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Managing Provenance and Versioning for an (Evolving) Dictionary in Linked Data Format

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The English-Xhosa Dictionary for Nurses is a unidirectional dictionary with English and isiXhosa as the language pair, published in 1935 and recently converted to Linguistic Linked Data. Using the Ontolex-Lemon model, an ontological framework was created, where the purpose was to present each lexical entry as "historically dynamic" instead of "ontologically static" (Veltman, 2006:6, cited in Rafferty, 2016:5), therefore the provenance information and generation of linked data for an ontological framework with instances constantly evolving was given particular attention. The output is a framework which provides guidelines for similar applications regarding URI patterns, provenance, versioning, and the generation of RDF data.
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Managing Provenance and Versioning for an (Evolving) Dictionary in Linked
Data Format
Frances Gillis-Webber1
1University of Cape Town, Woolsack Drive, Rondebosch, 7701, South Africa
fran@fynbosch.com
Abstract
The English-Xhosa Dictionary for Nurses is a unidirectional dictionary with English and isiXhosa as the language pair, published in
1935 and recently converted to Linguistic Linked Data. Using the Ontolex-Lemon model, an ontological framework was created,
where the purpose was to present each lexical entry as “historically dynamic” instead of “ontologically static” (Veltman, 2006:6, cited
in Rafferty, 2016:5), therefore the provenance information and generation of linked data for an ontological framework with instances
constantly evolving was given particular attention. The output is a framework which provides guidelines for similar applications
regarding URI patterns, provenance, versioning, and the generation of RDF data.
Keywords: provenance, versioning, multilingualism, lexicography, linked data, ontolex-lemon
1. Introduction
The English-Xhosa Dictionary for Nurses (EXDN) is a
bilingual dictionary of medical terms, authored by Neil
MacVicar, a medical doctor, in collaboration with
isiXhosa-speaking nurses. It was the second edition
published by Lovedale Press, a South African publisher,
in 1935, and as a literary work published in South Africa,
it falls under the jurisdiction of the Copyright Act of
South Africa, and is now in the public domain, free from
any restriction. EXDN is unidirectional; the language pair
is English and isiXhosa, with English as the source and
isiXhosa the target (Gouws & Prinsloo, 2005; Zgusta,
1971). IsiXhosa (referred here by its endonym) is an
indigenous Bantu language from the Nguni language
group (S40 in Guthrie’s classification) and is an official
language of South Africa (Doke, 1954; Subfamily:
Nguni (S.40)”, n.d.). Despite it being spoken in South
Africa by a large percentage of the population (16.0%
counted in the 2011 Census speak it as their L1), it has
minority status only (Statistics South Africa, 2012).
Other official South African languages in the Bantu
language family (referred hereon as African languages)
are: isiNdebele, isiZulu, Sesotho, Sesotho sa Leboa,
Setswana, SiSwati, Tshivena, and Xitsonga. In
comparison to English, there are limited language
resources (LRs) available for these languages, and this,
combined with the socio-economic constraints of the
speakers, renders these languages under-resourced
(Pretorius, 2014; “What is a …”, n.d.). Despite English
being an ex-colonial language in South Africa, with L1
speakers numbering 9.6%, it is a lingua frança with high
status, associated with both economic and political power
in the country (Ngcobo, 2010; Statistics South Africa,
2012). The African languages listed above, although
spoken by the majority, are minority languages and
through language shift and death, are at risk of becoming
endangered (Pretorius, 2014; Ngcobo, 2010).
In 2009, the first Human Language Technology Audit was
conducted (the second audit is currently underway at time
of writing (Wilken, personal communication 2017, Dec
12)), with Grover, van Huyssteen and Pretorius
identifying the following as issues:
“the lack of language resources, limited availability of
and access to existing LRs, [and] quality of LRs”
which hamper the development of new LRs for under-
resourced languages (2011, cited in Pretorius, 2014).
Although EXDN was published more than seventy-five
years ago, as a LR for an under-resourced language, its
content is still valuable. Linked Data is a simple data
model with an interoperable format and by publishing
lexicographic resources, particularly lesser-known
resources such as EXDN, in Linked Data, it enables the
“aggregation and integration of linguistic resources”,
which can serve as an aid for the future development of
new and existing LRs (Gracia, 2017).
Using the Ontolex-Lemon model, an ontological
framework was created, where the purpose was to present
each lexical entry as “historically dynamic” instead of
“ontologically static” (Veltman, 2006:6, cited in Rafferty,
2016:5), therefore the provenance information and
generation of Linked Data for an ontological framework
with instances constantly evolving was given particular
attention.
The rest of the paper is organised as follows: in Section 2,
the structure of the dictionary is briefly described; in
Section 3, the URI strategy is discussed; in Sections 4 and
5, the description of resources, provenance for lexical
entries and the lexicons are considered, and the versioning
and generation of Linked Data is presented. The
conclusions of the paper are presented in Section 6.
2. The Structure of the Dictionary
The frame structure of a dictionary is typically composed
of the central list, with front and back matter texts (Gouws
& Prinsloo, 2005); however, the frame structure of EXDN
consists of a central list, with front matter texts only. The
central list of EXDN is represented by the Roman
alphabet, with each letter acting as a guiding element for a
series of article stretches (Gouws & Prinsloo, 2005).
EXDN can also be described according to its
macrostructure and microstructure. EXDN’s
macrostructure comprises a lemmatised list in the source
language only: English - ordered alphabetically with a
singular and plural lemmatisation of nouns (Gouws &
Prinsloo, 2005). A dictionary’s microstructure pertains to
the structure of each article (lexical entry), with the
lemma serving as a guiding element for each (Gouws &
Prinsloo, 2005). In the case of EXDN, each article
comprises one of the following (or a combination
thereof): lexicographic definition, a translation, or a cross-
reference entry. If the article has a single target language
item, shown by a single word, then it is presumed that the
article is a translation equivalent, with full equivalence
(Gouws & Prinsloo, 2005). However, if the article has a
lexicographic definition in the target language, then zero
equivalence is presumed (Gouws & Prinsloo, 2005).
3. The URI Strategy
Archer, Goedertier and Loutas have defined a URI as a
compact sequence of characters that identifies an abstract
or physical resourceand it “can be further classified as a
locator, a name, or both” (2012).
A key set of principles have been identified for URIs:
URIs should be:
o short,
o stable,
o persistent, and
o human-friendly (Archer, Goedertier & Loutas,
2012; Hogan et al., 2012; Wood et al., 2014).
URIs should be HTTP(S) URIs (Berners-Lee, 2006;
Hogan et al., 2012).
The identifier portion of a URI should be:
o unique,
o and unambiguous (Simons & Richardson,
2013; Keller et al., 2011).
URIs should be dereferenceable, with a
representation returned when a human or software
agent navigates to the URI (Heath & Bizer, 2011;
Hyvönen, 2012).
URIs should differentiate between the resource, and
the document which describes a resource (Van
Hooland & Verborgh, 2014; Heath & Bizer, 2011).
In the sub-sections that follow, fragment identifiers, URI
patterns, and resource identifiers are discussed in more
detail.
3.1 Fragment Identifiers
Fragment identifiers are an optional part of the URI,
positioned at the end, and are of the pattern “#example”.
Although the usage of fragment identifiers have been
cautioned against by Wood et al., primarily because web
servers do not process the fragment, they are widely used
in vocabularies, where “the vocabulary is often served as
a document and the fragment is used to address a
particular term within that document” (2014). Within the
context of identifying sub-resources in relation to the
parent resource, fragment identifiers can be useful, as they
can clearly show a hierarchical relationship with the
parent resource (however, deeper levels cannot be
indicated).
According to Sachs and Finin, the URI should resolve
not to the address, but to all known information about the
resource (2010); from this one can infer that when
information for a sub-resource is returned, then
information for the parent resource should also be
returned. Conversely, when information for a parent
resource is returned, information of any sub-resources
should also be returned. By doing this, the need to have a
separate document to describe the parent resource and
each of the sub-resources is not necessary, as one
document can be used to describe the parent resource and
any sub-resources.
Additionally, when publishing Linked Data and
versioning is employed, by using fragment identifiers to
identify sub-resources within the same document,
redundancy can be reduced.
3.2 The URI Pattern
When working with EXDN data, the following use cases
were determined (Gillis-Webber, 2018):
U1: A URI which identifies a resource
U2: A URI which identifies a sub-resource in relation
to the parent resource
U3: A URI which identifies a version of the resource
U4: A URI which identifies a version combined with a
sub-resource
U5: A URI which identifies a document describing the
resource in U1
U6: A URI which identifies a document describing the
resource in U3
A pattern for a URI has been recommended by Archer et
al. (2012):
http://{domain}/{type}/{concept}/{reference}
Where:
{domain} is the host,
{type} is the resource (for eg. id) being identified,
{concept} refers to a real world object or a
collection, and
{reference} is the local reference for the resource
being identified.
When using the lemon model (a previous iteration of the
Ontolex-Lemon model), Gracia and Vila-Suero developed
a set of guidelines for publishing Linked Data for
bilingual dictionaries, and they too proposed the same
pattern as Archer et al. (2015). As an example, for the
lexical entry “bench”, the URI is as follows:
E1: http://linguistic.linkeddata.es/id/
apertium/lexiconEN/bench-n-en
Where:
linguistic.linkeddata.es is the host,
id is the resource,
apertium is the collection,
lexiconEN is the source lexicon,
bench-n-en is the reference.
When considered from a user perspective, the human-
friendliness of E1 can be evaluated accordingly:
id is not particularly informative and could be
deemed redundant;
although specifying the collection (apertium) is
useful, should a dataset from another collection be
merged with the existing dataset, if there are shared
lexical entries between both collections, this will
result in URIs which are incongruently defined;
both the lexicon and the reference are identifiable as
English, thus lexiconEN could also be deemed
redundant.
Ontolex-Lemon (and lemon as well) requires the lexical
entries in a lexicon to be the same language. If modelling
two languages, then the lexical entries of each language
would be contained within their own lexicon, with
translation relations explicitly defined between the
corresponding lexical entries or their senses, using the
vartrans module (“Final model specification”, n.d.).
BabelNet was also modelled on lemon, and by 2015 it had
271 lexicons, one for each of the languages it supported;
Flavi et al. remarked on this saying lemon requires us to
work on a language-by-language basis, whereas in
BabelNet this distinction does not need to be made
explicit”.
Continuing with the example lexical entry “bench”, in
BabelNet, the URI is as follows:
E2: http://babelnet.org/rdf/bench_n_EN
There should be a separation between the URIs and the
model used to describe the lexical data. If the model
should change, the persistence and longevity of the URIs
should not be impacted, and as a result, a “URI should be
agnostic of the selected model” (Gillis-Webber, 2018).
For E1 and E2, both the references (bench-n-en and
bench_n_EN respectively) have been encoded with
additional information by appending the lemma with the
language shortcode and an abbreviated form of part-of-
speech (POS), and by doing this, the URIs for the two
examples are identifiable to be of the English language
with POS noun.
E1 could therefore be revised to:
http://linguistic.linkeddata.es/entry/bench-n-en
And for a lexicon:
http://linguistic.linkeddata.es/lexicon/en
For each of the six use cases identified for EXDN at the
beginning of Section 3.2, the application of this simplified
pattern has continued, and below, the pattern of each use
case is provided, followed by a short description thereof,
as well as an associated example from Londisizwe.org,
the multilingual online dictionary derived from the EXDN
dataset.
A URI which identifies a resource has the form (Gillis-
Webber, 2018):
U1: {http(s):}//{Base URI}/
{Resource Path}/{Resource ID}
Where:
{http(s):} is the http: or https: scheme
{Base URI} is the host
{Resource Path}, for example, entry for a lexical
entry, and lexicon for a lexicon
{Resource ID}, for example, en-n-abdomen
An example URI is:
https://londisizwe.org/entry/en-n-abdomen
A URI which identifies a sub-resource in relation to the
parent resource has the form (Gillis-Webber, 2018):
U2: {http(s):}//{Base URI}/
{Resource Path}/{Resource ID}#{Fragment
ID}
Where:
{Fragment ID} is the fragment identifier, for
example, sense1
An example URI is:
https://londisizwe.org/entry/en-n-abdomen#sense1
The resource identifier, described in U1, will be unique
relative to the resource path. The fragment identifier will
be unique relative to the resource identifier.
A URI which identifies a version of the resource has the
form (Gillis-Webber, 2018):
U3: {http(s):}//{Base URI}/
{Resource Path}/{Resource ID}/{Version
ID}
Where:
{Version ID} is the version identifier, for example,
2017-09-19
An example URI is:
https://londisizwe.org/entry/en-n-abdomen/2017-
09-19
As the sub-resource is identified in relation to the parent
resource, any change to the sub-resource would result in a
change to the URI of the parent resource.
Therefore, a URI identifying a sub-resource when
employing the use of versioning has the form (Gillis-
Webber, 2018):
U4: {http(s):}//{Base URI}/
{Resource Path}/{Resource ID}/{Version
ID}#{Fragment ID}
An example URI is:
https://londisizwe.org/entry/en-n-abdomen/2017-
09-19#sense1
For a resource, each version should be dereferenceable,
and should remain so even as newer versions of the same
resource are published. Like that of the fragment
identifier, the version identifier is unique to the resource
identifier. The use case U1 will resolve to the latest
version available for that resource (Archer et al., 2012).
A URI which identifies a document describing the
resource in U1 has the form (Gillis-Webber, 2018):
U5: {http(s):}//{Base URI}/
{Document}/{Resource Path}/{Resource ID}
Where:
Using content negotiation, {Document} refers to the
HTML page, for example, page, or to the RDF
representation, for example, rdf, using any form of
serialisation.
Corresponding examples are:
https://londisizwe.org/page/entry/en-n-abdomen
https://londisizwe.org/rdf/entry/en-n-abdomen
A URI which identifies a document describing the
resource in U3 has the form (Gillis-Webber, 2018):
U6: {http(s):}//{Base URI}/
{Document}/{Resource Path}/{Resource
ID}/{Version ID}
An example URI is:
https://londisizwe.org/rdf/entry/en-n-
abdomen/2017-09-19
In the context of EXDN, a document which describes U2
(or U4) is not necessary, and instead it resolves to U5 (or
U6).
3.3 Resource Identifiers
The human-friendliness of URIs has been suggested in the
literature, with frequent references thereto: such as URIs
should be “user-friendly” (Archer, Goedertier & Loutas,
2012), “human readable” (Hogan et al., 2012),
“meaningful” (Villazón-Terrazas et al., 2012), and
“natural keys” should be used (Wood et al., 2014; Heath
& Bizer, 2011). Defined by Labra Gayo, Kontokostas
and Auer (n.d.) as “descriptive URIs”, and as “meaningful
URIs” by Vila-Suero et al. (2014), this type of URI is
generally used “with terms in English or in other Latin-
based languages” (Labra Gayo, Kontokostas & Auer,
n.d.).
Labra Gayo et al. defines “opaque URIs” as “resource
identifiers which are not intended to represent terms in a
natural language”, with it suggested by both Labra Gayo,
Kontokostas and Auer (n.d.), and Vila-Suero et al. (2014)
that in a multilingual context, using opaque URIs is
preferable so as to avoid language bias. By doing so
within the context of the Semantic Web, Vila-Suero et al.
argue that this is acceptable, as “resource identifiers are
intended for machine consumption so that there is no need
for them to be human readable” (2014).
Within the larger context of the Semantic Web, this view
may be accurate as data models are mostly language-
agnostic (Ehrmann, 2014), however in the context of
Linked Data, it is in opposition to a fundamental principle
thereof: a URI should be dereferenceable, to be looked up
by either a web browser for human consumption or a
software agent (Hyvönen, 2012).
Due to the localisation of this study within South Africa
and its languages being Latin-based, a pragmatic approach
was taken with regards to the URIs: descriptive URIs
were used, using English, however in a similar approach
to Babelnet, opaque URIs were used when modelling the
lexical concepts (Flati et al., 2015).
For lexical entries, a similar approach as that used in E1
was taken for the resource identifiers, however the
elements were reordered to aid programmatic extraction
(should it be required):
{Language Code}-{POS}-{Lemma}
Where:
{Language Code} is the lowercase form of the
language shortcode, using ISO 639-1, and if none
available, then ISO 639-2 (or ISO 639-3) will be used
{POS} is an abbreviated form of POS, described in
English
{Lemma} is the lowercase form of the lemma, with
underscores replacing any hyphens or spaces and any
diacritics are removed
For a lexical entry, a constraint of the Ontolex-Lemon
model is that it can be associated with exactly one POS
and exactly one language (“Final model specification”,
n.d.). For lexical entries which may share the same
lemma, such as:
isiXhosa: isibindi
isiZulu: isibindi
to avoid potential collision, it was considered best for the
EXDN dataset to include the language shortcode and the
abbreviated POS in the identifier as well, thus allowing
for the easy extensibility of the existing dataset to
additional languages. Thus for the two lexical entries
above, their identifiers would be as follows:
isiXhosa: xh-n-isibindi
isiZulu: zu-n-isibindi
For a lexicon, the resource identifier takes the form
(shown here including the resource path):
{Resource Path}/{Language Code}
In combination with the resource path, the resource
identifier should adequately identify the lexical entry (or
lexicon), thus allowing for any language to be represented
(with the exception of the written form of sign languages,
which can conceivably be any language) (Gillis-Webber,
2018).
4. The Description of Resources
As previously mentioned, when returning information for
a resource and any of its sub-resources, the information
returned should not be limited to describing these
resources, the inclusion of the following additional
information could be considered as well (Gillis-Webber,
2018):
A description of related resources;
A description of the metadata of the resource (for
example, provenance and version);
A description of the dataset which contains the
resource (Heath & Bizer, 2011:45).
In the case of EXDN, when publishing the information for
a lexicon which resolves, for example, to the URI
https://londisizwe.org/lexicon/en, it was not
considered practical to include information of the related
resources, particularly for each lexical entry. However,
when publishing the information for a lexical entry which
resolves, for example, to the URI
https://londisizwe.org/entry/en-n-abdomen, it was
considered necessary, and the following additional
information is thus included (Gillis-Webber, 2018):
Description of the document which describes the
lexical entry,
Metadata of the lexical entry,
Provenance information of the lexical entry,
Identification of the lexicon to which the entry
belongs,
Brief description of other lexical entries, resources
and ontology entities related to the lexical entry.
5. Modelling Provenance & Versioning
According to Di Maio (2015), knowledge is
“partial/incomplete/imperfect, with very few exceptions”.
Linked Data is about relationships, and when considered
within the context of Linguistics, datasets of different
lexicons can be interlinked, thus allowing for the
extension of an existing lexicon; for under-resourced
languages, this can be a powerful notion (Berners-Lee,
2009; McCrae et al., 2012). According to Bouda and
Cysouw (2012), when retrodigitising language resources,
the encoding thereof is not the challenge, but rather “the
continuing update, refinement, and interpretation” of the
dataset, and with each change, providing for traceability.
Like RDF datasets, ontologies and vocabularies are not
static, and they too evolve over time (Hyvönen, 2012).
This change can be attributed to factors such as error
correction, the addition of concepts and properties to the
underlying model, as well as change out in the world, and
our understanding thereof (Hyvönen, 2012).
As mentioned in Section 2, within the context of EXDN,
until established otherwise, then full equivalence is
presumed if the article has a single target language item,
and if anything more than a single target language, then it
is presumed the article is a lexicographic definition and
there is zero equivalence (Gouws & Prinsloo, 2005).
Google’s Cloud Translation API1 was used to translate the
isiXhosa texts, with English selected as the target
language. There are two models available: Phrase-Based
Machine Translation model (PBMT) and Neural Machine
Translation model (NMT), and using each model, an
article was translated (“Translating text”, n.d.). As an
example, the article stomach, which has the isiXhosa text
of “Uluusu lomntu.”, when translated on 2017-09-17
20:00:31 GMT+2, yielded the following:
PBMT: A person’s skin.
NMT: Homosexuality.
1 https://cloud.google.com/translate/
There are several possibilities for this: (1) the source data
contains errors, (2) the source data is so outdated that it is
not possible to translate this accurately, or (3) there are
not enough existing language pairs within the Cloud
Translation API to accurately translate the text (“Cloud
translation API”, n.d.). According to Google’s website,
the Cloud Translation API undergoes continuous updates
(“Cloud translation API”, n.d.) so although it is intended
to periodically repeat the translation process for the
EXDN dataset, for now, the translated texts are not used
for disambiguation purposes.
Continuing with the article stomach, when the lexical
entry with the identifier en-n-stomach was first published
in 2017, its only sense (en-n-stomach#sense1) was
linked to a lexical concept
(https://londisizwe.org/concept/000000007) which
had a language-tagged lexicographic definition "Uluusu
lomntu."@xh, and it was set as a concept of the DBpedia
resource: http://dbpedia.org/resource/Stomach.
However, after consultation with isiXhosa mother tongue
speakers in early 2018, the following was determined:
“uluusu” was incorrectly spelt in EXDN (it should
have been “ulusu”),
the equivalent of stomach is also isisu,
the meaning (gloss) of “ulusu lomntu” is “a person’s
stomach”, however it was difficult to determine if the
text should remain a lexicographic definition or if it
should become a lexical entry with “ulusu lomntu” as
the lemma.
As a result of this new information, the following changes
were implemented:
For the lexical entry en-n-stomach, the spelling
mistake was corrected in the lexical concept.
The lexical entry xh-n-isisu already existed,
however another sense was added (xh-n-
isisu#sense2), and it was linked to the same lexical
concept.
Because there is a shared conceptualisation between
https://londisizwe.org/entry/en-n-stomach#sense1
and https://londisizwe.org/entry/xh-n-
isisu#sense2, they are deemed to be equivalent.
As the purpose of digitising EXDN and converting its
dataset to Linked Data is to enable its reuse by external
resources, it is important that any changes are accurately
recorded, by way of versioning, with provenance
information included as well. The lexical entry xh-n-
isisu had a change to one of its senses (a sub-resource),
and the lexical concept 000000007 changed as well, so
there is now a new version for each. As there were not
any insertions or deletions for the English and isiXhosa
lexicons, these remained unchanged. In the event the
lexical entries had to be reviewed again, it is expected
they would be subject to further refinement.
As an aside, the Cloud Translation API was used again
(2018-03-02 20:36:48 GMT+2), this time with the
corrected text “Ulusu lomntu.”. PBMT remained
unchanged, however NMT returned the following
translation: Human skin.”. It was also repeated for the
original source text, and those translations remained
unchanged from 2017-09-17.
5.1 Versioning
Versioning is used by Babelnet, although it is applied
globally for their BabelNet-lemon schema description,
with Flati et al. acknowledging that “maybe a more
sophisticated infrastructure would be needed in order to
express more complex versioning description needs”
(2015). When the generation and publication of RDF data
for the Apertium Bilingual Dictionaries was detailed by
Gracia et al., versioning was not included in the
discussion (n.d.). Although briefly mentioned by McCrae
et al. (2012), Gracia et al. (n.d.), Eckart et al. (2012), van
Erp (2012), and De Rooij et al. (2016), it does not appear
that versioning has been discussed further within the
domain of Linguistic Linked Data, and in the context of
vocabularies used by Babelnet, Flati et al. commented that
changes are unaccounted for “and this aspect might thus
be investigated in more detail in the [near] future by the
whole community” (2015).
When describing the generation of RDF for the Apertium
Bilingual Dictionaries, Gracia et al. talked of three RDF
files: one per lexicon, and the third for the translations
(n.d.). From this, the author inferred that if versioning
was implemented, it would be done at file-level, in a
similar approach to that taken by BabelNet. However, in
the context of EXDN, it was felt that publishing only at
the lexicon-level could become unmanageable over time,
particularly on a 24-hour publishing schedule, and instead
it would be more practical to implement versioning at the
lexical entry-level as well. Versioning at the lexicon-level
is also done, but a file only includes the changes from the
previously published version, and any additional
information of the lexical entries, beyond the resource
identifier, is excluded. For each version of a lexical entry,
the file contains: all information of the lexical entry, its
senses, and translation relations for which any of its
senses is the source.
Thus, the following components have been identified for
the versioning of EXDN (Gillis-Webber, 2018):
Versioned URIs for lexicons, lexical entries, and
senses
Provenance metadata to describe the versions, with
the latest version mapping to previous versions (Van
Erp, 2012), and
The generation of files, one for each version of the
lexical entries and lexicons.
Within the context of EXDN, lexical concepts are
modelled as a shared conceptualisation between senses,
and they can be thought of as similar to that of a WordNet
synset, however, where WordNet models sets of similar
terms, lexical concepts model sets of equivalent senses
across languages (Bosque-Gil et al, 2015). Although the
lexical concepts are hosted on the same domain, they are
stored within a sense inventory called Londisizwe
Concepts for Senses2 this is considered to be a
standalone inventory, and as a result, it is not described
further here, although the same principles for versioning
do apply (Gillis-Webber, 2018).
Section 3.2 introduced versioned URIs, with the use
cases: U3 and U4. Modelling provenance, and the
2 https://londisizwe.org/concept
generation and publication of Linked Data are discussed
in the sections that follow.
5.2 Modelling Provenance for a Lexical Entry,
its Senses, and Translation Relations
The W3C Provenance Working Group defines provenance
(“PROV-O”, 2013):
as a record that describes the people, institutions, entities,
and activities involved in producing, influencing, or
delivering a piece of data or a thing.
A factor contributing to the reuse of a RDF dataset, either
by linking or by using the downloaded data, is trust trust
in the repository supplying the data, and trust in the data
itself (Faniel & Yakel, 2017). By documenting the
provenance of data using a systematic schema,
provenance provides a trust marker (essential in an open
environment like the web); and within the context of
EXDN, provenance information is documented using the
PROV Ontology, DCMI Metadata terms, and versioned
URIs (Faniel & Yakel, 2017; “PROV-O”, 2013; Tennis,
2007; Flati et al., 2015).
The metadata used to describe the EXDN dataset is as
follows:
Each lexical entry, sense, and translation relation is
identified as a prov:Entity.
The prov:generatedAtTime property is recorded for
each.
The date a lexical entry, sense or translation relation
is changed is recorded using dct:modified.
The person or organisation responsible for creating
the lexical entry or sense is identified using
dct:creator.
The source from which a lexical entry is primarily
derived is identified using the
prov:hadPrimarySource property.
The other sources from which a lexical entry, sense or
translation relation is derived, is identified using the
dc:source property.
One or more contributors (a person, an organisation
or a service) for a lexical entry, sense or translation
relation is identified using dct:contributor.
The licensing agreement for a lexical entry is
identified using dct:license, and Creative
Commons is used for the licensing.
For a lexical entry, dct:isPartOf is used to denote
inclusion of a lexical entry in a lexicon, and inclusion
of a sense in a lexical entry.
For a translation relation, dct:hasPart is used to
identify both the source and target language.
For a lexical entry, owl:sameAs is used to indicate
that U1 is the same as the latest version of U3.
For a sense or translation relation, owl:sameAs is used
to indicate that U2 is the same as the latest version of
U4.
For a lexical entry, sense or translation relation, the
version is indicated using owl:versionInfo.
For a lexical entry, sense or translation relation,
dct:hasVersion is used to show the previously
generated versions, using the versioned URIs (U3 for
lexical entries and U4 for senses and translation
relations).
The generated RDF for version two of the lexical entry
xh-n-isisu follows below. The lexical concept for
000000001 is also shown for reference purposes.
!!"#$%
&%
'%
(%
)%
*%
+%
,%
-%
%
.%
&/%
&&%
&'%
&(%
&)%
&*%
&+%
&,%
&-%
&.%
%
'/%
'&%
''%
'(%
')%
'*%
'+%
%
',%
'-%
'.%
(/%
(&%
('%
((%
()%
(*%
(+%
%
(,%
%
(-%
(.%
%
)/%
)&%
)'%
)(%
))%
)*%
)+%
),%
)-%
).%
*/%
*&%
*'%
*(%
*)%
**%
*+%
%
*,%
*-%
*.%
+/%
+&%
+'%
+(%
+)%
+*%
++%
+,%
+-%
+.%
%
,/%
,&%
,'%
,(%
,)%
,*%
,+%
,,%
,-%
,.%
-/%
-&%
%
0123456%7%%%%%%89::1;7<<=>?@5;5AB3C>2D<E%C%
0123456%>?:>=367%89::17<<BBBCB(C>2D<?;<=3F>?<>?:>=36GE%C%
0123456%@H27%%%89::17<<@H13@5IC>2D<23;>J2K3<E%C%
0123456%@K:7%%%89::17<<1J2=C>2D<@K<:32F;<E%C%
0123456%4>I47%%89::17<<6F=?;CK>F<4>I4</C&<E%C%
0123456%=K?I47%89::17<<5@C=>KCD>L<IJ:9>25:53;<?IF3;<E%C%
0123456%=K;97%%89::17<<5@C=>KCD>L<IJ:9>25:53;<;JHM3K:;<E%C%
0123456%=365?4>7%%%%%%%%%%
%%%%%%%%%%%%%%89::17<<BBBC=365?4>C?3:<>?:>=>DN<'C/<=365?4>GE%C%
0123456%F3;97%%89::17<<5@C?=FC?59CD>L<F3;9<E%C%
0123456%>B=7%%%89::17<<BBBCB(C>2D<'//'</,<>B=GE%C%
0123456%12>L7%%89::17<<BBBCB(C>2D<?;<12>LGE%C%
0123456%1B?7%%%89::17<<B>2@?3:O2@4C125?K3:>?C3@J<2@4<5@<E%C%
0123456%2@47%%%89::17<<BBBCB(C>2D<&...</'<''O2@4O;N?:I6O?;GE%C%
0123456%2@4;7%%89::17<<BBBCB(C>2D<'///</&<2@4O;K93FIGE%C%
0123456%L>5@7%%89::17<<2@4;C>2D<?;<L>5@GE%C%
0123456%6;@7%%%89::17<<BBBCB(C>2D<'//&<PQ!RK93FIGE%C%
%
89::1;7<<=>?@5;5AB3C>2D<2@4<3?:2N<69O?O5;5;JE%
%%%%2@4;7=IH3=%%%STUV%@>KJF3?:%4>2%:93%=365KI=%3?:2N7%%%%%%%%%
%%%%%%%%%%%%%%%%%5;5;JW%?%X5;5P9>;IYS03?%Z%
%%%%2@47:N13%%%%%4>I47U>KJF3?:%Z%
%%%%4>I47125FI2N[>15K%73?:2N<69O?O5;5;J%C%
%
73?:2N<69O?O5;5;J%
%%%%I%>?:>=367!365KI=$?:2N%W%>?:>=367\>2@%W%12>L7$?:5:N%Z%
%%%%=365?4>71I2:]4R133K9%%=365?4>7#>J?%Z%
%%%%@K:7=I?DJID3%89::17<<5@C=>KCD>L<L>KIHJ=I2N<5;>+(.O'<69>E%W%
%%%%%%%%%%%%%%%%%89::17<<=36L>C>2D<5@<5;>+(.O&<69E%Z%
%%%%@K:75@3?:54532%73?:2N<69O?O5;5;J%Z%
%%%%2@4;7=IH3=%%%%S5;5;JS069%Z%
%%%%>?:>=367KI?>?5KI=V>2F%73?:2N<69O?O5;5;JG=3FFI%Z%
%%%%>?:>=367;3?;3%73?:2N<69O?O5;5;JG;3?;3&%W%
%%%%%%%%%%%%%%%%%%73?:2N<69O?O5;5;JG;3?;3'%Z%
%%%%@K:7;JHM3K:%%%F3;97U/////*%Z%
%%%%>?:>=367@3?>:3;%@H27^H@>F3?%W%@H27R:>FIK9%Z%
%%%%>?:>=3673L>_3;%7K>?K31:<////////&%Z%
%%%%@K:75;`I2:]4%%7=365K>?<69%Z%
%%%%@K:7=5K3?;3%%
%%%%89::17<<K23I:5L3K>FF>?;C>2D<1JH=5K@>FI5?<FI2_<&C/<E%Z%
%%%%12>L79I@`25FI2NR>J2K3%S[93%$?D=5;9OP9>;I%U5K:5>?I2N%4>2%%
%%%%%%%%%%%%%%%%%%#J2;3;S03?%Z%
%%%%@K:7K23I:>2%%%89::1;7<<=>?@5;5AB3C>2DE%Z%
%%%%12>L7D3?32I:3@^:[5F3%S'/&-O/&O%
%%%%%%%%%%%%%%%%%%&/[/*7//7//abc/'7//Sdd6;@7@I:3[5F3%Z%
%%%%@K:7F>@5453@%%S'/&-O/&O&/Sdd6;@7@I:3%Z%
%%%%>B=7L32;5>?"?4>%S'/&-O/&O&/Sdd6;@7;:25?D%Z%
%%%%>B=7;IF3^;%%%%%73?:2N<69O?O5;5;J<'/&-O/&O&/%Z%
%%%%>B=79I;e32;5>?%73?:2N<69O?O5;5;J<'/&,O/.O&.%W%%
%%%%%%%%%%%%%%%%%%%73?:2N<69O?O5;5;J<'/&-O/&O&/%C%
%
73?:2N<69O?O5;5;JG=3FFI%
%%%%I%%%%%%%%%%%%%>?:>=367V>2F%Z%
%%%%>?:>=367B25::3?T31%%S5;5;JS069%C%
%
73?:2N<69O?O5;5;JG;3?;3&%
%%%%I%%%%%%%%%%%%%>?:>=367!365KI=R3?;3%W%12>L7$?:5:N%Z%
%%%%>?:>=3675;!365KI=5A3@R3?;3]4%7K>?K31:<////////&%Z%
%%%%@K:75@3?:54532%73?:2N<69O?O5;5;JG;3?;3&%Z%
%%%%@K:75;`I2:]4%%73?:2N<69O?O5;5;J%Z%%%%%
%%%%@K:7K23I:>2%%%89::1;7<<=>?@5;5AB3C>2DE%Z%
%%%%12>L7D3?32I:3@^:[5F3%S'/&-O/&O%%%
%%%%%%%%%%%%%%%%%%&/[/*7//7//abc/'7//Sdd6;@7@I:3[5F3%Z%
%%%%@K:7F>@5453@%%S'/&-O/&O&/Sdd6;@7@I:3%Z%
%%%%>B=7L32;5>?"?4>%S'/&-O/&O&/Sdd6;@7;:25?D%Z%
%%%%>B=7;IF3^;%%%%73?:2N<69O?O5;5;J<'/&-O/&O&/G;3?;3&%Z%
%%%%>B=79I;e32;5>?%%73?:2N<69O?O5;5;J<'/&,O/.O&.G;3?;3&%W%%
%%%%%%%%%%%%%%%%%%%%73?:2N<69O?O5;5;J<'/&-O/&O&/G;3?;3&%C%
%
73?:2N<69O?O5;5;JG;3?;3'%
%%%%I%%%%%%%%%%%%%>?:>=367!365KI=R3?;3%W%12>L7$?:5:N%Z%
%%%%>?:>=3675;!365KI=5A3@R3?;3]4%7K>?K31:<////////,%Z%
%%%%@K:75@3?:54532%73?:2N<69O?O5;5;JG;3?;3'%Z%
%%%%@K:75;`I2:]4%%73?:2N<69O?O5;5;J%Z%%%%%
%%%%@K:7K23I:>2%%%89::1;7<<=>?@5;5AB3C>2DE%Z%
%%%%12>L7D3?32I:3@^:[5F3%S'/&-O/&O%%%
%%%%%%%%%%%%%%%%%%&/[/*7//7//abc/'7//Sdd6;@7@I:3[5F3%Z%
%%%%>B=7L32;5>?"?4>%S'/&-O/&O&/Sdd6;@7;:25?D%Z%
%%%%>B=7;IF3^;%%%%73?:2N<69O?O5;5;J<'/&-O/&O&/G;3?;3'%Z%
%%%%>B=79I;e32;5>?%%73?:2N<69O?O5;5;J<'/&-O/&O&/G;3?;3'%C%
%
7K>?K31:<////////&%
%%%%I%%%%%%%%%%%%%%;_>;7f>?K31:%W%>?:>=367!365KI=f>?K31:%Z%
%%%%>?:>=367=365KI=5A3@R3?;3%73?:2N<3?O?OIH@>F3?G;3?;3&%Z%
%%%%>?:>=367=365KI=5A3@R3?;3%73?:2N<69O?O5;5;JG;3?;3&%Z%
%%%%>B=7;IF3^;%%%%%1B?7/**+)*,+O?%Z%
%%%%>B=7;IF3^;%%%%%F3;97Q/////*%Z%
%%%%@K:7;JHM3K:%%%%F3;97U/////*%Z%
%%%%>?:>=3675;f>?K31:]4%%@H27^H@>F3?%C%
%
Figure 1: Modelling of a lexical entry
5.3 Modelling Provenance for a Lexicon
Using the same principles from the previous sections, as
well as the lime module from Ontolex-Lemon, the
metadata of EXDN’s isiXhosa lexicon is described below
in RDF. The metadata only serves to describe the lexicon,
and when a lexical entry is inserted or removed from a
lexicon is not described. However, PROV-Dictionary3,
published by the W3C Provenance Working Group in
2013 as an extension to PROV, “introduces a specific type
of collection, consisting of key-entity pairs”, thus
allowing for the change of lexical entries in a lexicon, as
members of a collection, to be expressed as well (“PROV-
Dictionary: Modeling provenance …”, 2013).
The generated RDF for version three of the lexicon xh
follows below:
!!"#$%
&%
'%
(%
)%
*%
+%
,%
-%
.%
&/%
&&%
&'%
&(%
&)%
&*%
&+%
&,%
&-%
%
&.%
'/%
%
'&%
''%
'(%
%
')%
'*%
'+%
%
',%
'-%
'.%
(/%
(&%
('%
((%
()%
%
(*%
(+%
(,%
(-%
(.%
)/%
)&%
)'%
)(%
))%
)*%
)+%
),%
%
0123456%7%%%%%%89::1;7<<=>?@5;5AB3C>2D<E%C%
0123456%=5F37%%89::17<<BBBCB(C>2D<?;<=3F>?<=5F3GE%C%
0123456%@K:7%%%89::17<<1J2=C>2D<@K<:32F;<E%C%
0123456%4>I47%%89::17<<6F=?;CK>F<4>I4</C&<E%C%
0123456%>B=7%%%89::17<<BBBCB(C>2D<'//'</,<>B=GE%C%
0123456%12>L7%%89::17<<BBBCB(C>2D<?;<12>LGE%C%
0123456%2@47%%%89::17<<BBBCB(C>2D<&...</'<''O2@4O;N?:I6O?;GE%C%
0123456%2@4;7%%89::17<<BBBCB(C>2D<'///</&<2@4O;K93FIGE%C%
0123456%L>5@7%%89::17<<2@4;C>2D<?;<L>5@GE%C%
0123456%6;@7%%%89::17<<BBBCB(C>2D<'//&<PQ!RK93FIGE%C%
%
89::1;7<<=>?@5;5AB3C>2D<2@4<=365K>?<69E%
%%%%2@4;7=IH3=%%%STUV%@>KJF3?:%4>2%:93%=365K>?7%5;5P9>;IS03?%Z%
%%%%2@47:N13%%%%%4>I47U>KJF3?:%Z%
%%%%4>I47125FI2N[>15K%7=365K>?<69%C%
%
7=365K>?<69%
%%%%I%=5F37!365K>?%W%L>5@7UI:I;3:%W%%
%%%%%%12>L7U5K:5>?I2N%W%12>L7f>==3K:5>?%W%12>L7$?:5:N%Z%
%%%%=5F37=I?DJID3%%S69S%Z%
%%%%@K:7=I?DJID3%89::17<<5@C=>KCD>L<L>KIHJ=I2N<5;>+(.O'<69>E%W%
%%%%%%%%%%%%%%%%%89::17<<=36L>C>2D<5@<5;>+(.O&<69E%Z%
%%%%@K:75@3?:54532%7=365K>?<69%Z%
%%%%=5F37=365KI=$?:253;%S&Sdd6;@75?:3D32%Z%
%%%%=5F37=5?DJ5;:5KfI:I=>D%%
%%%%%%%%%%%89::17<<BBBC=365?4>C?3:<>?:>=>D53;<'C/<=365?4>E%Z%
%%%%@K:7@3;K251:5>?%S!>?@5;5AB3C>2D%O%5;5P9>;I%=365K>?S03?%Z%
%%%%@K:7K23I:>2%%%%89::1;7<<=>?@5;5AB3C>2DE%Z%
%%%%12>L7D3?32I:3@^:[5F3%S'/&-O/&O%
%%%%%%%%%%%%%%%%%%%&*[/+7//7//abc/'7//Sdd6;@7@I:3[5F3%Z%
%%%%@K:7F>@5453@%%%S'/&-O/&O&*Sdd6;@7@I:3%Z%
%%%%>B=7L32;5>?"?4>%S'/&-O/&O&*Sdd6;@7;:25?D%Z%
%%%%>B=7;IF3^;%%%%%7=365K>?<69<'/&-O/&O&*%Z%
%%%%>B=79I;e32;5>?%7=365K>?<69<'/&,O/.O&.%W%
%%%%%%%%%%%%%%%%%%%7=365K>?<69<'/&-O/&O&'%W%
%%%%%%%%%%%%%%%%%%%7=365K>?<69<'/&-O/&O&*%Z%
%%%%@K:7234323?K3;%7=365K>?<3?%Z%
%%%%L>5@7@I:IUJF1%%89::1;7<<=>?@5;5AB3C>2D<@I:I<69O%
%%%%%%%%%%%%%%%%%%%=365K>?<'/&-O/&O&*E%C%
%
7=365K>?<69<'/&-O/&O&'%
%%%%I%%%%%%%%%%%%%%12>L7U5K:5>?I2N%C%
%
7=365K>?<69<'/&-O/&O&*%%
%%%%I%%%%%%%%%%%%%%12>L7U5K:5>?I2N%Z%
%%%%12>L7@325L3@gNT3F>LI=V2>F%7=365K>?<69<'/&-O/&O&'%Z%
%%%%12>L7hJI=5453@T3F>LI=%i%%
%%%%%%%%I%%%%%%%%%%12>L7T3F>LI=%Z%
%%%%%%%%12>L7@5K:5>?I2N%7=365K>?<69<'/&-O/&O&'%Z%
%%%%%%%%12>L723F>L3@j3N%S69O?OJ=J;Jk=>F?:JSdd6;@7;:25?D%Z%
%%%%l%Z%
C%
%
Figure 2: Modelling of a lexicon
Where:
Lines 3637: the previous version is identified as a
dictionary. There were two dictionary entries,
although those entries are not listed here, instead they
would have been listed in the file of the previously
published URI:
https://londisizwe.org/lexicon/xh/2018-01-12
3 https://www.w3.org/TR/2013/NOTE-prov-dictionary-20130430/
Lines 39 40: the current version is identified as a
dictionary.
Line 41: states that the current version was derived
from the previous version.
Lines 42 46: indicates the key that was removed.
There is now only one lexical entry, xh-n-isisu, in
the isiXhosa lexicon.
The class prov:Dictionary is defined as “an entity that
provides a structure to some constituents, which are
themselves entities. These constituents are said to be
members of the dictionary”, and the concept of
‘dictionary’ can be extended to include “a wide variety of
concrete data structures, such as maps or associative
arrays” (“PROV-Dictionary: Modeling provenance …”,
2013). Within the context of EXDN, while
prov:Dictionary has only been applied to lexicons, it
could conceivably also be applied to lexical entries and
lexical concepts both of which are containers, with each
having senses as its members. While this has not yet been
explored for the EXDN dataset, it is work that will be
considered in the future.
5.4 Generation and Publication of Linked Data
In a similar vein to versioning, the generation and
publication of RDF data is only briefly mentioned in the
literature (Vila-Suero et al., 2014; Ehrmann et al., 2014;
Gracia et al., n.d.), although for BabelNet, Ehrmann et al.
did talk of RDF dump files (which no longer seem to be
available for download). For the RDF files discussed in
Section 5.1 for the Apertium Bilingual Dictionaries,
Gracia et al. (n.d.) talked of loading them into a Virtuoso4
triple store, with a SPARQL endpoint to access the RDF
data, as well as the development of a Linked Data
interface using Pubby5. The topic was explored further by
Gracia in a presentation in 2017, recommending the use of
a SPARQL store, with “a mechanism to make [our] URIs
dereferenceable: through a common web server (as files),
or by making use of a Linked Data interface. According
to Heath and Bizer (2011), storing static RDF files on a
web server is “the simplest way to publish Linked Data”,
and within the context of EXDN, this was the selected
route. A Dictionary Writing System was custom-
developed for the purpose of maintaining the EXDN
dataset, with automated processes implemented for file
generation.
Because of the versioning requirements listed in the
previous section, the following approach to publication is
taken:
When a lexical entry (or its senses or translation
relations of which one of the senses of the lexical
entry is the source) changes, a new file in the various
formats required is generated. U1 always point to the
latest version of the lexical entry. This is an
automated task, scheduled to run daily at 5AM.
Lexical entries are members of the lexicon collection,
and if there are any changes to the members
(insertions or deletions), then a new version of the
lexicon file is generated, using the same principle as
that described for lexical entries. This process is
repeated per lexicon.
4 https://virtuoso.openlinksw.com/
5 http://wifo5-03.informatik.uni-mannheim.de/pubby/
The files representing the latest version of the lexicon
and its lexical entries are manually merged and
compressed to create a data dump. It is planned to
automate this process in the future. A SPARQL
endpoint is currently not available, although it is
planned to trial Dydra6, a cloud-hosted RDF platform
(“Dydra”, 2011).
6. Conclusion
Although EXDN was published in 1935, once the dataset
is fully converted to Linked Data, it will continue to
evolve: with the identification of additional resources to
link to; by merging with other LRs; as well as the planned
implementation of a crowdsourcing approach to correct,
change, and add lexicographic definitions, cross-reference
entries, translations, senses, and annotations to lexical
entries in multiple African languages. Within the context
of EXDN, provenance and versioning has thus been
identified as essential components whilst converting the
dictionary to Linguistic Linked Data, as well as for its on-
going improvements thereafter.
Furthermore, the lemmatisation approach for African
languages, as well as annotations within a multilingual
environment were modelling challenges identified by the
author whilst working with the EXDN dataset. Likewise,
the representation of hierarchy in RDF, be it in the form
of sub-senses, or inflection, with multiple affixes attached
to a word stem, has been identified as a modelling
challenge by Gracia, Kernerman and Bosque-Gil (2017).
Both a lexicography module and a morphology module
for the Ontolex-Lemon model is in progress with the
Ontology-Lexica Community Group, and when
implemented, it is expected that the modelling of EXDN’s
lexical entries and senses may change (Bosque-Gil, 2017;
McCrae & Gracia, 2017). Although the Ontolex-Lemon
model takes a modular approach, as its range extends,
provenance and versioning will be of importance so that
any change to the RDF representation of data is accurately
recorded.
7. Acknowledgements
Thank you to the reviewers for the kind advice and
suggestions on improving this paper.
8. Bibliographical References
Archer, P., Goedertier, S. & Loutas, N. (2012). D7.1.3
Study on persistent URIs, with identification of best
practices and recommendations on the topic for the MSs
and the EC. Available:
https://joinup.ec.europa.eu/sites/default/files/document/2
013-02/D7.1.3%20-
%20Study%20on%20persistent%20URIs.pdf [2017,
December 26].
Berners-Lee, T. (2006). Linked data. Available:
https://www.w3.org/DesignIssues/LinkedData.html
[2017, December 25].
Berners-Lee, T. (2009). Tim Berners-Lee: the next web
[Video file]. Available:
http://www.ted.com/talks/tim_berners_lee_on_the_next
_web.html [2017, April 15].
6 https://dydra.com
Bosque-Gil, J. (2017). Linked data and dictionaries
[Seminar]. 2nd Summer Datathon on Linguistic Linked
Open Data. 27 June.
Bosque-Gil, J., Gracia, J., Aguado-de-Cea, G. & Montiel-
Ponsoda, E. (2015). Applying the OntoLex model to a
multilingual terminological resource. In The semantic
web: ESWC 2015 satellite events. F. Gandon, C. Guéret,
S. Villata, J. Breslin, C. Faron-Zucker & A.
Zimmerman, Eds. 283-294.
Bouda, P. & Cysouw, M. (2012). Treating dictionaries as
a linked-data corpus. In Linked Data in Linguistics. C.
Chiarcos, S. Nordhoff & S. Hellman, Eds. Heidelberg:
Springer. 15-24.
Cloud translation API: dynamically translate between
thousands of available language pairs. n.d. Available:
https://cloud.google.com/translate/ [2018, February 28].
De Rooij, S., Beek, W., Bloem, P., van Harmelen, F. &
Schlobach, S. (2016). Are names meaningful?
Quantifying social meaning on the semantic web. In The
Semantic Web: ISWC 2016. P. Groth, E. Simperl, A.
Gray, M. Sabou, M. Krötzsch, F. Lecue, F. Flöck & Y.
Gil, Eds. 184-199.
Di Maio, P. (2015). Linked data beyond libraries. In
Linked data and user interaction. H.F. Cervone, L.G.
Svensson, Eds. Berlin: Walter de Gruyter GmbH. 3-18.
Doke, C.M. 1954. The Southern Bantu languages.
London: International African Institute.
Dydra. (2011). Available:
https://www.w3.org/2001/sw/wiki/Dydra [2018, January
3].
Eckart, K., Riester, A. & Schweitzer, K. (2012). A
discourse information radio news database for linguistic
analysis. In Linked Data in Linguistics. C. Chiarcos, S.
Nordhoff & S. Hellman, Eds. Heidelberg: Springer. 65-
76.
Ehrmann, M., Cecconi, F., Vannella, D., McCrae, J.,
Cimiano, P. & Navigli, R. (2014). Representing
multilingual data as linked data: the case of Babelnet
2.0. Available:
http://wwwusers.di.uniroma1.it/~navigli/pubs/LREC_20
14_Ehrmannetal.pdf [2017, December 27].
Faniel, I.M. & Yakel, E. (2017). Practices do not make
perfect: Disciplinary data sharing and reuse practices
and their implications for repository data curation. In
Curating research data: Practical strategies for your
digital repository. L.R. Johnston, Ed. Chicago,
Association of College and Research Libraries. 103-126.
Final model specification. n.d. Available:
https://www.w3.org/community/ontolex/wiki/Final_Mo
del_Specification [2017, December 27].
Flati, T., Moro, A., Matteis, L., Navigli, R. & Velardi, P.
(2015). Guidelines for linguistic linked data generation:
multilingual dictionaries (Babelnet). Available:
https://www.w3.org/2015/09/bpmlod-
reports/multilingual-dictionaries/ [2017, December 27].
Gillis-Webber, F. (2018). The construction of an
ontological framework for bilingual lexicographic
resources: applying linguistic linked data principles.
M.Phil. dissertation. University of Cape Town.
Gouws, R.H. & Prinsloo, D.J. (2005). Principles and
practice of South African lexicography. Stellenbosch:
SUN MeDIA.
Gracia, J. (2017). Introduction to linked data for language
resources [Practical session]. 2nd Summer Datathon on
Linguistic Linked Open Data. 26 June.
Gracia, J., Kernerman, I. & Bosque-Gil, J. (2017). Toward
linked data-native dictionaries. Available:
https://elex.link/elex2017/wp-
content/uploads/2017/09/paper33.pdf [2018, January
17].
Gracia, J. & Vila-Suero, D. (2015). Guidelines for
linguistic linked data generation: bilingual dictionaries.
Available: https://www.w3.org/2015/09/bpmlod-
reports/bilingual-dictionaries/ [2017, December 25].
Gracia, J., Villega, M., Gómez-Pérez, A. & Bel, N. n.d.
The Apertium bilingual dictionaries on the web of data.
Available: http://www.semantic-web-
journal.net/system/files/swj1419.pdf [2017, December
31].
Heath, T. & Bizer, C. (2011). Linked data: evolving the
web into a global data space. Morgan & Claypool
Publishers.
Herbert, R.K. & Bailey, R. (2002). The Bantu languages:
sociohistorical perspectives. In Language in South
Africa. R. Mesthrie, Ed. Cambridge: Cambridge
University Press. 50-78.
Hogan, A., Umbrich, J., Harth, A., Cyganiak, R., Polleres,
A. & Decker, S. (2012). An empirical survey of linked
data conformance. Web Semantics: Science, Services
and Agents on the World Wide Web. 14:14-44.
Hyvönen, E. (2012). Publishing and using cultural
heritage linked data on the semantic web. Morgan &
Claypool Publishers. DOI:
10.2200/S00452ED1V01Y201210WBE003
Keller, M.A., Persons, J., Glaser, H. & Calter, M. (2011).
Report on the Stanford Linked Data Workshop.
Available: https://www.clir.org/wp-
content/uploads/sites/6/LinkedDataWorkshop.pdf [2017,
December 26].
Labra Gayo, J.E., Kontokostas, D. & Auer, S. n.d.
Multilingual linked data patterns. Available:
http://www.semantic-web-
journal.net/system/files/swj495.pdf [2017, December
27].
McCrae, J., Aguado-de-Cea, G., Buitelaar, P., Cimiano,
P., Declerck, T., Gómez-Pérez, A., Gracia, J., Hollink,
L., Montiel-Ponsoda, E., Spohr, D. & Wunner, T.
(2012). Interchanging lexical resources on the semantic
web. Language Resources & Evaluation. 46:701-719.
McCrae, J.P. & Gracia, J. (2017). Introduction to the
Ontolex-Lemon Model [Practical session]. 2nd Summer
Datathon on Linguistic Linked Open Data. 26 June.
Ngcobo, M.N. Department of Linguistics and Modern
Languages. (2010). Only study guide for LIN3704:
Language planning and language description. Pretoria:
University of South Africa.
Pretorius, L. (2014). The multilingual semantic web as
virtual knowledge commons: the case of the under-
resourced South African languages. In Towards the
multilingual semantic web. P. Buitelaar & P. Cimiano,
Eds. Berlin: Springer-Verlag. 49-66.
PROV-Dictionary: Modeling provenance for dictionary
data structures. (2013). Available:
https://www.w3.org/TR/2013/NOTE-prov-dictionary-
20130430/ [2018, January 1].
PROV-O: The PROV ontology. (2013). Available:
https://www.w3.org/TR/prov-o/ [2018, January 1].
Rafferty, P. (2016). Managing, searching and finding
digital cultural objects: putting it in context. In
Managing digital cultural objects: analysis, discovery
and retrieval. A. Foster & P. Rafferty, Eds. London:
Facet Publishing. 3-24.
Sachs, J. & Finin, T. (2010). What does it mean for a URI
to resolve?. Available:
http://ebiquity.umbc.edu/_file_directory_/papers/495.pd
f [2017, December 26].
Simons, N. & Richardson, J. (2013). New content in
digital repositories: the changing research landscape.
Oxford: Chandos Publishing.
Statistics South Africa. (2012). Census 2011 Census in
brief. Pretoria: Statistics South Africa. Available:
http://www.statssa.gov.za/census/census_2011/census_p
roducts/Census_2011_Census_in_brief.pdf [2017,
November 5].
Subfamily: Nguni (S.40). n.d. Available:
http://glottolog.org/resource/languoid/id/ngun1276
[2018, February 11].
Tennis, J.T. (2007). Scheme versioning in the semantic
web. In Knitting the semantic web. J. Greenberg & E.
Méndez, Eds. 85-104.
Translating text. n.d. Available:
https://cloud.google.com/translate/docs/translating-text
[2018, January 5].
Van Erp, M. (2012). Reusing linguistic resources: Tasks
and goals for a linked data approach. In Linked Data in
Linguistics. C. Chiarcos, S. Nordhoff & S. Hellman,
Eds. Heidelberg: Springer. 57-64.
Van Hooland, S. & Verborgh, R. (2014). Linked data for
libraries, archives and museums. London: Facet
Publishing.
Vila-Suero, D., Gómez-Pérez, A., Montiel-Ponsoda, E.,
Gracia, J. & Aguado-de-Cea, G. (2014). Publishing
linked data on the web: the multilingual dimension. In
Towards the Multilingual Semantic Web. P. Buitelaar &
P. Cimiano, Eds. Berlin: Springer-Verlag. 101-117.
Villazón-Terrazas, B., Vilches-Blázquez, L.M., Corcho,
O. & Gómez-Pérez, A. (2012). Methodological
guidelines for publishing government linked data.
Available:
https://www.lri.fr/~hamdi/datalift/tuto_inspire_2012/Su
ggestedreadings/egovld.pdf [2017, December 25].
What is a language resource?. n.d. Available:
http://www.elra.info/en/about/what-language-resource/
[2017, November 1].
Wood, D., Zaidman, M., Ruth, L. & Hausenblas, M.
(2014). Linked data: structured data on the web. New
York: Manning Publications Co.
Zgusta, L. (1971). Manual of lexicography. Prague:
Academia, Publishing House of the Czechslovak
Academy of Sciences.
... The English-Xhosa Dictionary for Nurses (EXDN) is a bilingual dictionary of medical terms, authored by Neil MacVicar, a medical doctor, in collaboration with Xhosa-speaking nurses [1] (p. 1). It was published in 1935 in South Africa and is now in the public domain [1] (p. 1). ...
... The English-Xhosa Dictionary for Nurses (EXDN) is a bilingual dictionary of medical terms, authored by Neil MacVicar, a medical doctor, in collaboration with Xhosa-speaking nurses [1] (p. 1). It was published in 1935 in South Africa and is now in the public domain [1] (p. 1). EXDN is unidirectional, with English as the source language and Xhosa, an indigenous Bantu language from the Nguni language group (S40 in Guthrie's classification), the target language [1] (p. 1), [2] (p. ...
... It was published in 1935 in South Africa and is now in the public domain [1] (p. 1). EXDN is unidirectional, with English as the source language and Xhosa, an indigenous Bantu language from the Nguni language group (S40 in Guthrie's classification), the target language [1] (p. 1), [2] (p. ...
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