datos.bne.es: Publishing and

consuming

Daniel Vila Suero

dvila@fi.upm.es

Ontology Engineering Group, Universidad Politécnica de Madrid

Acknowledgements: OEG Members, BNE staff (Elena Escolano, Marina Jimenez Piano, Ana Manchado, Mar Hernández Agustí,

Ricardo Santos and others)

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datos.bne.es

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Background

• Initiative from Biblioteca Nacional de España together with OEG-UPM Madrid.

• Multidisciplinary effort: Librarians, Computer scientists, linguists..

• Close collaboration between library experts and computer scientists.

• Initiated as a small scale proof-of-concept: the "Cervantes dataset" using IFLA vocabularies (FRBR, ISBD) and others (MADS, DC, RDA..)

datos.bne.es

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Main goals

• Perform the transformation incrementally and iteratively

• Develop a system where library experts can define and assess the mappings to RDF independently from the IT people

• Be vocabulary agnostic (BNE uses FRBR as core model, but the system would allow them to use RDA for example)

• Have a clear picture of the source data before you start to transform (help to detect possible deficiencies in the source data)

datos.bne.es

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Source MARC recordsdatos.bne.es

AUTHORITY BIBLIOGRAPHIC

Persons

Corporate bodies

Conferences

Titles

Subject

76576 Maps

320727 Sound recordings

166017 Gravings, drawings, pictures

35770 Manuscripts

143959 Ancient books

2696560 Modern books

178473 Scores

3021 Electronic resources

156634 Serials

96672 Videos

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Some figuresdatos.bne.es

• Total number of authority records: 4.100.000• Total number of bibliographical records: 2.390.140• Total number of RDF triples: 58.053.215 • Number of links: (15% authorities): 587.520 • Linked sources:

• VIAF• SUDOC (French Collective University Catalogue) FR• GND (German National Library Authorities) GER• LIBRIS Sweden• DBPedia• Soon BNF, BNB, German Bibliographie

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Some statisticsdatos.bne.es

2,390,103

1,969,526

1,163,764

1,114,719

497,644

282,879

Manifestation

Work

Person

Expression

Thema

Corporate Body

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Some statisticsdatos.bne.es

"is c

reat

or (p

erso

n) o

f"

"is c

reat

ed b

y (p

erso

n)

"is e

mbo

dimen

t of"

"is e

mbo

died

in"

"is re

alize

d th

roug

h"

"is re

aliza

tion

of"

"is p

art (

work)

of"

"has

par

t (wor

k)"

"is s

ubor

dinat

e of

"

"is c

reat

ed b

y (c

orpo

rate

bod

y)"

"is c

reat

or (c

orpo

rate

bod

y) o

f"

"is p

art (

expr

essio

n) o

f"

"has

par

t (ex

pres

sion)

"

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000 2,129,2222,129,222

1,246,773

1,246,773

1,054,736

1,054,736

85,347 85,347 78,56116,462 16,462

755 755

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Publishing

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Our data modelPublishing

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Transformation processPublishing

• How to facilitate the mapping process to library experts?1. Use a familiar and intuitive interface: Spreadsheets

2. Work only on what's in the database: Pre-process records to build the spreadsheets

• 3 step-process 3 different spreadsheets

1. Classification: is it a Person? a Work? a Manifestation?

2. Annotation: name, birth date, title, language of expression

3. Relation: find relationships between entities (Person is creator of a certain work)

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Publishing

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Mapping processPublishingOpen mappings at: http://bne.linkeddata.es/mapping-marc21

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Mapping processPublishing

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Mapping processPublishing

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Still a lot of work to doPublishing

• We cover only core relations of FRBR

• There are a significant amount of manifestations not linked to their expressions currently looking at more sophisticated clustering techniques

• Manifestations are not linked to their corresponding digitalized materials at the digital library (Biblioteca Digital Hispánica) Next version (to be published this year) will contain these links

• Classification step can be further automatized

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Consuming

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Perspectives

• 2 different perspectives:- Systems and applications:

• SPARQL endpoint, • Linked Data API

- End-user interfaces

• + an interesting side-effect:- By applying FRBR and RDF mappings we can (and did)

improve the catalogue

• Using standard web technologies and more intuitive models we open the door to:

- Data analytics and cleansing, catalogue enrichment, reuse by smaller institutions…

Consuming

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Graph analysis exampleConsuming

Using Open-source tools:Gephi for example

http://bne.linkeddata.es/graphvis

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Enabling access to systems and appsConsuming

Linked Data API: http://datos.bne.es/frontend/persons

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Flexible access to dataConsuming Out of the box:

• Search by every field• Access cluster of resources• Filtering• Paging• Serve multiple formats: XML,

Turtle, JSON

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Different views on the dataConsuming

HTML

XML

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ConsumingEND-user interfaces

Current linked data opens the door to:• Re-rank OPAC results• Better clustering of results• Recommendation• Enhance data from other sources