Canalizing the Maelstrom of Metadata - Extensions on the Hourglass Model

Canalizing the maelstrom of metadata: extensions on the Hourglass Model

Brecht Declercq, VIAA, Belgium

CCAAA – Joint Technical SymposiumSingapore, 07.03.2016

A theoretical frameworkfor developing strategies

for the creation and useof (descriptive) metadata

1. What is the Hourglass Model?

Linked dataUser generated metadata

Automatically extracted metadata

Preservation metadata

Descriptive metadata

etc ...

Production metadata?Linked metadata

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

The Hourglass Model

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

USERGENERATEDMETADATA

AUTOMATICALLYGENERATEDMETADATA

PRODUCTION METADATA

FULLMANUAL

METADATA

PRESERVATION &COLLECTION

MANAGEMENT

ENHANCEMENT&

CONTEXTUALISATION

SEARCH &

RETRIEVAL

The Hourglass Model

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

USERGENERATEDMETADATA

AUTOMATICALLYGENERATEDMETADATA

PRODUCTION METADATA

FULLMANUAL

METADATA

PRESERVATION &COLLECTION

MANAGEMENT

ENHANCEMENT&

CONTEXTUALISATION

SEARCH &

RETRIEVAL

The Hourglass Model

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

USERGENERATEDMETADATA

AUTOMATICALLYGENERATEDMETADATA

PRODUCTION METADATA

FULLMANUAL

METADATA

PRESERVATION &COLLECTION

MANAGEMENT

ENHANCEMENT&

CONTEXTUALISATION

SEARCH &

RETRIEVAL

The Hourglass Model

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

USERGENERATEDMETADATA

AUTOMATICALLYGENERATEDMETADATA

PRODUCTION METADATA

FULLMANUAL

METADATA

PRESERVATION &COLLECTION

MANAGEMENT

ENHANCEMENT&

CONTEXTUALISATION

SEARCH &

RETRIEVAL

The Hourglass Model

2. Extending the model

Recent developments: Further integration with production systems New approaches: e.g. scan & OCR tape boxes

1. Metadata from production

- collaboration of producers often needed! almost only for contemporaryborn digital content

+ cheap high quality quick high level of detail

1. Metadata from production

2. User generated metadata

Recent developments: Diversification: from low tech to high tech New approaches: consumer generated metadata

from ‘conscious’ to ‘unconscious’ metadata

ARCHIVEBROADCAST

TARGET GROUP

EDUCATION

TARGET GROUP

RESEARCH

TARGET GROUP

GENERALAUDIENCE

MEDIA VALUE CHAIN: METADATA FLOWFROM USER GENERATED METADATA TO CONSUMER GENERATED METADATA

FIRST PURPOSE RE-PURPOSEARCHIVE

BROADCASTER BUSINESS INTELLIGENCE ARCHIVE BUSINESS INTELLIGENCE

- reliability? IPR issues labour intensity - net gains? subjective sustainable?

+ very cheap high quality public involvement with your collection!

2. User generated metadata

3. Automatically generated metadataRecent developments: Ever more cases in daily practice

3. Automatically generated metadataRecent developments: New approaches: SaaS

- high tech quality? interface? system architecture integration?

+ cheap quick high level of detail objective

3. Automatically generated metadata

3. Implementing the Model

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

Evolutions : starting pointFULL

MANUALMETADATA

PRESERVATION &COLLECTION

MANAGEMENT

SEARCH &

RETRIEVAL

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

Evolutions : 1st MAM implementationFULL

MANUALMETADATA

PRESERVATION &COLLECTION

MANAGEMENT

SEARCH &

RETRIEVAL

PRODUCTION METADATA

ENHANCEMENT&

CONTEXTUALISATION

PRODUCTION METADATA

USERGENERATEDMETADATA

AUTOMATICALLYGENERATEDMETADATA

CREATIONLEVEL

PROCESSINGLEVEL

PURPOSELEVEL

FULLMANUAL

METADATA

PRESERVATION &COLLECTION

MANAGEMENT

SEARCH &

RETRIEVAL

The Hourglass Model

A NEW METADATA CREATION AND USE STRATEGY: Institutionally: new relations with the world outside Organisationally: new roles, structures, competencies Technically: new systems, new architectures

organisationalinstitutionalTechnical“open, smart and connected”

[J. Oomen]

Institutional

MORE OPENNESS AT THE INPUT, E.G. USER AS METADATA CREATOR

MORE OPENNESS AT OUTPUT: E.G. LINKING COLLECTIONS, (OPEN) API’S

Organisational

NEW TECHNICAL AND INSTITUTIONAL POSSIBILITIES

NEW USERS / TARGET GROUPSNEW NEEDS / DEMANDS

DECI

SIO

N M

AKIN

G

PRO

CESS

MAN

AGEM

ENT

QUA

LITY

CHE

CKIN

G

RECO

GNIZ

E &

CO

NN

ECT

MET

ADAT

A M

ANAG

ER

Technical

MAMs AND ESB’S ARE NOT DEAD

(c) Dinah Handel, CUNY

SOLID STANDARDS, FLEXIBLE CONNECTIONS

GRADUAL SYSTEM ADAPTATIONS

RAPIDLY EVOLVING TECHNOLOGY

EVER MORE EXTERNAL CONNECTIONS

Technical

4. Conclusion

A future-proof frameworkfor helping AV archives

to allow their metadata strategyto evolve

Slide 34

Thank you!

brecht.declercq@viaa.be

http://be.linkedin.com/in/brechtdeclercq

@brecht_declercq