
• Back-up and store data
• Create metadata and documentation
• Archive data
UK Data Archive

88
Access to data
Giving access to data
• Distribute data
• Share data
• Control access
• Establish copyright
• Promote data
UK Data Archive

89
Re-using data
Re-using data
• Follow-up research
• New research
• Undertake research reviews
• Scrutinize findings
• Teach and learn
UK Data Archive

90
Sharing data to advance Science

91
Metadata @ Arts, Social Sciences
and Humanities
• No tradition in using
descriptive standards
• Data models according to
researchers needs
• Can be based on common
principles within the research
domain
• Increase of data sharing
thanks to VRIs (Dariah,
Clarin…)
Source: Digital Curation Centre, metadata standards in Social Science & Humanities

92
EOSC
European Open Science Cloud
Source: EOSC infographic Source: EOSC Declaration

V. Best practices in metadata
modeling

94
Identify standards & common practices
• Identify and use relevant metadata standards in your field
• If no metadata standards exist, explore common practices in the field
and collaborate if possible

95
Data modeling
• Create a data model
• Choose and use standard terminology to enable discovery
• Maintain consistent data typing

96
Data documentation
• Create a data dictionary
• Update data documentation on a regular basis during every step of
the lifecycle
• Document the integration of multiple datasets
• Describe the temporal extent your dataset

97
Data storage
• Create, manage, and document your data storage system
• Document and store data using stable file formats
• Describe the overall organization of your dataset

98
Data access and reuse
• Describe the dataset, incl. rights, versions, processing tools,…
• Provide the organization structure of your dataset
• Include a metadata specifications document in each dataset
• Deposit your dataset in a domain specific of institutional repository

99
Discover more
• Digitisation: Standards Landscape for European Museums, Archives, Libraries
• Digital Curation Centre Resources on Social Sciences and Humanities
• European Open Science Cloud Declaration
• FAIR data principles
• Data one, Best practices in RDM
• Research Data management at KU Leuven
• LIBIS Services for researchers
• Ontologies for Cultural Heritage

100
Thank you! Questions?
Roxanne Wyns - Roxanne.Wyns@kuleuven.be
Source: http://jennriley.com/metadatamap/

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