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Cross domain knowledge discovery, complex system theory and semantic web Aida Slavic, Christophe Gueret, Andrea Scharnhorst Why Otlet? Presentation at the First Annual KnowEscape Conference, Nov 18-20, 2013, Aalto University, Espoo Finland
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Cross domain knowledge discovery, complex system theory and semantic web

Dec 13, 2014

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Cross domain knowledge discovery, complex system theory and semantic web - or - Why Otlet?
Aida Slavic, Christophe Gueret, Andrea Scharnhorst
Presentation at the First Annual KnowEscape Conference,
Nov 18-20, 2013, Aalto University, Espoo Finland
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Page 1: Cross domain knowledge discovery, complex system theory and semantic web

Cross domain knowledge discovery, complex system theory and semantic webAida Slavic, Christophe Gueret, Andrea Scharnhorst

Why Otlet?Presentation at the First Annual KnowEscape Conference, Nov 18-20, 2013, Aalto University, Espoo Finland

Page 2: Cross domain knowledge discovery, complex system theory and semantic web

Paul Otlet - Mundaneum

Bibliographical Institute

Ordering the knowledge of the world

Universal Decimal Classification

Palais Mondial

Picture of the Mundaneum. Taken by Andrea Scharnhorst Paul Otlet. Picture © Mundaneum

Page 3: Cross domain knowledge discovery, complex system theory and semantic web

Classification

All pictures © Mundaneum

Page 4: Cross domain knowledge discovery, complex system theory and semantic web

The scientific process

All pictures © Mundaneum

Page 5: Cross domain knowledge discovery, complex system theory and semantic web

Workplaces - workspaces

All pictures © Mundaneum

Page 6: Cross domain knowledge discovery, complex system theory and semantic web

Encyclopedia Universalis Mundaneum – a Visual

Encyclopedia

All pictures © Mundaneum

Page 7: Cross domain knowledge discovery, complex system theory and semantic web

The What, How and Why together

All pictures © Mundaneum

Page 8: Cross domain knowledge discovery, complex system theory and semantic web

Begreifen & Vermitteln

All pictures © Mundaneum

Page 9: Cross domain knowledge discovery, complex system theory and semantic web

Otlet - VisionsEvery information scientist (= We all are IS says Martin White) should once in her/his life visit the Mundaneum

Without history we are condemned to eternal repetition (Mircea Eliade, pre-historic societies live in eternal return).

Visual language experiments, exhibitions, objects

Retrieval service (see R. Boyd, Proceedings Classifications & Visualizations 2013) – entrepreneur

The UDC as part of Otlet’s heritage!

Page 10: Cross domain knowledge discovery, complex system theory and semantic web

Designing interfaces to collections –

visual enhanced browsing

All datasets in EASY - the digital research data archive at DANS at one glance. www.drasticdata.nl

Page 11: Cross domain knowledge discovery, complex system theory and semantic web

Steps towards visual enhanced/facetted

browsing

AH CS M&P SoSc

Page 12: Cross domain knowledge discovery, complex system theory and semantic web

Translated in over 40 languages, used in over 130 countries:

bibliographies and bibliographic databases

libraries (also some museums, archives)

digital collections, web portals, alerting services

Annually updated and distributed as a file: 18 versions/‘editions’ since 1992

1992: 60,000 classes - 2011: 69,000 classes

10,000 classes cancelled

19,000 new classes added

Back to UDC – Facts and Figures

Page 13: Cross domain knowledge discovery, complex system theory and semantic web

Understanding the evolution of Knowledge

Organization Systems

More research needed – various KOSACM – Veslava OsinskaMESH – Alexander Petersen/Orion PennerISI Classifications – Sandor SoosWikipedia – Janos Kertesz, Krzysztof Suchecki….

Page 14: Cross domain knowledge discovery, complex system theory and semantic web

Cross-language linking of concepts, i.e. managing link between concepts and language

=512.16 Jižní skupina turkických jazyků

Южная группа тюркских языков [Russian]

तु�र्की� भा�षा�ओं र्की� दक्षि�णी समू�ह [Hindi]

Թուրքական լեզուների հարավային խումբ [Armenian]

Νότια ομάδα των Τουρκικών γλωσσών [Greek]

突厥南部语 [Chinese]

দক্ষি�ণস্থ শ্রে�ক্ষিণর তু ক্ষি�� ভা�ষা�সমূ�হ [Bengali]

チュルク語南部群 [Japanese]

ಟರ್ಕಿ� ಭಾ�ಷೆಗಳ ದರ್ಕಿಣ ಭಾ�ಗದ ಸಮೂ�ಹ [Kannada]

Hierarchies: graphic knowledge presentation, browsing knowledge space (supporting interactive user behaviour)

Linking concepts ‘fish’ in zoology, in sport, in cooking, in food industry, in animal

husbandry

UDC Applications: Scope and Potentials

Page 15: Cross domain knowledge discovery, complex system theory and semantic web

Sharks

Natural SciencesBiology

AnimalsVertebrata

Pisces (Fishes)Elasmobranchii

Sharks

Arts. Recreation. Entertainment. SportFilm. Cinema (motion pictures)

Film genresDocumentary films

Documentaries about sharks

Social SciencesEconomic science

Economic sectorsTourism

Adventure tourismSwimming with sharks

Arts. Recreation. Entertainment. SportSport

Sport fishingSea fishing

Shark fishing

Applied SciencesAgriculture

FishingFishing for deep-sea species

Shark fishing

Applied SciencesIndustries

Leather industryFish skin

Sharkskin

Linking concepts across knowledge

Page 16: Cross domain knowledge discovery, complex system theory and semantic web

Two requirements:

• publishing classification: open access to classification vocabulary for m2m processing

• publishing library catalogues: open access to collections and collections’ metadata for m2m processing

Classifications can be used on the Web to:Improve and enrich semantics and access points in the retrieval of information

Enable information discovery across collections and languages

KOS and Libraries in the web of knowledge

Page 17: Cross domain knowledge discovery, complex system theory and semantic web

Linked Open Data – Big Data

Page 18: Cross domain knowledge discovery, complex system theory and semantic web

See also: Tutorial Linked Data: stap voor stap. Paul Hermans, http://www.den.nl/nieuws/bericht/3075/

What are Linked (Open) Data?

Page 19: Cross domain knowledge discovery, complex system theory and semantic web

What is the clue?

Peter Richmond as chair of MP0801

Peter Richmond publishing with Sorin Solomon

Peter Richmond using EI/M0HBL

Ah! This is one person!URI … /this is a person/ this is this person

Designed for machines by humans!Occupied by machines guided by humans!Retrievable by (some) humans! Information/Data in databases live urban

(some say in ghettos)Information/Data in the semantic web livein the wild – self-organized, endangered

Science+EngineeringData models + standards,Web technologiesAlgorithms

Page 20: Cross domain knowledge discovery, complex system theory and semantic web

connecting collections of data by programs (machine-to-machine)

XML/RDF presentation relies on unique identification of resources (URI) pointing to one another

COLLECTION CATALOGUES

XML/RDF export

UDC

XML/RDF export

KOS and Libraries stream into the LOD cloud – what is the

problem?

Page 21: Cross domain knowledge discovery, complex system theory and semantic web

UDC as LODThe first stage contains the following UDC data:

UDC number (notation) skos:notationclass identifier (URI) skos:Conceptbroader class (URI) skos:broadercaption skos:prefLabelincluding note skos:noteapplication note skos:notescope note skos:scopeNoteexamples skos:examplesee also reference skos:related

Page 22: Cross domain knowledge discovery, complex system theory and semantic web

example of the UDC class =162.3 Czech [Common auxiliary of language]

For (machine) eyes only! Who said machine make life

easier?

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Enable automatic redirection on the Web from cancelled UDC numbers. UDC MRF database holds data as follows:

SKOS does not offer solution for presenting this kind of data at the moment

But in RDF, it is possible to use other models in combination with SKOS…

Dublin Core for versioning links the two classes using properties in the term namespace : isReplacedby; replaces

UDC CLASS NUMBER: 22DESCRIPTION: The Bible. Holy scriptureREPLACED BY: 26-23 Judaism – Scriptures

27-23 Christianity - Scriptures

Issues - I

Page 24: Cross domain knowledge discovery, complex system theory and semantic web

37:004 Application of computers in education32:37 Relationships between politics and education

Library catalogues or authority data shared on the web contain many pre-combined number and when published as linked data these numbers may have their own URI

How to link representations between notations from the original schemes and complex subject expressions developed at the point of indexing?

Complex UDC expressions appear in the process of use and may not appear in the original scheme

Issues - 2

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Issues - 3Versions of UDC

Can be controlled in the editions

But what about the actual use in libraries – here UDC numbers don’t come with a year when they have been assigned

Updates of UDC – how to give the web a memory

Provenance

Memento

URI …/last/….

Page 26: Cross domain knowledge discovery, complex system theory and semantic web

SummaryHeritage of Otlet and other Information/Documentation pioneers -> Mundaneum 2015 Exhibit Knowledge Maps

Self-organized knowledge creation and KOS belong together – both are an intriguing object for study – best studied combined

Transition to Big Data in form of Linked (Open) Data requires careful and inventive preparations

There is a long way from visionary drawings to useful visual navigation – but to start the journey is worth-while and needed.

Page 27: Cross domain knowledge discovery, complex system theory and semantic web

Referenceshttp://en.wikipedia.org/wiki/Mircea_Eliade

Eliade, M. (1974). The myth of the eternal return or, Cosmos and history: Trans. from the French by Willard R. Trask. Princeton: Princeton University Press.

• Knowledge Space Lab publications on Wikipedia and UDC – see http://arxiv.org/find/all/1/all:+AND+akdag+udc/0/1/0/all/0/1 and http://arxiv.org/abs/1203.0788

• http://scimaps.org/maps/map/design_vs_emergence__127/

• http://udcc.org/ and http://udcc.org/index.php/site/page?view=bib

• http://www.mundaneum.org/