1. Semantics for Archives & Records Management at OECD
the Semantically Enriched Archivist
Semantics for Archives & Records Management at OECD
45th ICA / SIO Conference, Brussels, 22 May 2019

2. As archivists we often face issues…
Performance: (…by the way, it took the artist 18 hours to find the needle…)

3. because information without context…
…is like a fish without water

4. Solution = Context + Structure Well, that’s exactly the Archivist’s bread and butter,

5. …the Fundamentals of archival description…
Provenance
So, if we embed the:
Principle of Provenance
Principle of Structure
Business Context
Series
Dossier
as metadata in…
Content Type
Status

6. a set of Corporate Taxonomies, we can use them…

7. to semantically empower our search & discovery !

8. Yes, but what about the backlog ?????

9. Manual indexing is no longer an option…

10. We need robots to help us. But is that possible?

11. Yes!
How ? Through Semantic Analysis

12. What do the semantic robots do?

13. Semantic Enrichment = Structure the Unstructured

14. How do we develop these robots ?
We develop on a set of test documents (Test corpus)
We debug to correct patterns and disambiguate
We test on complete corpus
and we put in production using
Web Services

15. Some OECD Archival Examples
Problem 1: We don’t know what type of document it is! Document Type Classification Problem 2: We don’t have resources to index scanned documents manually! (OCR-ed) Document Indexing Problem 3: Full text search gives too many results! Topics and Geographical Areas Classification

16. Solution1 Document Type Classification
Is this document a Report, an Agenda, an Invoice ?
Quality : 95 % Precision – 85 % Recall

17. Solution 2 (OCR-ed) Document Indexing

18. (OCR-ed) Document Indexing …
Type
Precision
Description
95.05
Record Date
86.17
Original Security
87.13
Cote Exclusion
85.15
OCR Quality %
High
79.21
Medium
14.85
Low
5.94
Total
100.00
Overall quality is remarkably good BUT….
100% is not possible
And OCR can be a challenge…

19. OCR = Problems We can normalise dates But titles are more difficult:
(in French, lionceau = lion cub…)

20. BUT…
Our biggest issue is:
The « COLLECTION »
Stamp

21. Solution 3 Topics and Geographical Areas Classification
Identify the 15 Best Topics and Geographical areas using the Central OECD Taxonomies

22. Topics and Geographical Areas Classification
Works remarkably well…. Even on OCR-ed documents!
Cartridge V
Number of Validations
Overall Precision
Overall Recall
Overall F-Measure
257
434136
99.4
98.6
99.0
279
363149
99.7
98.0
98.9
529
439726
98.2
Total

23. How do we use all these Metadata ?

24. OECD Taxonomies and Ontologies

25. NO !

26. Taxonomies and Ontologies

27. O.N.E Sight – OECD Semantic Discovery Interface

28. Architecture
Semantic Layer
Data hub

29. Multi-view annotation graphs
We use several semantic robots,
based on several different taxonomies
(generic, innovation-oriented, etc…)
We tag a same resource in different ways
We can see a same resource in context from different « semantic » viewpoints

30. The OECD Semantic Timeline
2013 Launch Call for Tender
2014 Taxonomy & Document Type Analysis
2015
OECD.Records Enrichment
2017 OCR-ed Document
Semantic Analysis
2018
O.N.E Sight Launch

31. Knowledge Gardeners Conclusion Semantics are:
Indispensable for our profession
True enablers for Knowledge Discovery
By becoming Semantically Enriched
Archivists, Librarians or Information Scientists
we really have become :
Knowledge Gardeners