1. Wikidata + GLAM
Example Projects
Beat Estermann, Lausanne, 14 September 2017
▶ Bern University of Applied Sciences, E-Government Institute
Palais de Justice de Montbenon, Lausanne. Photo: Olivier Bruchez. CC BY-SA 2.0 (Flickr / Wikimedia Commons).
Unless otherwise noted,, the content of this presentation is made available under the CC BY 4.0 license.

2. ▶ Inventory of Heritage Institutions
▶ Inventory of Protected Buildings
▶ Performing Arts
Example Projects – Overview

3. Inventory of Heritage Institutions

4. ▶ Starting Point:
• Existing inventories of heritage institutions in various countries
(cf. OpenGLAM Benchmark Survey)
• For most countries, many heritage institutions are not referenced in Wikidata yet.
▶ Goal / Rationale:
• Create a worldwide inventory of heritage institutions
▶ Swiss Pilot Project:
• Case Report
▶ Potential Partners:
• ICOM, IFLA, ICA
The Project in a Nutshell
Platform Typology According to Information Depth
Description of institutions
Description of collections
Item-level metadata
Item-level content
Searchable content (OCR, transcriptions, etc.)
Structured Data

5. tinyurl.com/zhdke63  1858 GLAMs in CH and FL
Example item with few / many statements

6. ▶ Existing Data Set of Swiss Heritage Institutions
• Add coordinates based on street address
• Clean up existing statemets (e.g. institution != building)
• Add further statements (e.g. inception, director, etc.)
• Translate labels and descriptions
▶ Swiss ISIL Inventory
• Ingest the ISplus dataset (ISIL Inventory)
▶ Ontology / Conceptual Work
• Clean out the existing ontology (clarify & translate definitions)
• How to describe the institutions’ collections in Wikidata?
▶ Data Ingest for Other Countries
• Find a contact person in the respective country,
▶ Tools for Data Maintenance
• Set-up / create tools to monitor coverage and data completeness
▶ Put the Data to Use
• In Wikipedia, Wikivoyage, etc.
• In apps, etc.
To do

7. ▶ Finding the time / volunteers to further pursue the project
 break the tasks down into smaller chunks
▶ Finding a contact person in every country that assists in
gathering the GLAM inventories and helps maintaining
the database
▶ How to model the description of heritage collections?
• Information to guide users, visitors, researchers, etc.
• Information to support the coordination of preservation and
digitization activities
Main Challenges

8. Inventory of Protected Buildings

9. The Project in a Nutshell
▶ Switzerland: Ingested the federal inventory of cultural properties of
national or regional significance.
▶ Monuments lists of several other countries have been ingested as well.

10. «Monumental» – The Web App
URL: https://tools.wmflabs.org/monumental/
Documentation: https://www.wikidata.org/wiki/Wikidata:Tools/Monumental

11. ▶ Data Import Switzerland
• Import the monuments data from the canton of Zurich and the City of
Zurich
• Import the remaining monuments data and labels from Wikipedia
monuments lists (e.g. via the WLM Monuments Database)
▶ Data Cleansing?
▶ Tools for Data Maintenance
• Set-up / create tools to monitor coverage and data completeness
• Create a tool to facilitate the annual update of the official data set and to
monitor changes in Wikidata
▶ Put the Data to Use
• In Wikipedia, Wikivoyage, etc.
To do

12. ▶ Time-Consuming Data Reconciliation for the Zurich Data Sets
• Overlaps: many objects are already in the national data set
• Group-part relationships need to be dealt with on a one-by-one basis
▶ Ontology
• Minor coordination issues with the community regarding the creation /
use of properties
Main Challenges

13. Performing Arts

14. ▶ Starting Point:
• Platform Project of Swiss Theatre Collection & Swiss Dance Archive
• Swiss Performing Arts Data Model
▶ Goal / Rationale:
• Create a worldwide inventory of performing arts productions
• Such an inventory provides considerable value added when it comes to
interlinking finding aids from various theatre archives
▶ Swiss Pilot Project:
• Ingesting a dataset with 30 years of production data of the Schauspielhaus Zürich
▶ Potential Partners:
• Swiss Archive of the Performing Arts
• Belgian and Dutch theatre archives
• Carnegie Hall
• User:Harmonia Amanda (inventory of Broadway productions)
• British Library (playbills crowdsourcing project)
• Fachinformationsdienst Darstellende Kunst, University of Frankfurt
• University Tor Vergata, Rome
• Bern University of Applied Sciences (students projects)
The Project in a Nutshell

15. Swiss Performing Arts Data Model
Coverage:
• Theatrical, musical & choreographic works (FRBR)
• Performance works, performing arts productions
• Creators, contributors, artists
• Performance roles
• Venues
• Organizations
• Theatre seasons
• Festivals, competitions, events
• Awards
• Heritage objects
• Archival collections (RiC, ISAD(G))
Technological approach / philosophy:
• RDF-based ontology with a focus on linked data
• Integration of dominant and emerging data models in
the different heritage domains (archives, libraries,
museums)
• Mapping to ontologies widely used within the LOD
community

16. Status Quo – Wikidata

17. ▶ Project framework established for Performing Arts Productions, Corporate Bodies,
Venues and Events:
• WikiProject « Performing Arts »
• WikiProject « Cultural Venues »
• WikiProject « Cultural Events »
Status Quo – Wikidata
Achievements & Current Challenges
• Performing Arts Data Model partly implemented
• Initiated an overview of existing data sources
• Data cleansing & linking is a great challenge
• Still very little performance data ingested
PLUS: synergies with existing projects in
the area of bibliographic records
(works) and authority control (persons)

18. ▶ There is plenty of relevant material, but it needs organizing and curation
▶ Structured data on Wikimedia Commons is expected to be a great enabler
Status Quo – Wikimedia Commons

19. ▶ Current examples show a great potential for the inclusion of
Wikidata-powered content in the field of the performing arts.
▶ Current initiatives may benefit from improved coordination – also
across linguistic borders.
▶ Despite many examples of how structured data is used, the data is
usually not pulled from Wikidata.
▶ Large parts of the structured data in Wikipedia related to the
performing arts is not available on Wikidata.
Status Quo – Wikipedia

20. Example: List of Productions of « Les Galas Karsenty »
(French Wikipedia)

21. Example: Infobox « Das Land des Lächelns »
(German Wikipedia)

22. Example: Infobox « Aksandr Golovin »
(Russian Wikipedia)

23. Example: Listing of the scenographic work of
Aleksandr Golovin (Russian Wikipedia)

24. Example: List of theatrical works by William
Shakespeare (German Wikipedia)

25. Example: Infobox Opéra Bastille (French Wikipedia)

26. Example: List of Artistic Directors and Well-Known
Artists at Stadttheater Bern (German Wikipedia)

27. ▶ Implementation of elements of the Swiss Performing Arts Data Model on Wikidata;
mapping between the two data models
▶ Implementation of data modelling examples on Wikidata
▶ Data ingestion (Swiss & Belgian performing arts related data, etc.)
▶ Community building
Further tasks down the road:
• Ingest structured data from Wikipedia to Wikidata
• Monitor data quality and completeness on Wikidata
• Change existing templates to pull the data directly from Wikidata; create
additional templates where they are missing
• Enhance the metadata of performing arts related media objects on Wikimedia
Commons (linking them to a performance database implemented on Wikidata)
Next Steps – Join us!

28. Synergies & Potential for Cross-pollination

29. Wikidata, Wikipedia, Wikimedia
Commons
• Complementary data (artists, works,
etc.)
• Potential for crowdsourcing / community-
sourcing certain aspects of data
maintenance
• Application of the data model in an
international context
• Visibility, exposure of performing arts
related information
Swiss Performing Arts Platform
• Plenty of performance data from
Switzerland
• Comprehensive data model for the
performing arts domain
• Plenty of know-how and source material
in the area of the performing arts
• Digital content (in the longer term, due to
copyright issues)
Areas for Cooperation
• Mutual interlinking of data & content
• Community building and outreach to further data providers
• Establishing a widely accepted data modelling practice in the area of the performing arts
• Organization of editathons and similar events

30. Thank You for Your Attention!
Contact
Beat Estermann
Bern University of Applied Sciences
beat.estermann@bfh.ch
+41 31 848 34 38