2f:null 30:["$","title",null,{"children":"Combined usage of SKOS and OWL: an experimentation | Figay | Observable"}] 35:T1629,When having to deal with management of terminologies produced a digital way, the question first arises concerning which terminology description language is to be used, which should be in addition a standardized langage. A candidate the **[Simple Knowledge Organisation System](https://www.w3.org/2004/02/skos/intro#skosrdf)** (SKOS), defined by the **World Wide Web Consortium** (W3C). In the area of Knowledge Organisation Systems (KOS), it concerns thesauri, classification schemes, subject heading lists and taxonomies within the framework of the Semantic Web. Being part of the Semantic Web Framework, SKOS is built on top of the Resource Description Framework (RDF). Using SKOS, concepts can be identified using URIs, labeled with lexical strings in one or more natural languages, assigned notations (lexical codes), documented with various types of note, linked to other concepts and organized into informal hierarchies and association networks, aggregated into concept schemes, grouped into labeled and/or ordered collections, and mapped to concepts in other schemes. ## The related Semantic Web specifications The **Ressource Description Framework** ([RDF](https://www.w3.org/RDF/) ) is a standard model for interchange on the Web, facilitating data merging even if the underlying schemas differ. It supports the evolution of schemas over time without requiring all the data consumers to be changed. RDF extends the linking structure of the Web to use URIs to name the relationship between things as well as the two ends of the link (this is usually referred to as a "triple"). Using this simple model, it allow s structured and semi-structured data to be mixed, exposed and shared across different applications. This linking structure forms a directed, labeled graph, where the edges represent the named link between two resources, represented by graph nodes. This graph view is the easiest possible mental model for RDF and is often used in easy-to-understand visual explanations The **Ontology Web Language** ([OWL](https://www.w3.org/OWL/)) is an other W3C specification being part of the Semantic Web Framework. OWL was designed to represent rich and complex knowledge about things, groups of things and relations between things. It is a computational logic-based allowing usage of computer programs to verify the consistency of that knowledge or to make implicit knowledge explicit. OWL documents, known as ontologies, can be published in the Web and may refer to or to be referred from other OWL ontologies. The current version of OWL, also referred to as "OWL 2", was developed by the W3C and published in 2009, with a second edition in 2012. It extends the previous version with new constructs improving mainly the usage of reasoning. [SKOS specifications document](http://www.w3.org/TR/skos-reference/skos.html) defines the **Simple Knowledge Description Framework** in HTML (HTML variant) and is associated to a [RDF representation](http://www.w3.org/TR/skos-reference/skos.rdf) (RDF schema variant). So a terminology in SKOS will be defined as RDF data complying with the SKOS RDF Schema. The specifications also states how to combine usage of SKOS and OWL. Some other schemas are made available. An informative one is provided for the convenience of tools and applications that wish to work within the constraints of OWL DL: the [SKOS RDF Schema - OWL 1 DL Sub-set](http://www.w3.org/TR/skos-reference/skos-owl1-dl.rdf). A complementary vocabulary comes with SKOS named SKOS-XL with an [HTML variant](http://www.w3.org/2008/05/skos-xl#) and a [RDF variant](http://www.w3.org/TR/skos-reference/skos-xl.rdf).SKOS-XL is an appendix to the SKOS recommendation to describe the terms as resources in their own right. Where SKOS alone allows to express properties and relations at the level of abstract concepts, SKOS-XL allows to express assertions and relations between terms, of the type . The use of SKOS-XL remains optional. The SKOS/OWL consistency is also discuss in some papers, such as ["SKOS with OWL: Don’t be Full-ish!"](http://ceur-ws.org/Vol-432/owled2008eu_submission_22.pdf). Various SKOS datasets are available on Internet. A [list](https://www.w3.org/2001/sw/wiki/SKOS/Datasets) which is not necessarily exaustive is provided on the SKOS pages. ## Considered tooling for experimentation **[Protégé](https://protege.stanford.edu/) ** is an open source free reference implementation of an OWL ontology editor, which comes with several plugins for graph visualization (e.g. Ontograph) and for reasoning (e.g. plugin for Pellet reasoner). In order to understand what SKOS is and how it can be used in conjunction with OWL and with an ontology solution, Protégé is a perfect candidate for experimentation. ## The experimentation The performed experimentation is the following: Identification of a taxonomy defined relying on SKOS, with available RDF file containing it. Here our choice is the Digital Europa Thesaurus (DET), defined within the frame of Eurovoc. "EuroVoc is a multilingual, multidisciplinary thesaurus covering the activities of the EU, the European Parliament in particular. It contains terms in 23 official EU languages, plus in three languages of countries which are candidates for EU accession." The DET thesaurus is made available as a SKOS RDF file. We will explore how such a SKOS thesaurus can be used with Protégé, without than with combination with OWL, in order to illustrate the interest of the combined usage. We will also clarify from this experimentation what are the differences between a thesaurus (in SKOS) and an ontology (in OWL). 36:T15ff,** Mapping between SKOS and OWL** Concepts defined in SKOS, which are individuals of SKOS:Concept, can be mapped by mean of SKOS mapping properties. The SKOS mapping properties are skos:closeMatch, skos:exactMatch, skos:broadMatch, skos:narrowMatch and skos:relatedMatch. These properties are used to state mapping (alignment) links between SKOS concepts in different concept schemes, where the links are inherent in the meaning of the linked concepts. As seen previously, some of this concepts can also be considered as OWL Class, as they are defining a group of things having the same properties and for which a concept was defined (e.g. common name in a dictionary). Do we have some equivalent OWL constructs in order to reflect these mapping properties. skos:exactMatch is owl:equivalentClass similar when the concept correspond to a class, and owl:equivalentProperty similar when the concept corresponds to a property. When considering two different domain ontologies, which can be considered as two different skos:conceptScheme instances, they can reflect an mapping between ontology. skos:closeMatch is not transitive, so we don't have similar construct in owl. skos:narrower is OWL subsumption similar within a given ontology, i.e. to sub classes when the considered concept corresponds to a class, and sub property when the considered concept corresponds to a property. skos:narrowMatch is OWL subsumption similar when considering the mapping of two domain ontologies, as the matching concepts belongs to two different schemes. A SKOS concept scheme can be viewed as an aggregation of one or more SKOS concepts. Semantic relationships (links) between those concepts may also be viewed as part of a concept scheme. This definition is, however, meant to be suggestive rather than restrictive, and there is some flexibility in the formal data model stated below. The notion of a concept scheme is useful when dealing with data from an unknown source, and when dealing with data that describes two or more different knowledge organization systems. So it means that it should be possible to derive from an OWL ontology from a given skos:conceptscheme, which will contains all what is inScheme or defined within a given defined set of SKOS resources. Based on the previous defined similarity or equivalence, it will be possible to produce a structured set of OWL classes and properties with some equivalences and subsumptions. When considering several SKOS schemes with mappings, it also means that a derived mapping between the two derived ontologies can also be produced. It doesn't mean that the derivation will be automatic, as it will be highly dependant of the kinds of concepts defined with SKOS, which could be common names, relations or properties, but also many other kind of things such as verbs,etc. In the reverse, producing an ontology in OWL could be easily combined with SKOS for capturing labels more specialized than those proposed by RDF:label (the SKOS labels are specializing RDF:label), and then a SKOS dictionary can be easily derived from the produced OWL file an automated way relying on the established similarities between SKOS and OWL languages constructs. SKOS annotated OWL ontology => consistent SKOS dictionary Some work was already performed concerning SKOS to OWL translation in the past, e.g. by the [Ontology Alignment Evaluation Initiative](http://oaei.inrialpes.fr/2007/skos2owl.html), or the [SKOS2OWL tool](http://www.heppnetz.de/projects/skos2owl/). As produced around 2007, before OWL2, they may be outdated, and the underlying transformation rules may have to be revised, within the context of the production of standards which are SMART. It is also to be considered that producing OWL ontology annotated with SKOS properties is a practice adopted for the production of Reference Data Libraries (ISO 15926 and OASIS PLCS). So it means it is possible to consistently and easily derived a SKOS dictionary from the Reference Data Libraries, constituting a controlled vocabulary for the considered domain. It should also be possible to use such a controlled vocabulary in combination with Natural Language Processing, in order to extract information from some text content allowing to populate a knowledge base or a models repository, or in the reverse to produce some documents derived from a knowledge base and from a model repository. Some work has been performed, as reflected by some articles such as ["SKOS Concepts and Natural Language Concepts: an Analysis of Latent Relationships in KOSs"](http://eprints.rclis.org/31658/1/Mastora-SKOS_KOS_Concepts_NLP.pdf) or within [Ten Ways of Leveraging Ontologies for Rapid Natural Language Processing Customization for Multiple Use Cases in Disjoint Domains](https://www.ronpub.com/OJSW_2020v7i1n03_Erekhinskaya.pdf). The difficulties here will come from the pragmatic related to the production of a textual document, which will have to be aligned with the one related to the considered models, which are not always accurate for narrative (story telling). This is something to be investigated, which is going far beyond the simple study of combined usage of OWL and SKOS. However, when willing to produce standards which are SMART, without creating silos and inconsistencies between the different knowledge artifacts, constituting a framework for producing multiple representations of a same domain of knowledge which are consistent, such investigation is to be performed and some principles and guidelines are to be established, considering that the representations are to be interpreted by people and processed by automates. 37:T97f,# Why a thesaurus isn't an ontology Roughly, an ontology defined, for a given domain of knowledge, classes, as a group of individual sharing common properties. With OWL, relying on descriptive logic, it also provides some constraints which will allows logical consistency checking and inferences when using a reasoning engine. In a dictionary related to natural language, the defined concepts can be of different natures: common names, verbs, etc. What is the closest to an ontology class in such a dictionary is a common name, which can apply to a whole population of things (individuals) responding to the definition of the common name. If similar, it isn't identical, as an entry of a dictionary for a natural language is something allowing to create sentences, according to grammatical rules, and in order to communicate mixing different goals: narrative intent, descriptive intent, etc. As ontology is about how to describe the being, the focus of an ontology is mainly on the descriptive intent. An ontology will allow to structure knowledge and to take advantage of logic for validation and reasoning. It also appears, from the previous experimentation, that an OWL class is usually associated to what SKOS capture as a concept instance, and which is capture when using the SKOS RDF Schema for OWL DL to an OWL individual. Having a resource being at the same time an OWL class and an OWL individual was forbidden in OWL 1. Since OWL 2, this is allowed. It is what is called "punning". However such a mechanism is not well supported by Protégé. Some patterns exist for Ontology Engineering in order to deal with such limitation, in particular separating in different files what concerns a resource considered as a class and what concerns the same resource considered as an individual. So it is possible to reference the SKOS RDF ressources related to the concept instances (without the typing as SKOS concept, and to defined them as OWL class of an ontology when relevant. E.g. we can create an "Abeille" class with the same IRI than than the "Abeille" individual typed as a SKOS Concept in the DET taxonomy. This should not be systematic, as only a subpart of the defined concepts are subject to be an OWL class in an ontology, i.e. some of the common names. We can however illustrates what should be the approach by replacing systematically in the SKOS RDF File of the DET the typing as skos:concept as an owl:class.38:Te4d,

Other ressources

Publicly available thesauri

Thesaurus EUROVOC : © European Union, 2013, http://eurovoc.europa.eu/.
Thesaurus UNESCO : copyright UNESCO, thanks to University of Murcia.
Thesaurus W : propriété des archives de France, données téléchargées ici en mai 2013
Descripteurs New-York Times : Creative Commons Attribution 3.0 United States License, New York Times Company. Données téléchargées ici en mai 2013.
Thesaurus Reegle sur l'énergie : Données téléchargées ici en aout 2013, avec l'accord de l'éditeur.

Some available tools on the market

PoolParty
MarkLogic
SKOSPlay: SKOS Play is an online application for displaying and printing SKOS thesaurus and taxonomies, and convert Excel files to SKOS. This documentation will help you go beyond the online application, to integrate SKOS Play in larger projects where you need to run it from the command line, install a local server, or customize the application.
OpenSKOS
qSKOS: qSKOS is a tool for finding quality issues in SKOS vocabularies. It can be used as command line tool or API. For release information please see the changelog. qSKOS is also the basis for the PoolParty SKOS Quality Checker, an online service that lets you check your vocabularies without needing to locally install qSKOS.Currently we work on integrating qSKOS into the PoolParty Thesaurus Server, a commercially available Web-based development tool for SKOS vocabularies. In it's final stage we combine qSKOS' scientifically-grounded quality checks with the easy-to-use graphical interface of the PoolParty software. Integrated in the development workflow, quality checks can work as an assistive technology, just like syntax-checkers in development environments or spell-checkers in word processing applications.Parts of qSKOS' functionality have also been integrated into the rsine (Resource Subscription and Notification Service) project. It enables you to monitor changes to SKOS vocabularies as soon as they occur and send out immediate notifications (e.g., by email) if some potential quality problems are detected. Rsine is also published as open source and hosted on GitHub (here).

These are the tools (linked to their respective sites) that are involved in the Excel-to-RDF (SKOS) conversion:

SKOS Play Convert
qSKOS
BioPortal
GitHub actions

Some other links

https://2019.semantics.cc/dynaccurate-%E2%80%93-tool-deal-evolution-terminologies-mappings-and-semantic-annotations
http://eulersharp.sourceforge.net/2003/03swap/countries#
https://www.w3.org/2001/sw/wiki/SKOS/Datasets
file:///Users/nicolasfigay/Downloads/Developing_a_web-based_SKOS_editor.pdf
https://www.makeitatriple.com/the-other-nlp/
https://github.com/cmader/qSKOS
https://neo4j.com/developer/graph-data-science/build-knowledge-graph-nlp-ontologies/
https://medium.com/vaticle/text-mined-knowledge-graphs-beyond-text-mining-1ff207a7d850
https://medium.com/vaticle/biomedical-fact-extraction-and-reasoning-knowledge-graphs-from-scientific-text-c5b94f5f5dc9
https://docs.marklogic.com/guide/search-dev/entity

39:T4e6,***[OpenSKOS API invocation](http://openskos.org/api)*** OpenSKOS is a CATCHPlus project. It provides API's on SKOS (Simple Knowledge Organization System). You can either join OpenSKOS as a "tenant" in a SaaS (Software as a Service) construction, or you can download the source code and run your own instance of this software. The OpenSKOS API is a RESTful web service, and it provides a set of predefined HTTP requests, providing HTTP, RDF, JSON or JSONP responses. This section provides a demonstration on how to query the API from observable. * First a CORS proxy selector is defined. * Then the dataURL is to be selected within a list illustrating different queries which can be performed. * Finally, combining the proxy and the dataURL, a url is created which can be provided as parameter to a fetch function, to a d3.json function or to a d3.xml function. Note 1: We are here querying the OpenSKOS tenant, knowing that it can also be envisaged to download the code and to enact on the web our own application, and to have some creation and update requests. Note 2: Several potential proxies are provided, which are to be tested till an appropriate response. Note 3: A notebook can be created with some forms for queries, creation and update.3a:T4a1,The list of defined terms is the following: [SMART](#SMART), [Digital Twin](#DigitalTwin), [Cyber-Physical System](#CPS), [Application Protocol](#ApplicationProtocol), [protocol](#protocol), [communication protocol](#CommunicationProtocol), [ontology](#ontology), [model](#model), [executable model](#ExecutableModel), [schema](#schema), [database schema](#DatabaseSchema), [data dictionary](#DataDictionary), [vocabulary](#Vocabulary), [controlled vocabulary](#ControlledVocabulary), [lexicon](#lexicon), [linguistic](#linguistic), [language](#language), [natural language](#NaturalLanguage), [natural language processing](#NaturalLanguageProcessing), [formal language](#FormalLanguage), [computer language](#ComputerLanguage), [programming language](#ProgrammingLanguage), [modeling language](#ModelingLanguage), [metamodel](#metamodel), [dictionary](#dictionary), [data description language](#DataDescriptionLanguage), [thesaurus](#thesaurus), [documentary thesaurus](#DocumentaryThesaurus), [lexicographic thesaurus](#LexicographicThesaurus), [synonyms](#synonyms), [morpheme](#morpheme), [hyponyms](#hyponyms), [meronyms](#meronyms), [taxonomy](#taxonomy), [semiotics](#semiotics)3b:T767,CommunicationProtocol = md`**communication protocol**: A communication protocol is a system of rules that allows two or more entities of a communications system to transmit information via any kind of variation of a physical quantity. The protocol defines the rules, syntax, semantics and synchronization of communication and possible error recovery methods. Protocols may be implemented by hardware, software, or a combination of both. Communicating systems use well-defined formats for exchanging various messages. Each message has an exact meaning intended to elicit a response from a range of possible responses pre-determined for that particular situation. The specified behavior is typically independent of how it is to be implemented. Communication protocols have to be agreed upon by the parties involved. To reach an agreement, a protocol may be developed into a technical standard. A programming language describes the same for computations, so there is a close analogy between protocols and programming languages: protocols are to communication what programming languages are to computations. An alternate formulation states that protocols are to communication what algorithms are to computation. Multiple protocols often describe different aspects of a single communication. A group of protocols designed to work together is known as a protocol suite; when implemented in software they are a protocol stack. Internet communication protocols are published by the Internet Engineering Task Force (IETF). The IEEE (Institute of Electrical and Electronics Engineers) handles wired and wireless networking and the International Organization for Standardization (ISO) handles other types. The ITU-T handles telecommunication protocols and formats for the public switched telephone network (PSTN). As the PSTN and Internet converge, the standards are also being driven towards convergence.`3c:T58c,model = md`**model**:(4){03782816} [06] S: (n) model#4 (model%1:06:00::), simulation#3 (simulation%1:06:00::) (representation of something (sometimes on a smaller scale)) (WordNet) (1)A model is an informative representation of an object, person or system. The term originally denoted the plans of a building in late 16th-century English, and derived via French and Italian ultimately from Latin modulus, a measure. Representational models can be broadly divided into the concrete (e.g. physical form) and the abstract (e.g. behavioural patterns, especially as expressed in mathematical form). Of particular importance in the modern context, conceptual models are central to philosophy of science, as almost every scientific theory effectively embeds some kind of model of the physical or human sphere. In commerce, a model might instead reference a specific version or configuration of a product offering, rather than functioning as a representation of something else. In taxonomic settings (e.g. biology, architecture, art) a model is sometimes a particular instance of a set of related entities (species, built structures, artistic compositions) chosen as a convenient reference point around which to build discourse; such a model is almost always chosen to typify some central tendency of the group, exemplify the group's defining characteristic, or reify the group's historical lineage. (Wikipedia)`3d:T7e8,DatabaseSchema = md`**database schema**: The database schema is its structure described in a formal language supported by the database management system (DBMS). The term "schema" refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases). The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database.These integrity constraints ensure compatibility between parts of the schema. All constraints are expressible in the same language. A database can be considered a structure in realization of the database language. The states of a created conceptual schema are transformed into an explicit mapping, the database schema. This describes how real-world entities are modeled in the database. "A database schema specifies, based on the database administrator's knowledge of possible applications, the facts that can enter the database, or those of interest to the possible end-users." The notion of a database schema plays the same role as the notion of theory in predicate calculus. A model of this "theory" closely corresponds to a database, which can be seen at any instant of time as a mathematical object. Thus a schema can contain formulas representing integrity constraints specifically for an application and the constraints specifically for a type of database, all expressed in the same database language. In a relational database, the schema defines the tables, fields, relationships, views, indexes, packages, procedures, functions, queues, triggers, types, sequences, materialized views, synonyms, database links, directories, XML schemas, and other elements. A database generally stores its schema in a data dictionary. Although a schema is defined in text database language, the term is often used to refer to a graphical depiction of the database structure. In other words, schema is the structure of the database that defines the objects in the database.`3e:T65b,linguistics = md`**linguistics**: Linguistics is the scientific study of language.It encompasses the analysis of every aspect of language, as well as the methods for studying and modeling them. The traditional areas of linguistic analysis include phonetics, phonology, morphology, syntax, semantics, and pragmatics.Each of these areas roughly corresponds to phenomena found in human linguistic systems: sounds (and gesture, in the case of signed languages), minimal units (words, morphemes), phrases and sentences, and meaning and use. Linguistics studies these phenomena in diverse ways and from various perspectives. Theoretical linguistics (including traditional descriptive linguistics) is concerned with building models of these systems, their parts (ontologies), and their combinatorics. Psycholinguistics builds theories of the processing and production of all these phenomena. These phenomena may be studied synchronically or diachronically (through history), in monolinguals or polyglots, in children or adults, as they are acquired or statically, as abstract objects or as embodied cognitive structures, using texts (corpora) or through experimental elicitation, by gathering data mechanically, through fieldwork, or through introspective judgment tasks. Computational linguistics implements theoretical constructs to parse or produce natural language or homologues. Neurolinguistics investigates linguistic phenomena by experiments on actual brain responses involving linguistic stimuli. Linguistics is related to philosophy of language, stylistics and rhetoric, semiotics, lexicography, and translation.(Wikipedia)`3f:T413,language = md`**language**:Language is the ability to express a thought and communicate by means of a system of signs (vocal, gestural, graphics, tactile, olfactory, etc.) endowed with semantics, and most often with syntax - but it is not systematic (cartography is an example of non-syntactic language). The fruit of an acquisition, language is one of the many manifestations of language. In humans, it is the observed capacity to express a thought and to communicate, among other things, by means of a system of signs by an external support or not. This ability includes linguistic functions such as: * Phonetics (where we can observe the physical actions in the mouth) * Phonology (which designs are present across multiple languages and which are only in a specific language) * Syntax (the representation of sentences and words in the mind just before speaking) * The pragmatics (the definitions that one finds while speaking which are less obvious and pictorial but also typical for those who speak the language in question). (wikipedia)`40:T699,FormalLanguage = md`**formal language** : In mathematics, computer science and linguistics, a formal language is a set of words. The alphabet of a formal language is the set of symbols, letters or lexemes which are used to construct the words of the language; often, it is assumed that this alphabet is finished. The aim of formal language theory is to describe formal languages. Words are sequences of elements of this alphabet; words that belong to a particular formal language are sometimes called well-formed words or well-formed formulas. A formal language is often defined by a formal grammar, such as algebraic grammars, and analyzed by automata. In computer science, formal languages are often used as a basis for the definition of programming languages and other systems; the words of a language then also include a meaning, a semantics. In algorithmic complexity theory, decision problems are generally defined as formal languages, and complexity classes are defined as the sets of formal languages that can be analyzed by machines with limited computational resources. In mathematical logic, formal languages are used to represent the syntax of axiomatic systems, and the formalist attitude in mathematics or logicism asserts that in principle, mathematics can be reduced to the syntactic manipulation of formal languages. The study of formal languages includes all the means of description and analysis of these languages, such as formal grammars for generation and automata for recognition, but it is also interested in machine learning and translation. automatic languages. In the field of translation, language theory applies to programming language compilers.(wikipedia)`41:T9dc,ProgrammingLanguage = md`**programming language**: (1) computer science) a language designed for programming computers (WordNet) (2) A programming language is a conventional notation for formulating algorithms and producing computer programs that apply them. In a way similar to a natural language, a programming language is composed of an alphabet, a vocabulary, grammar rules, meanings, but also a translation environment supposed to make its syntax understandable by the machine. Programming languages make it possible to describe on the one hand the structures of the data which will be manipulated by the computer apparatus, and on the other hand to indicate how the manipulations are carried out, according to which algorithms. They serve as means of communication by which the programmer communicates with the computer, but also with other programmers; the programs usually being written, read, understood and modified by a team of programmers. A programming language is implemented by an automatic translator: compiler or interpreter. A compiler is a computer program which first transforms a source code written in a given programming language into a target code which can be directly executed by a computer, namely a program in machine language or in intermediate code2, while the The interpreter performs this translation "on the fly". Programming languages offer different possibilities of abstraction and a notation close to algebra, making it possible to describe in a concise and easy to understand way the operations of manipulation of data and the evolution of the program flow according to the situations. The possibility of abstract writing frees the programmer's mind from superfluous work, in particular taking into account the specificities of the computer hardware, and thus allows him to concentrate on more advanced problems. Each programming language supports one or more programming approaches - paradigms. The concepts inducing the paradigm are part of the programming language and allow the programmer to express in the language a solution that has been imagined according to this paradigm. The first programming languages were created in the 1950s at the same time as the advent of computers. However, many programming concepts were initiated by one language or sometimes several languages, before being improved and then extended in the following languages. Most of the time the design of a programming language has been strongly influenced by the experience gained with previous languages.`42:T594,metamodel = md`**metamodel** A [metamodel](https://en.wikipedia.org/wiki/Metamodeling) or surrogate model is a model of a model, and metamodeling is the process of generating such metamodels. Thus metamodeling or meta-modeling is the analysis, construction and development of the frames, rules, constraints, models and theories applicable and useful for modeling a predefined class of problems. As its name implies, this concept applies the notions of meta- and modeling in software engineering and systems engineering. Metamodels are of many types and have diverse applications. Meta-models are closely related to ontologies. Both are often used to describe and analyze the relations between concepts. Ontologies: express something meaningful within a specified universe or domain of discourse by utilizing a grammar for using vocabulary. The grammar specifies what it means to be a well-formed statement, assertion, query, etc. (formal constraints) on how terms in the ontology’s controlled vocabulary can be used together. Meta-modeling: can be considered as an explicit description (constructs and rules) of how a domain-specific model is built. In particular, this comprises a formalized specification of the domain-specific notations. Typically, metamodels are – and always should follow - a strict rule set. "A valid metamodel is an ontology, but not all ontologies are modeled explicitly as metamodels". (wikipedia)`43:T936,dictionary = md`**dictionary**: (1) a reference book containing an alphabetical list of words with information about them (WordNet) (2) A [dictionary](https://en.wikipedia.org/wiki/Dictionary) is a listing of lexemes from the lexicon of one or more specific languages, often arranged alphabetically (or by radical and stroke for ideographic languages), which may include information on definitions, usage, etymologies, pronunciations, translation, etc..It is a lexicographical reference that shows inter-relationships among the data. A broad distinction is made between general and specialized dictionaries. Specialized dictionaries include words in specialist fields, rather than a complete range of words in the language. Lexical items that describe concepts in specific fields are usually called terms instead of words, although there is no consensus whether lexicology and terminology are two different fields of study. In theory, general dictionaries are supposed to be semasiological, mapping word to definition, while specialized dictionaries are supposed to be onomasiological, first identifying concepts and then establishing the terms used to designate them. In practice, the two approaches are used for both types. There are other types of dictionaries that do not fit neatly into the above distinction, for instance bilingual (translation) dictionaries, dictionaries of synonyms (thesauri), and rhyming dictionaries. The word dictionary (unqualified) is usually understood to refer to a general purpose monolingual dictionary. There is also a contrast between prescriptive or descriptive dictionaries; the former reflect what is seen as correct use of the language while the latter reflect recorded actual use. Stylistic indications (e.g. "informal" or "vulgar") in many modern dictionaries are also considered by some to be less than objectively descriptive. Although the first recorded dictionaries date back to Sumerian times (these were bilingual dictionaries), the systematic study of dictionaries as objects of scientific interest themselves is a 20th-century enterprise, called lexicography, and largely initiated by Ladislav Zgusta. The birth of the new discipline was not without controversy, the practical dictionary-makers being sometimes accused by others of "astonishing" lack of method and critical-self reflection. (wikipedia)`44:T6f1,thesaurus = md`**thesaurus**: (1)a book containing a classified list of synonyms) (WordNet) (2)A thesaurus (plural thesauri or thesauruses) or synonym dictionary is a reference work for finding synonyms and sometimes antonyms of words. They are often used by writers to help find the best word to express an idea: "to find the word, or words, by which [an] idea may be most fitly and aptly expressed" (Peter Mark Roget, 1852). Synonym dictionaries have a long history. The word 'thesaurus' was used in 1852 by Peter Mark Roget for his Roget's Thesaurus. While some thesauri, such as Roget's Thesaurus, group words in a hierarchical hypernymic taxonomy of concepts, others are organized alphabetically or in some other way. Most thesauri do not include definitions, but many dictionaries include listings of synonyms. Some thesauri and dictionary synonym notes characterize the distinctions between similar words, with notes on their "connotations and varying shades of meaning". Some synonym dictionaries are primarily concerned with differentiating synonyms by meaning and usage. Usage manuals such as Fowler’s A Dictionary of Modern English Usage often prescribe appropriate usage of synonyms. Thesauri are sometimes used to avoid repetition of words, leading to elegant variation, which is often criticized by usage manuals: "writers sometimes use them not just to vary their vocabularies but to dress them up too much". (3)In library and information science, a thesaurus is a kind of controlled vocabulary. A thesaurus can form part of an ontology and be represented in the Simple Knowledge Organization System (SKOS). Thesauri are used in natural language processing for word-sense disambiguation and text simplification for machine translation systems.(Wikipedia)`45:T48c,DocumentaryThesaurus = md`**Documentary thesaurus**: (1) A thesaurus, descriptor thesaurus or [documentary thesaurus](https://fr.wikipedia.org/wiki/Th%C3%A9saurus_documentaire), is an organized list of controlled and standardized terms (descriptors and non-descriptors) representing the concepts of a domain of knowledge. It is a controlled language used for indexing documents and searching for documentary resources in specialized computer applications. Thesauri are therefore one category of documentary languages among others. The terms (in the example opposite: vehicle, ship, etc.) are linked together by relationships of synonymy (equivalent term), hierarchy (generic term and specific term) and association (associated term); each term belongs to a category or domain. (Wikipedia) (2)In information science, a documentary thesaurus is a kind of controlled vocabulary. A thesaurus can be part of an ontology and be represented, for example, in the Simple Knowledge Organization System (SKOS). Thesauri are used in natural language processing for disambiguation of the meaning of words and text simplification for machine translation systems (wikipedia)`46:T49c,taxonomy = md`**taxonomy**: [Taxonomy](https://fr.wikipedia.org/wiki/Taxonomie) is a branch of the natural sciences (renamed biology in the twentieth century), which aims to describe the diversity of living organisms and to group them into entities called taxa in order to identify them (in particular thanks to the determination keys), describe, name and classify them . It constitutes a sub-branch of systematics which aims, first of all, to enumerate and define the kinship links between the different living organisms, and to classify them into hierarchical categories (eg genera, families, orders). These two disciplines are so closely linked that the difference between taxonomy and systematics is not always obvious. Contemporary, evolutionary taxonomy is based on a fundamentally phylogenetic conception of classification, but also on taxonomies for the analysis of empirical elements long ignored by science before the arrival, during the second half of the twentieth century, of the discoveries of molecular biology (Wikipedia). By extension, the term taxonomy is now used in other sciences, such as human and social sciences, information sciences or computer science.`47:T6e8,semiotics = md`**semiotics**: [Semiotics](https://en.wikipedia.org/wiki/Semiotics) (also called semiotic studies) is the study of sign processes (semiosis), which are any activity, conduct, or process that involves signs, where a sign is defined as anything that communicates a meaning that is not the sign itself to the sign's interpreter. The meaning can be intentional such as a word uttered with a specific meaning, or unintentional, such as a symptom being a sign of a particular medical condition. Signs can communicate through any of the senses: visual, auditory, tactile, olfactory, or gustatory (taste). The semiotic tradition explores the study of signs and symbols as a significant part of communications. Unlike linguistics, semiotics also studies non-linguistic sign systems. Semiotics includes the study of signs and sign processes, indication, designation, likeness, analogy, allegory, metonymy, metaphor, symbolism, signification, and communication. Semiotics is frequently seen as having important anthropological and sociological dimensions; for example, the Italian semiotician and novelist Umberto Eco proposed that every cultural phenomenon may be studied as communication. Some semioticians focus on the logical dimensions of the science, however. They examine areas belonging also to the life sciences—such as how organisms make predictions about, and adapt to, their semiotic niche in the world (see semiosis). In general, semiotic theories take signs or sign systems as their object of study: the communication of information in living organisms is covered in biosemiotics (including zoosemiotics and phytosemiotics).Semiotics is not to be confused with the Saussurean tradition called semiology, which is a subset of semiotics. 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33:{"id":"352c18f902d41c9e","slug":"combined-usage-of-skos-and-owl-an-experimentation","title":"Combined usage of SKOS and OWL: an 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usage of SKOS and OWL: an experimentation","cells":[{"id":0,"value":"# Combined usage of SKOS and OWL: an experimentation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":292,"value":"

Introduction

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"$35","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"

Experimentation Step 1: opening a SKOS thesaurus with Protégé

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":306,"value":"First we download the thesaurus in RDF, and we open it using a text editor in order to have a look at its content. We can see that it is is a RDF file with an XML syntax. It provides a set of RDF resources, with types named within the naming space of SKOS: broader, inScheme, narrower, prefLabel, etc.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"FileAttachment(\"DET Thesaurus as text file.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":186,"value":"Figure 1: the textual content of the DET taxonomy: a pure RDF file","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"Then we just open this file with Protégé. Even if not an OWL file, Protégé opens it without problem.\nWhat we can see inside is capture in the following figures.\nThe figure xxx shows some automatically created SKOS classes: Concept, ConceptScheme and Label.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"FileAttachment(\"DET in Protege Created Classes.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":195,"value":"Figure 2: The created classes after import of the SKOS taxonomy in Protégé","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":" The figure xxx shows that in addition some annotation properties are automatically created, corresponding to the properties defined in the DET file. The are prefixed with skos. Not any object properties or data properties are created when important the taxonomy. It is important to understand that only object and data properties can be considered by reasoning tools or even by ontograph for connecting with graph edges the different resources (nodes) of the taxonomy.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"FileAttachment(\"DET in Protege annotations.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":203,"value":"Figure 3: the used SKOS properties as Annotation Properties after import in Protégé","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":50,"value":"We can then navigate in the defined concepts, which are individual of type concepts. In the figure xxx, we can see that they are display by their id, which is not very understandable.\nAll the properties are in the Annotation frame, with the skos name (e.g. skos:prefLabel) and the value (e.g. abandon scolaire).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":54,"value":"FileAttachment(\"DET concepts display with ids.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"Figure 4: the DET defined SKOS concepts after the import in Protégé","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":60,"value":"# Experimentation Step 2: opening a SKOS thesaurus with Protégé with import of SKOS RDF Schema for OWL DL.\nA first thing we can do with Protégé is to change in the \"view\" menu how the content will be rendered by the editor. When selecting \"rendered by annotation property\", all the available annotation property will be proposed, including the SKOS properties. Here we will selected prefLabel, which is a preferred label. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":67,"value":"FileAttachment(\"DET prefLabel for rendering.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":212,"value":"Figure 5: Indicating to Protégé to use skos:prefLabel for content rendering in the Protégé Editor","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":70,"value":"Doing so, resources are rendered by prefLabel in the editor which is quite more readable.\nLet's note that can also parameter the langage to be used with prefLabel, and indicates languages for which the label was made available in the thesaurus.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":78,"value":"FileAttachment(\"DET rendering with prefLabel.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":216,"value":"Figure 6: How the individual are displayed after selecting prefLabel for rendering","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":81,"value":"This work also with Ontograph plugin, which will allow to display the graph of a given query. The following figure shows the result of research of \"abeille\". We can see the concept \"abeille\", and all the properties as annotation properties with the name of the properties and their values.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":85,"value":"FileAttachment(\"DET ontograph display.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":220,"value":"Figure 7: how ontograph display the content after changing the rendering","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":92,"value":"Let's no consider combined usage with ontology. At this stage, even if we can edit the content of the RDF file containing the SKOS taxonomy, we are not really dealing with an ontology.\nFor this, we can rely on a SKOS description in OWL provided by the SKOS community with the SKOS specifications.\nLet's import it (here we make it from a locally downloaded file) in the SKOS taxonomy. Let's not that with the previous exercise, Protégé may have created automatically some annotations for the SKOS properties. They have to be removed from the file in order taking advantage of using OWL Core DL.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":104,"value":"FileAttachment(\"DET Import of skos core dl.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":227,"value":"Figure 8: Importing the SKOS CORE DL in order to study the impact in Protégé","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":108,"value":"So what changed after this import?\nFirst exploring the defined entities, we see that more OWL classes are defined, with some being sub classes of the others, which defined the modeling concepts of SKOS.\n ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":116,"value":"FileAttachment(\"DET after import of SKOS CORE DL.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":231,"value":"Figure 9: the new class hierarchy after important SKOS CORE DL (to be compared with figure 2)","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":121,"value":"The main change is that some of the SKOS properties (but not all with SKOS CORE DL) are now Object Properties.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":127,"value":"FileAttachment(\"DET Object Properties after SKOS CORE DL Import.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":237,"value":"Figure 10: the Object Properties after the import of SKOS CORE DL (it was empty before)","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":129,"value":"It means that now links typed according to these objects properties will be subject to both reasoning, semantic validation or graph display with Protégé (and any other OWL technologies). Let's explore it.\nFirst, if we make the same query on \"abeille\" in Ontograph, we will have quite more in the graph, not only the node \"abeille\" and its type, but also existing links typed according to an object property in the SKOS taxonomy.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":137,"value":"FileAttachment(\"DET ontograph after import of SKOS CORE DL.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":241,"value":"Figure 11: what is displayed in ontograph when querying \"abeille\" after the import of SKOS CORE DL (no edges before)","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":140,"value":"Similarly, if looking at the \"Individual per Class\" pane, and selecting \"abeille\", we can see on the Object Property Frame some of the properties which were previously in the annotation properties pane.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":147,"value":"FileAttachment(\"DET OProperty after SKOS CORE DL import.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":245,"value":"Figure 12: Some SKOS properties as propety assertion (not annotations anymore) after the import of SKOS CORE DL","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"If displaying the Arc types in ontograph, we can see that they correspond to the SKOS language relationships (e.g. inScheme, narrower and related) defined as Object Properties. So we do have a semantic graph here where the fact that SKOS relations between a terminology elements are part of the semantic graph.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":154,"value":"FileAttachment(\"DET Ontograph arcs after SKOS CORE Import.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":249,"value":"Figure 12: New arc types as SKOS relationships in ontograph after the import of SKOS CORE DL","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":159,"value":"In addition, if launching a reasoning engine, it will be possible to validate the logical consistency of the defined terminology and to inferred the implicit links between the taxonomy elements, and to performed some logical queries (DL queries) on top of the constituted knowledge base.\nAs a simple exemple, let's query all the DET terminology elements which are related to \"abeille\". In DL it will be formalize the following way:\ninverse (skos:related) some {abeille}\nDespite the fact that the inverse relation is not explicitly defined in SKOS so capture in the terminology, because we are using a reasoning engine, the tool will give us the result as captured in the next figure.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":165,"value":"FileAttachment(\"DET DL Query after SKOS CORE DL import with Pellet.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":253,"value":"Figure 13: Ability for launching DL Queries when reasoner is launched after the import of SKOS CORE DL","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":787,"value":"$36","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":330,"value":"$37","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":398,"value":"FileAttachment(\"DET SKOS tranformed as ontology@1.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":414,"value":"Figure 15: Brut ForceTransformation of the thesaurus as an ontology","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":401,"value":"We can see here that we still have all the SKOS properties. However they are now attached to classes and not anymore to individuals typed as skos:concepts. The arising question is to define what are the relevant concepts which should become classes. Also some kind of skos links between concepts should become object properties within the ontology.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":390,"value":"So even if relying on a description of SKOS in OWL and using an ontology editor in order to edit and manipulate the SKOS thesaurus, what is finally produced is not an ontology: it is a thesaurus. However, links can be established between thesauri and ontologies, and implemented a consistant way relying on patterns related to the usage of semantic web technologies.\n\nExploring more on details the conditions for thesaurus concepts instance to be an ontology class, and how to publish an ontology class definition as part of the thesaurus with global consistency is something required in order providing consistent digital assets sets including business vocabularies, thesauri and ontologies. The link should also be established concerning how to derive consistently software artefacts such as schemas for databases, file documents or file models.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":257,"value":"

Conclusion

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":173,"value":"In this article, we described an experimentation aiming at clarifying relationships between thesauri and ontologies, relying on the combined usage of SKOS and OWL.\n\n1- we were able to open and edit a SKOS taxonomy in RDF with Protégé\n\n2- Importing SKOS OWL DL, we were able to take advantage of reasoning and semantic graph drawing on top of the taxonomy, but still working on a taxonomy.\n\nThe following figures show what were the differences opening the SKOS thesaurus standalone and opening the SKOS thesaurus importing the SKOS OWL DL definition: in terms of classes and properties structures (figure 14), in terms of semantic graphs drawing with ontograph (figure 15) and in terms of Descriptive Logic querying (figure 16).\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":359,"value":"FileAttachment(\"SKOS properties with and without SKOS DL.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":371,"value":"Figure 15: Impact on importing SKOS DL in Protégé in terms of Object properties versus Annotations\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":362,"value":"FileAttachment(\"SKOS Ontograph with and without SKOS DL.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":375,"value":"Figure 16: Impact of import of SKOS DL in terms of semantic graph visualisation with Ontograph","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":365,"value":"FileAttachment(\"SKOS Logical Querying with SKOS DL.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":379,"value":"Figure 17: Impact of import of SKOS DL in terms of support of DL queries with implicit made explicit","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":353,"value":"But the experimentation also illustrated that a thesaurus isn't an ontology. However, we can easily combine the usage of SKOS and OWL using an ontology editor, and work on such environment at clarifying how we can related ontologies and thesauri a consistant way.\n\nIn particular, SKOS OWL DL being informative, it could be required to adapt and extend it for better consistency of related thesauri and ontologies.\n\nIt will be investigated in future articles.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":264,"value":"

References

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":272,"value":"

Resources directly used in the experimentation

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"

Here are some links to SKOS definition with OWL, coming from https://www.w3.org/2004/02/skos/vocabs:

These files are OWL 1.1 files in RDF-XML, and their production is highly related to the SKOS specifications which discusses the combined usage of SKOS and OWL.

\n ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"$38","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":180,"value":"nonMaxWidth = html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1174,"value":"nonMaxWidthLi = html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":319,"value":"nonMaxWidthTitle = html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":808,"value":"

AnnexesAnnex 1: OpenSKOS

Note: the remote access to OpenSKOS content may not work due to some access restriction of you company. It is part of what is to be considered when willing to publish Notebook accessing to remote data source for exploiting them.

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":465,"value":"$39","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":657,"value":"myTerm = \"person\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":740,"value":"labels2 = {\n return d3.json(url2);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":661,"value":"**** Autocomplete with myTerm providing a set of labels:****","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":674,"value":"labels = {\n var t = [];\n labels2.forEach(function (label) {\n t.push({ Label: label });\n });\n\n return t;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":712,"value":"viewof table3 = Inputs.table(labels)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":735,"value":"viewof selectedLabel = Inputs.select(labels2, {\n label: \"Select a label to be research on OpenSKOS\",\n value: \"\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":747,"value":"labelURL = proxy +\n \"http://openskos.org/api/find-concepts?q=prefLabel:%22\" +\n selectedLabel +\n \"%22&fl=uri&format=json\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":756,"value":"response2 = {\n return d3.json(labelURL);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":768,"value":"viewof table6 = Inputs.table(response2.response.docs)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":770,"value":"viewof selectedURI = Inputs.select(response2.response.docs[1], {\n label: \"Select a URI to be research on OpenSKOS\",\n value: \"\"\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":645,"value":"****Query Response:****","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":480,"value":"response = {\n return d3.json(url);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":637,"value":"****Institutions query response:****","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":617,"value":"institutions = {\n var table3 = [];\n if (dataURL === \"http://openskos.org/api/institutions?format=json\") {\n table3 = Inputs.table(response.institutions, {});\n return table3;\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":641,"value":"****Collections query response:****","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":634,"value":"collections = {\n var table4 = [];\n if (dataURL === \"http://openskos.org/api/collections?format=json\") {\n table4 = Inputs.table(response.collections, {});\n return table4;\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":507,"value":"viewof proxy = Inputs.select(\n [\n \"\",\n \"https://cors-anywhere.herokuapp.com/\"\n ],\n {\n label: \"Select CORS proxy if fetch fails\",\n value: \"https://cors-anywhere.herokuapp.com/\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":529,"value":"viewof dataURL = Inputs.select(\n [\n \"http://openskos.org/api/autocomplete/\" +\n myTerm +\n \"?searchLabel=\" +\n searchLabel +\n \"&returnLabel=\" +\n returnLabel,\n \"http://openskos.org/api/find-concepts?q=prefLabel:%22Dood%20Paard%22&fl=uri&format=json\",\n \"http://openskos.org/api/find-concepts?q=\" + myTerm + \"&format=json\",\n \"http://openskos.org/api/find-concepts?q=status:approved&format=json\",\n \"http://openskos.org/api/collections?format=json\",\n \"http://openskos.org/api/institutions?format=json\"\n ],\n {\n label: \"Select OpenSKOS query\",\n value: \"http://openskos.org/api/collections?format=json/\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":563,"value":"lang = \"fr\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":565,"value":"searchLabel = \"prefLabel\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":570,"value":"returnLabel = \"prefLabel\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":510,"value":"url = proxy + dataURL","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":665,"value":"autocompleData = \"http://openskos.org/api/autocomplete/\" + myTerm","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":671,"value":"url2 = proxy + autocompleData","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":514,"value":"fetch(url).then((response) => response.json())","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":604,"value":"**Installing an OpenSKOS server**\n\nThe application is made available on Github. The most appropriate way for quickly experimenting deploying our own server seems to be through relying on docker (cf. [Development Using Docker](https://github.com/OpenSKOS/OpenSKOS#8-development-using-docker) )","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":831,"value":"## Annex 2: Some definitions about the used terms\nWhen talking about SKOS or Ontology within the context of manufacturing data standardization (the assessment here is made within the context of the manufacturing standards which are SMART in order to support digital twins and virtual manufacturing), some vocabulary is to be defined in order to understand clearly what we are talking about (different domains of knowledge are to be combined).\n\nThis section provides some definitions, extracted from different sources: WordNet (the most simple and general) and then Wikipedia. In some case, this is extended from more specialized resources when having to go more in details for the purpose of combined usage of SKOS and OWL. This is also a way to illustrate which kind of content we can find inside WordNet and Wikipedia, not always sufficient when willing to enter on technical details.\n\nThis could be a starting point for defining a dedicated glossary for supporting activities related to standards which are SMART.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1022,"value":"$3a","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":813,"value":"SMART = md`\n**SMART**: Standards that are Machine Applicable, Readable and Transferable (SMART)\nA set of requirements authored and published digitaly\n* Opportunity to use them as databases\n* Directly integrable in IT Systems\n* Directly implementable as digital processes\n* Always up to date\n* Rapidly deployed at large scale\n* Digital validation et verification méthods\n* Fit for your IA, Big Data, DigitalTwin, …\n* Standards requirements for Digital Twin\n* Digital certification\n* Information models, data dictionaries\n* interoperability needs\n* machine 2 machine (M2M)\n* Automated standards updates\n* Interoperability needs, cyber, trust\n* Digital certification\n* ontologies , trust\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":841,"value":"DigitalTwin = md`**Digital Twin**: A Digital Twin is an organized set of digital models representing a real-world entity to respond to specific problems and usage. The Digital Twin is updated in relation to reality, at a frequency and precision fitting the above problems and usage.\nThe Digital Twin is equipped with advanced operating tools to understand, analyze, predict or optimize the operation and control of the real entity.We can add that\n* the real world entity will sometime be a cyber-physical system\n* There will be data and IT and communication infrastructure involved`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":844,"value":"CPS = md`**cyber-physical system**: A cyber-physical system (CPS) is a system in which a mechanism is controlled or monitored by computer-based algorithms. In cyber-physical systems, physical and software components are deeply intertwined, able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioral modalities, and interact with each other in ways that change with context.\nExemple of Cyber-physical systems are :\n* Internet of Things (IoT)\n* Industrial Internet\n* Smart Manufacturing\n* Smart Cities\n* Smart Grid\n* Smart\" Anything (e.g., Cars, Buildings, Homes, Hospitals, Appliances)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":851,"value":"ApplicationProtocol = md`**application protocol**:\n(ISO 10303)\nA communication protocol between application, at the application layer (proposed by NFI)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":987,"value":"protocol = md`**protocol**: {06677853} [10] S: (n) protocol#1 (protocol%1:10:01::), communications protocol#1 (communications_protocol%1:10:00::) ((computer science) rules determining the format and transmission of data)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":982,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":886,"value":"ontology = md`**ontology**:\n\n(1) (computer science) a rigorous and exhaustive organization of some knowledge domain that is usually hierarchical and contains all the relevant entities and their relations (WordNet)\n\n(2) The metaphysical study of the nature of being and existence (WordNet)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":969,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":992,"value":"ExecutableModel = md`**executable model**:\nWithin the model-driven engineering field, the concept of \"i-DSML\" (interpreted Domain Specific Modeling Language) refers to executable models which are interpreted through an engine. ()[https://hal-univ-pau.archives-ouvertes.fr/hal-01909100]`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":881,"value":"schema = md`**schema**:\n\n(1){05936599} [09] S: (n) schema#1 (schema%1:09:01::), scheme#4 (scheme%1:09:01::) (an internal representation of the world; an organization of concepts and actions that can be revised by new information about the world) (WoldNet)\n\n(2) The word schema comes from the Greek word σχῆμα (skhēma), which means shape, or more generally, plan. The plural is σχήματα (skhēmata). In English, both schemas and schemata are used as plural forms.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":861,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":896,"value":"DataDictionary = md`**data dictionary**: A [data dictionary](https://en.wikipedia.org/wiki/Data_dictionary), or metadata repository, as defined in the IBM Dictionary of Computing, is a \"centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format\". Oracle defines it as a collection of tables with metadata. The term can have one of several closely related meanings pertaining to databases and database management systems (DBMS):\n* A document describing a database or collection of databases\n* An integral component of a DBMS that is required to determine its structure\n* A piece of middleware that extends or supplants the native data dictionary of a DBMS (Wikipedia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":959,"value":"vocabulary = md`**vocabulary**:\n\n(1) a listing of the words used in some enterprise (WordNet)\n\n(2) a language user's knowledge of words (WordNet)\n\n(3)A vocabulary is a set of familiar words within a person's language. A vocabulary, usually developed with age, serves as a useful and fundamental tool for communication and acquiring knowledge. Acquiring an extensive vocabulary is one of the largest challenges in learning a second language. (Wikipedia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":901,"value":"ControlledVocabulary = md`**controlled vocabulary**:A [controlled vocabulary](https://fr.wikipedia.org/wiki/Vocabulaire_contr%C3%B4l%C3%A9) is a lexicon whose goal is to make it possible to organize knowledge in order to optimize the search for information. Controlled vocabulary is used in schemas for subject indexing, subject headings, thesauri and taxonomies. A controlled vocabulary requires the use of predefined terms, which have been preselected by the vocabulary designer. They are therefore opposed to natural language, where no restriction exists as to the choice of vocabulary. (Wikipedia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":964,"value":"lexicon = md`**lexicon**: (linguistic) A lexicon is the vocabulary of a language or branch of knowledge (such as nautical or medical). In linguistics, a lexicon is a language's inventory of lexemes. The word lexicon derives from Greek word λεξικόν (lexikon), neuter of λεξικός (lexikos) meaning 'of or for words'.Linguistic theories generally regard human languages as consisting of two parts: a lexicon, essentially a catalogue of a language's words (its wordstock); and a grammar, a system of rules which allow for the combination of those words into meaningful sentences. The lexicon is also thought to include bound morphemes, which cannot stand alone as words (such as most affixes). In some analyses, compound words and certain classes of idiomatic expressions, collocations and other phrases are also considered to be part of the lexicon. Dictionaries represent attempts at listing, in alphabetical order, the lexicon of a given language; usually, however, bound morphemes are not included. (Wikipedia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":856,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":906,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":938,"value":"NaturalLanguage = md`**natural language**: a human written or spoken language used by a community; opposed to e.g. a computer language (WordNet)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":954,"value":"NaturalLanguageProcessing = md`**Natural Language Processing**: Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of \"understanding\" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":911,"value":"$40","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":944,"value":"ComputerLanguage = md`**computer language**: computer-oriented language#1 (computer-oriented_language%1:10:00::), machine language#1 (machine_language%1:10:02::), machine-oriented language#1 (machine-oriented_language%1:10:00::) (a programming language designed for use on a specific class of computers)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":924,"value":"$41","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":949,"value":"ModelingLanguage = md`**modeling language**: A modeling language is any artificial language that can be used to express information or knowledge or systems in a structure that is defined by a consistent set of rules. The rules are used for interpretation of the meaning of components in the structure. (Wikipedia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":974,"value":"$42","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":871,"value":"$43","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":931,"value":"DataDescriptionLanguage = md`**data description language**:\n(SQL) In the context of SQL, data definition or data description language (DDL) is a syntax for creating and modifying database objects such as tables, indices, and users. DDL statements are similar to a computer programming language for defining data structures, especially database schemas. Common examples of DDL statements include CREATE, ALTER, and DROP. (wikipedia)\nXML Schema is an example of a DDL for XML.\nJSON Schema is an example of a DDL for JSON.\nEXPRESS is an example of a DDL for STEP Application Protocol Information models`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":837,"value":"$44","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":866,"value":"$45","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":876,"value":"LexicographicThesaurus = md`**Lexicographic thesaurus**: A thesaurus or analog dictionary is a reference work in which words are organized by lexical field, where synonyms and antonyms of words can be found. They are intended for people who write, to help find the best word to express an idea. (Wikipédia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1045,"value":"synonyms = md`**synonyms**: A [synonym](https://en.wikipedia.org/wiki/Synonym) is a word, morpheme, or phrase that means exactly or nearly the same as another word, morpheme, or phrase in a given language. For example, in the English language, the words begin, start, commence, and initiate are all synonyms of one another: they are synonymous . The standard test for synonymy is substitution: one form can be replaced by another in a sentence without changing its meaning. Words are considered synonymous in only one particular sense: for example, long and extended in the context long time or extended time are synonymous, but long cannot be used in the phrase extended family. Synonyms with exactly the same meaning share a seme or denotational sememe, whereas those with inexactly similar meanings share a broader denotational or connotational sememe and thus overlap within a semantic field. The former are sometimes called cognitive synonyms and the latter, near-synonyms, plesionyms or poecilonyms. (wikipedia)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1049,"value":"morpheme = md`**morpheme**: A morpheme is the smallest meaningful lexical item in a language. A morpheme is not necessarily the same as a word. The main difference between a morpheme and a word is that a morpheme sometimes does not stand alone, but a word, by definition, always stands alone. The field of linguistic study dedicated to morphemes is called morphology. In English, when a morpheme can stand alone, it is considered a root because it has a meaning of its own (such as the morpheme cat). When it depends on another morpheme to express an idea, it is an affix because it has a grammatical function (such as the –s in cats to indicate plurality). However this definition is not universal and it does not apply to, e.g. Latin where many roots cannot stand alone. For instance, the Latin root reg- (king) must always be suffixed with a case marker: rex (reg-s), reg-is, reg-i, etc. In a language like Latin, a root can be defined as the main lexical morpheme of a word.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1033,"value":"hyponyms = md`**hyponyms**: In linguistics, hyponymy (from Greek ὑπό, hupó, \"under\", and ὄνυμα, ónuma, \"name\") is a semantic relation between a hyponym denoting a subtype and a hypernym or hyperonym denoting a supertype. In other words, the semantic field of the hyponym is included within that of the hypernym. In simpler terms, a hyponym is in a type-of relationship with its hypernym. For example: pigeon, crow, eagle, and seagull are all hyponyms of bird, their hypernym; which itself is a hyponym of animal, its hypernym. Hypernymy or hyperonymy (from Greek ὑπέρ, hupér, \"over\", and ὄνυμα, ónuma, \"name\") is the converse of hyponymy. Other names for hypernym include umbrella term and blanket term.A synonym of co-hyponym based on same tier (and not hyponymic) relation is allonym (which means \"different name\").A hyponym refers to a type. A meronym refers to a part. For example, a hyponym of tree is pine tree or oak tree (a type of tree), but a meronym of tree is bark or leaf (a part of tree).`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1030,"value":"meronyms = md`**meronyms**: In linguistics, meronymy (from Greek μέρος, méros, \"part\", and ὄνυμα, ónuma, \"name\") is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym is in a part-of relationship with its holonym. For example, finger is a meronym of hand which is its holonym. Similarly, engine is a meronym of car which is its holonym. Holonymy (from Greek ὅλος, hólos, \"whole\", and ὄνυμα, ónuma, \"name\") is the converse of meronymy. A closely related concept is that of mereology, which specifically deals with part–whole relations and is used in logic. It is formally expressed in terms of first-order logic. A meronymy can also be considered a partial order.A meronym refers to a part. A hyponym refers to a type. For example, a meronym of tree is bark or leaf (a part of tree), but a hyponym of tree is pine tree or oak tree (a type of tree).`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":891,"value":"$46","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":916,"value":"$47","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W48","stdlib":"1","titling":"auto"}} 34:"$33:body"