=Paper=
{{Paper
|id=Vol-1676/paper2
|storemode=property
|title=Classification of Knowledge Organization Systems with Wikidata
|pdfUrl=https://ceur-ws.org/Vol-1676/paper2.pdf
|volume=Vol-1676
|authors=Jakob Voß
|dblpUrl=https://dblp.org/rec/conf/ercimdl/Voss16
}}
==Classification of Knowledge Organization Systems with Wikidata==
https://ceur-ws.org/Vol-1676/paper2.pdf
Classification of Knowledge Organization
Systems with Wikidata
Jakob Voß
Verbundzentrale des GBV (VZG), Göttingen, Germany
jakob.voss@gbv.de
Abstract. This paper presents a crowd-sourced classification of knowl-
edge organization systems based on open knowledge base Wikidata. The
focus is less on the current result in its rather preliminary form but on the
environment and process of categorization in Wikidata and the extrac-
tion of KOS from the collaborative database. Benefits and disadvantages
are summarized and discussed for application to knowledge organization
of other subject areas with Wikidata.
Keywords: Knowledge Organization Systems · Wikidata
1 Classification of Knowledge Organization Systems
Since introduction of the term knowledge organization system (KOS), several
attempts have been made to classify KOSs by types such as glossaries, the-
sauri, classifications, and ontologies [6, 4, 11, 2, 10]. The set of KOS types and
each of their extent varies depending on both domain or context of application
(for instance different academic fields) and criteria of classification (for instance
classification by purpose or structure). In many cases, KOS types are arranged
according to the degree of controls, ranging from simple term lists to complex
ontologies.
The most elaborated classification of KOS types in the field of knowledge orga-
nization is the the NKOS KOS Types Vocabulary [3]. It was developed by the
DCMI NKOS Task Group with definitions mainly based on the KOS Taxon-
omy by Zeng and Hodge [17] and on ISO 25964 [7]. The KOS types vocabulary
differentiates between 14 types of KOS (categorization scheme, classification
scheme, dictionary, gazetteer, glossary, list, name authority list, ontology, se-
mantic network, subject heading scheme, synonym ring, taxonomy, terminology,
and thesaurus). One of the rare applications of these KOS types is their use in
the Basel Register of Thesauri, Ontologies & Classifications (BARTOC)1 where
more then 1.800 KOSs have been classified so far [8].
1
http://bartoc.org/
2 Wikidata
Wikidata2 is the most recent project of the Wikimedia Foundation. In short, it
is a collaboratively edited, free knowledge database that can be read and edited
by both humans and machines. A good overview is given by two of Wikidata’s
main creators Vrandečić and Krötzsch [16]. The primary goals of the project are:
1. Centralize links between Wikipedia language editions and other Wikimedia
project sites. For instance all Wikipedia articles about “encyclopedia” (in
any language) are linked to one Wikidata item with identifier Q5292. These
so called sitelinks and other data about the concept known as “encyclopedia”
can be looked up at https://www.wikidata.org/wiki/Q5292.3
2. Centralize Infoboxes. More and more manually edited infoboxes (tables with
basic, factual information about a topic) are being extended to use Wikidata
as their database backend, so the displayed information will be the same in
all Wikipedia editions.
3. Provide an interface for rich queries. The content of Wikidata can be queried
via a public SPARQL interface at https://query.wikidata.org/ (see figure 1
for an example). Query results are planned to be integrated into Wikipedia
and other projects as lists, tables, maps and other forms.
The data model of Wikidata is neither relational nor based on RDF (although
mappings to RDF exists) but it reflects the strategy of Wikidata to store state-
ments instead of facts. Each statement should be sourced by references and
contradicting statements are not forbidden on purpose. Statements can further
be controlled by qualifiers, such as domain and date of validity, eventually sup-
porting n-ary relations between Wikidata items. The Wikidata ontology consists
of Wikidata properties, which are defined by community consensus. For instance
P571 identifies the property “inception” to state the date when something was
created or founded. Labels and scope notes can be edited independently from
statements with support of synonyms and homonyms.
3 Knowledge Organization Systems in Wikidata
To a large degree, Wikidata contains mappings to other KOSs: links between
Wikidata items to VIAF and Geonames are among the most used Wikidata
properties with around 100.000 Wikidata each4 and at least 1051 of 2490 Wiki-
data properties5 refer to external identifier systems of other databases.6 With
2
https://www.wikidata.org/
3
In RDF this URL corresponds to the URI http://www.wikidata.org/entity/Q5292.
4
https://www.wikidata.org/wiki/Wikidata:Database_reports/List_of_properties
5
Measured at https://www.wikidata.org/wiki/Special:ListProperties, 2016-05-24
6
See also Voß et al. [15] for a German introduction to authority data in Wikidata.
uniquely identified records about virtually anything, Wikidata can also be seen
as a KOS in its own right, so it is included in BARTOC.7 For the scope of this
study, Wikidata items about KOS types and KOS instances are of special inter-
est. KOS instances are Wikidata items linked to KOS type items with property
“instance of” (P31)“. For instance the Dewey Decimal Classification (Q48460) is
an instance of both a”library classification” (Q48473) and a “universal classi-
fication scheme” (Q24243801). Both are connected to the item “classification
scheme” (Q5962346) with property “subclass of” (P279).
Despite their obvious use for knowledge representation and classification, the
subclass and instance properties have no special role in Wikidata. Instead they
can freely be used to connect any Wikidata items, only constrained by human
intervention of other editors and, hopefully, community consensus in common
sense. The lack of stricter rules on use of subclass and instance properties in
Wikidata has led to criticism among researchers that try to use it as a formal
ontology [1, 12]. Nevertheless, Wikidata can successfully be queried for a hierar-
chical list of transitive subclasses of “knowledge organization system” (Q6423319)
and additional numbers for each class (figure 1).
SELECT ?item ?itemLabel ?broader ?parents ?size ?sites {
{
# number of additional superclasses
SELECT ?item (count(distinct ?parent)-1 as ?parents) {
?item wdt:P279* wd:Q6423319
OPTIONAL { ?item wdt:P279 ?parent }
} GROUP BY ?item
} {
# number of instances
SELECT ?item (count(distinct ?element) as ?size) {
?item wdt:P279* wd:Q6423319
OPTIONAL { ?element wdt:P31 ?item }
} GROUP BY ?item
} {
# number of sitelinks
SELECT ?item (count(distinct ?site) as ?sites) {
?item wdt:P279* wd:Q6423319
OPTIONAL { ?site schema:about ?item }
} GROUP BY ?item
}
OPTIONAL { ?item wdt:P279 ?broader }
SERVICE wikibase:label { bd:serviceParam wikibase:language "en" }
}
Fig. 1. SPARQL query to extract KOS classification data from Wikidata
7
http://bartoc.org/en/node/1940
4 A KOS classification extracted from Wikidata
The following classification of KOS types was extracted from Wikidata via
SPARQL (figure 1). The command line tool ‘wdtaxonomy’, created especially
to extract and display taxonomies, proved to be hugely useful for analysis [14].
The outcome, at the time of its creation at August 23rd 2016, contains 189
Wikidata items of KOS types, grouped in a multi-hierarchy. Classes within one
level are sorted by their Wikidata identifier, reflecting the relative time when
they were added to the database. Items with multiple superclasses within the
KOS type hierarchy are shown in italics at the their second occurrence, for in-
stance a ‘plant taxonomy’ is both a ‘biological classification’ and a ‘taxonomy’.
Superclasses from other parts of Wikidata are indicated with upwards point-
ing arrows (↑), for instance ‘datamodel’ is also subclass of ‘model’ and ‘data set’.
The numbers right to each class label indicate the current number of instances in
Wikidata (if there are any), and after a small plus sign the number of Wikipedia
articles or other Wikimedia projects sites linked with the entry (sitelinks). For
instance three Wikidata items are marked as instance of ‘semantic network‘ and
twenty Wikipedia editions include an article about semantic networks (3+20).
knowledge organization system ↑↑↑ 2+3 · · defining vocabulary ↑ +1
· encyclopedia ↑ 299+183 · · multi-field dictionary +1
· · internet encyclopedia ↑ 29+27 · authority control 36+42
· · encyclopedic dictionary 42+7 · mind map ↑ +46
· · · biographical encyclopedia ↑ 59+8 · ontology 26+31
· · universal encyclopedia 1+2 · · metamodel 6+11
· · hypertext encyclopedia 6+1 · · upper ontology 5+2
· dictionary ↑ 182+126 · · process ontology +1
· · lexicon ↑ 4+38 · · soft ontology +1
· · lexicographic thesaurus 7+48 · · weak ontology +1
· · orthographic dictionary +7 · concept map ↑ +26
· · etymological dictionary 1+13 · semantic network ↑ 3+20
· · glossary ↑ 13+35 · data model ↑↑ 5+17
· · visual dictionary 1+6 · · database model 3+11
· · explanatory dictionary 4+6 · · data dictionary ↑ +15
· · · explanatory combinatorial dictionary +2 · · data schema +3
· · · monolingual learner’s dictionary +2 · · · XML Schema 1+28
· · encyclopedic dictionary · · · database schema +13
· · reverse dictionary +9 · · · · database normalisation 3+32
· · machine-readable dictionary +10 · · · · star schema +12
· · · online dictionary 9+6 · · · logical data model +2
· · · · Wiktionary language edition ↑↑ 7 · · information model ↑ +8
· · rime dictionary 4+7 · · · database schema
· · rhyming dictionary +11 · · domain model +6
· · conceptual dictionary +6 · · conceptual schema +6
· · bilingual dictionary 2+13 · · canonical model +1
· · slang dictionary 2+3 · · GIS data model +1
· · idiom dictionary +5 · · · ArcGIS data model +1
· · Anagram dictionary +1 · · generic data model +1
· · author dictionary +1 · · semantic data model +1
· · language for specific purposes dictionary +1 · · standard data model +2
· · medical dictionary 1+2 · · White pages schema +1
· · phonetic dictionary +1 · · logical data model
· · picture dictionary +2 · conceptual graph ↑ +6
· · single-field dictionary +1 · controlled vocabulary 10+8
· · specialized dictionary +2 · · thesaurus 11+5
· · · sub-field dictionary +1 · synonym ring +5
· numbering scheme +3 · · · · zoological nomenclature 2+2
· catalog ↑↑ 124+11 · · library classification 26+22
· · authority control · · decimal classification 6+1
· · directory 4+43 · · faceted classification 1+11
· · telephone directory ↑ 1+28 · · universal classification scheme 12
· · civil registry ↑ 2+25 · · specialized classification scheme 10
· · · birth registry ↑ 1 · · · biological classification 10+112
· · web directory ↑ 11+30 · · · · plant taxonomy
· · address book ↑ 1+11 · · · · syntaxonomy +9
· · astronomical catalog 26+26 · · · · taxonomy of Chordata +1
· · · star catalogue 19+31 · · · · · taxonomic classification of Passeriformes +1
· · · catalogue of galaxies 2+1 · · · · taxonomy of birds 1+2
· · land registration 4+25 · · · · · taxonomic classification of Passeriformes
· · · Ōtabumi +4 · · · linguistic typology 3+42
· · exhibition catalogue 7+5 · · · climate classification 1+14
· · inventory 2+36 · · · · genetic climate classification 1+1
· · · heritage register 75+1 · · · · effective climate classification 2+1
· · · · buildings at risk register ↑ +1 · · · classification of wine 1+7
· · business directory +4 · · · chemical classification 3+8
· · gazetteer ↑ 3+18 · · · video game content rating system ↑ 8+17
· · urbarium 2+18 · · · classification in sports 88+3
· · business register 1+1 · · · · age category in soccer +1
· · · company register 9+13 · · · · olympic sailing class ↑ 4+6
· · bibliography 610+6 · · · · equestrian sports classification +1
· · · discography 5543+35 · · · · weight class 3+7
· · · library catalog ↑ 19+24 · · · · · wrestling weight classes +2
· · · · union catalog 15+7 · · · · · lightweight class
· · · catalogue raisonné ↑ 48+10 · · · · age category in athletics 5
· · · filmography 799+10 · · · · competition class 84
· · · · videography 19 · · · · · glider competition class 9 3
+
· · · subject bibliography +1 · · · · · group 3+4
· · · playlist ↑ +14 · · · · · · rally group 1
· · · national bibliography 2+2 · · · musical instrument classification 1+11
· · · regional bibliography 10+1 · · · medical classification 8 3
+
· · · bibliographic index +4 · · · corporate taxonomy +1
· · · · bibliographic database ↑ 41+13 · · · economic taxonomy 2+2
· · · annotated bibliography +1 · · · · job classification system 7+1
· · · catalogue of classical compositions 23+1 · · · · patent classification 4+2
· · · metabibliography +1 · · · · industry classification 18+3
· · · · list of music references 1+1 · · · · product classification +1
· · medal table 132+2 · · · military taxonomy +2
· · · Olympic medal table 55+3 · · · · military casualty classification 6
· · auction catalog +3 · · · safety taxonomy +1
· · product catalog +4 · · · astronomy classification 1
· · records catalog +1 · · · · stellar classification 25+59
· · thematic catalog 9+7 · · · · asteroid classification 3
· · nuancier 1+2 · · · · · asteroid family 82+25
· · · RAL color system ↑ +16 · · · · · asteroid spectral type 19 22
+
· · music catalog 2+1 · · · · · minor-planet group 1+7
· · population register ↑ +1 · terminology 3+1
· · recording catalog +1 · · nomenclature 7+25
· · index ↑ 4 · · · biological nomenclature 12+12
· · terminology registry 2 · · · · phylogenetic nomenclature +10
· · · metadata registry + 4 · · · · botanical nomenclature
· conceptual model ↑ 3 14
+ · · · · zoological nomenclature
· · systems architecture 1 9
+ · · · nosography 1+3
· · hierarchical temporal memory +5 · · · chemical nomenclature 3+27
· · conceptual model (computer science) +1 · · · · IUPAC chemical nomenclature 3+29
· · domain model
· · conceptual schema
· · semantic data model
· classification scheme 61+23
· · taxonomy 9+63
· · · numerical taxonomy +5 Summary
· · · taxonomy 6+40 number of classes: 189 (100%)
· · · · plant taxonomy +21 with instance: 116 (61%)
· · · · · Taxonomy of Narcissus +1 with sitelink: 175 (92%)
· · · · botanical nomenclature 1+9
5 Discussion
The classification of KOS types extracted from Wikidata is detailed but obvi-
ously sketchy in its current form. The system was even more incomplete before
large parts of it had been edited by the author, mainly to adjust or add missing
English labels and items without any instance or subclass statement. A couple
of items were also moved or merged after notification and discussion with the
Wikidata community.8 Instead of criticizing usage limitations of Wikidata class
hierarchies such as Spitz et al. [12], or suggesting methods to better spot clas-
sification inconsistencies such as Brasileiro et al. [1], peculiarities of knowledge
organization systems based on Wikidata shall be highlighted in the following.
First of all, classes and instances are more or less given by existence or non-
existence of Wikidata items with sitelinks: only 14 of 189 classes in the clas-
sification above don’t have at least one corresponding Wikipedia article. To
some degree new Wikidata items can also be added without sitelink, but this is
controversial at least for abstract concepts which have no obvious unique iden-
tification.9 KOS types therefore usually require some Wikipedia article before
inclusion. The strong connection to Wikipedia also forbids removal, reinterpre-
tation or merging of concepts that don’t easily fit into a classification, unless
one engages in editing Wikipedias. Anyway, KOS derived from Wikidata are
build by a bottom-up approach from general encyclopedic concepts. As scope
and definition of a Wikidata item vary between Wikipedia language editions,
the concepts are fuzzy to some degree. For instance at the moment there are two
items for classification as process and classification as result but only one item for
both metamodelling and metamodel.10 One should not try to solve all of these
cases in structured data, as Graham [5] warned about application of Wikidata:
“We just need to ensure that we aren’t seduced into codifying, categorizing, and
structuring in cases when we should be describing the inherent messiness of a
situation.” It has already been shown that the category system of Wikipedia is
more a thesaurus than a classification [13]. KOS extraction from Wikidata may
also result in less strict hierarchies without strong formal logic. Participation
in Wikidata differs from collaborative ontology engineering [9]. Although the
database is often referred to as knowledge base, its practical purpose in many
ways is more knowledge organization than knowledge representation.
The number of sitelinks can be used as indicator how established or widely
known a concept is. The number of instances more depends on which KOS
instances are relevant for inclusion in Wikimedia projects and have been classified
in Wikidata at all. Despite this bias, instances are very helpful to judge the
application of a concept for classification. Both new Wikidata instances and new
sitelinks are added to KOS types virtually every day. The benefit of this dynamic
growth is better coverage of multiple views and domains, so most KOS extracted
8
The question about ‘taxonomy’ vs. ‘biological classification’ could not be resolved.
9
See https://www.wikidata.org/wiki/Wikidata:Notability
10
“classifying” (Q13582682), “classification” (Q5962346), and “metamodel” (Q1925081)
from Wikidata include aspects of a universal classification and less suffer from
opinionated knowledge organization. The downside of this crowd-sourcing is lack
of a final consensus. Therefore extraction of KOS from Wikidata is an iterative
process that requires continuing review and contribution to Wikidata (figure 2).
extraction
Wikipedias Wikidata KOS analysis
discussion discussion modification
Fig. 2. Iterative process of KOS extraction from Wikidata
6 Summary and outlook
This paper introduced the extraction of knowledge organization systems from
Wikidata exemplified by a classification of KOS types. With 181 classes the
result is probably the most detailled classification of KOS types so far. Before
further evaluation and cleanup, however, it can only serve as starting point.
The strong grounding in Wikipedia is both benefit and challenge. The system
is more build bottom-up from instances instead of top-down from theoretical
properties like existing classifications and typologies. Further improvement of the
particular classification requires involvement of both the Wikidata community
and domain experts in knowledge organization. For instance one could express
different characteristic of division as Wikidata qualifiers.11 It is also not sure
yet whether the hierarchical structures extracted from Wikidata can better be
expressed by other types of KOS such as multi-level models [1] or thesauri [13].
Further work on the KOS classification includes alignment with the NKOS KOS
Types Vocabulary [3]. KOS instances have been classified in both Wikidata and
BARTOC [8], connected via Wikidata property “BARTOC ID” (P2689). More
elaborated KOS extraction should also incorporate Wikidata qualifiers. Existing
tools such as SQID Wikidata Browser12 could further be extended to better
support management of KOSs extracted from Wikidata.
References
[1] Freddy Brasileiro et al. “Applying a Multi Level Modeling Theory to As-
sess Taxonomic Hierarchies in Wikidata”. In: Proceedings of WWW 2016
Companion. 2016. doi: 10.1145/2872518.2891117.
11
This has already been started for domain-specific subtypes of classification schemes.
12
http://tools.wmflabs.org/sqid/
[2] Eva Bratková and Helena Kučerová. “Knowledge Organization Systems
and Their Typology”. In: Revue of Librarianship 25.2 (2014), pp. 1–25.
url: http://full.nkp.cz/nkkr/knihovna142_suppl/1402sup01.htm.
[3] Dublin Core Metadata Initiative. NKOS Task Group. KOS Types Vocabu-
lary. Oct. 2015. url: http://wiki.dublincore.org/index.php/NKOS%5C_
Vocabularies.
[4] Alan Gilchrist. “Thesauri, taxonomies and ontologies – an etymological
note”. In: Journal of documentation 1 (2003), pp. 7–18. doi: 10 . 1108 /
00220410310457984.
[5] Mark Graham. “The Problem With Wikidata”. In: The Atlantic (2012).
url: http : / / www . theatlantic . com / technology / archive / 2012 / 04 / the -
problem-with-wikidata/255564/.
[6] Gail Hodge. Systems of knowledge organization for digital libraries: beyond
traditional authority files. Digital Library Federation, 2000.
[7] ISO 25964 Information and documentation – Thesauri and interoperability
with other vocabularies. ISO standard. 2013.
[8] Andreas Ledl and Jakob Voß. “Describing Knowledge Organization Sys-
tems in BARTOC and JSKOS”. In: Proceedings of International Confer-
ence on Terminology and Knowledge Engineering. 2016, pp. 168–178. url:
http://hdl.handle.net/10760/29366.
[9] Claudia Müller-Birn et al. “Peer-production system or collaborative on-
tology engineering effort: what is Wikidata?” In: OpenSym. Ed. by Dirk
Riehle. ACM, 2015, 20:1–20:10. doi: 10.1145/2788993.2789836.
[10] Vreda Pieterse and Derrick G. Kourie. “Lists, Taxonomies, Lattices, The-
sauri and Ontologies: Paving a Pathway Through a Terminological Jungle”.
In: Knowledge Organization 41.3 (2014), pp. 217–229.
[11] Renato Rocha Souza, Douglas Tudhope, and Maurício Barcellos Almeida.
The KOS spectra: a tentative typology of Knowledge Organization Systems.
2010. url: http://mba.eci.ufmg.br/downloads/ISKO%5C%20Rome%
5C%202010%5C%20submitted.pdf.
[12] Andreas Spitz et al. “State of the Union: A Data Consumer’s Perspective
on Wikidata and Its Properties for the Classification and Resolution of
Entities”. In: Proceedings of ICWSM 2016. 2016.
[13] Jakob Voß. Collaborative thesaurus tagging the Wikipedia way. Tech. rep.
2006. url: http://arxiv.org/abs/cs/0604036.
[14] Jakob Voß. wikidata-taxonomy 0.2.7. 2016. doi: 10 . 5281 / zenodo . 60708.
url: https://github.com/nichtich/wikidata-taxonomy.
[15] Jakob Voß et al. Normdaten in Wikidata. 2014. isbn: 978-1-291-85658-3.
url: https://hshdb.github.io/normdaten-in-wikidata/.
[16] Denny Vrandečić and Markus Krötzsch. “Wikidata: A Free Collaborative
Knowledgebase”. In: Communications of the ACM 57.10 (2014), pp. 78–85.
doi: 10.1145/2629489.
[17] Marcia Lei Zeng and Gail Hodge. Taxonomy of Knowledge Organization
Sources/Systems. 2000. url: http://nkos.slis.kent.edu/KOS_taxonomy.
htm.