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Keynote presentation for Euralex, July 8, 2010.
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- 1. Onomasiological dictionaries and ontologies Patrícia Cunha França EURALEX, Leeuwarden, July 8, 2010
- 2. Summary • Introduction • Defining concepts: from onomasiology to ontology • On the differences between dictionaries and ontologies • Similarities between dictionaries and ontologies • Concluding remarks • References
- 3. Introduction • “Among the wide Spectrum of information representation and retrieval tools are thesaurus and ontologies, which are the most often linked in bibliography, even though they come from very different disciplinary areas.” (Arano, 2005)
- 4. Defining concepts • Onomasiology: field, • Onomasiological within Lexicology, that dictionaries: aims “to find the linguistic • ideological dictionary; forms, or the words, that • analogic dictionary; can stand for a given • pictorial dictionary; concept/idea/ • synonym dictionary; object” (Grzega & • conceptual dictionary; Schöner, 2007: 7) • semantic dictionary; • thesaurus. • Onomasiological dictionary: words are grouped by semantic fields; an entry represents a concept.
- 5. • Ontology: multidisciplinary field concerned with the representation of entities that make up the world. • ontologies: representational artifacts that present some kind of relations between concepts. • formal ontology: representational artifact that uses a high degree of formalism to represent entities (OBO Foundry, ontologies built with Protégé). • linguistic ontology: specific kind of ontology that focus on lexical items and presents some kind of linguistic information (WordNet). • conceptualization: the theoretical level of the building process of constructing an ontology.
- 6. • Ontology: multidisciplinary field concerned with the representation of entities that make up the world. • ontologies: representational artifacts that present some kind of relations between concepts. • formal ontology: representational artifact that uses a high degree of formalism to represent entities (OBO Foundry, ontologies built with Protégé). • linguistic ontology: specific kind of ontology that focus on lexical items and presents some kind of linguistic information (WordNet). • conceptualization: the theoretical level of the building process of constructing an ontology.
- 7. • Ontology: multidisciplinary field concerned with the representation of entities that make up the world. • ontologies: representational artifacts that present some kind of relations between concepts. • formal ontology: representational artifact that uses a high degree of formalism to represent entities (OBO Foundry, ontologies built with Protégé). • linguistic ontology: specific kind of ontology that focus on lexical items and presents some kind of linguistic information (WordNet). • conceptualization: the theoretical level of the building process of constructing an ontology. In Ray apud Nickles et al., 2007: 42
- 8. (concertos, entrevistas) e ainda uma parte dedicada aos entusiastas ?ilustração que se segue temos a mesma ontologia representada em OWL, i. Na ADMIRADOR. atributo ‘NAME’). está assente num formato XML61. De notar que este tipo de representação é, na prátic Entre estes conceitos estão representadas várias relações (toca, grava, toca em, Neste modelo também é possível verificar a cardinalidade de todos aos conceitos, gerada automaticamente e informação é geralmente inserida através de um edit participa). gráfico62. Por exemplo, no Protegé, uma das ferramentas usadas para editar ontologia que é dada pelas restrições nas relações entre conceitos. Estas restrições em UML são é apresentada automaticamente um editor XML ao mesmo tempo que é apresentado chamadas multiplicities. Estas multiplicities estão especificadas na forma ‘min..max’ e editor gráfico. estão colocadas no final da linha que representa a relação entre conceitos. Por exemplo, ‘0..n’ na relação ‘PLAYS’ entre a classe ‘MUSICIAN’ e a classe ‘INSTRUMENT’ significa que um membro da classe ‘MUSICIAN’ pode tocar entre nenhum a um número não determinado de instrumentos, em que ‘n’, tal como na Matemática, significa um conjunto de números xemplo de ontologia sobre músicos visualizada como uma rede semântica. Ilustração V I I I – E naturais. ( in GA!EVI", DJURI" E DEVED#I", 2006: 49) Como bem refere"# '()%*+,-# ./0$+,# %# .%*%12+, (2006: 49) a ontologia da +@0>=$(AB!# (C+"(-# %DE$%>>(# %"# @+FG0(G%"# F(=0$(@# H%IGIJ# K:"# "L>+C!# =!C(# 0"# 58 Aqui entende-se conceptualização como sinónimo de teoria lógica, entendida como um conjunto de axiomas e regras de inferência que visam representar formalmente o raciocínio válido. Ilustração X - A ontologia sobre músicos representada em O W L ( in !"#$%&'()*+,-&')$)*$%$*.&', 2006: 50) 49-50 Gaševic, Djuric and Devedžic, 2006: 63 3.2.1.4. Vocabulário usado por uma teoria lógica No que respeita à definição 6, uma ontologia é vista não como uma teoria lógi mas simplesmente como o vocabulário usado por essa teoria. O vocabulário de um teoria lógica pode conter símbolos lógicos (por exemplo , , , />, #, {}, ) Ilustração I X - Modelo U M L da ontologia sobre músicos (letras minúsculas e letras maiúsculas). símbolos não-lógicos ( in !"#$%&'()*+,-&')$)*$%$*.&', 2006: 50). 61 A XML (eXtended Markup Language) é uma linguagem recomendada pela W3C. É uma linguagem
- 9. Na ilustração que se segue temos a mesma ontologia representada em OWL, i. atributo ‘NAME’). está assente num formato XML61. De notar que este tipo de representação é, na prátic Neste modelo também é possível verificar a cardinalidade de todos aos conceitos, gerada automaticamente e informação é geralmente inserida através de um edit gráfico62. Por exemplo, no Protegé, uma das ferramentas usadas para editar ontologia que é dada pelas restrições nas relações entre conceitos. Estas restrições em UML são é apresentada automaticamente um editor XML ao mesmo tempo que é apresentado chamadas multiplicities. Estas multiplicities estão especificadas na forma ‘min..max’ e editor gráfico. estão colocadas no final da linha que representa a relação entre conceitos. Por exemplo, ‘0..n’ na relação ‘PLAYS’ entre a classe ‘MUSICIAN’ e a classe ‘INSTRUMENT’ significa que um membro da classe ‘MUSICIAN’ pode tocar entre nenhum a um número não determinado de instrumentos, em que ‘n’, tal como na Matemática, significa um conjunto de números naturais. Ilustração X - A ontologia sobre músicos representada em O W L ( in !"#$%&'()*+,-&')$)*$%$*.&', 2006: 50) 49-50 Gaševic, Djuric and Devedžic, 2006: 3.2.1.4. Vocabulário usado por uma teoria lógica No que respeita à definição 6, uma ontologia é vista não como uma teoria lógi mas simplesmente como o vocabulário usado por essa teoria. O vocabulário de um teoria lógica pode conter símbolos lógicos (por exemplo , , , />, #, {}, ) Ilustração I X - Modelo U M L da ontologia sobre músicos (letras minúsculas e letras maiúsculas). símbolos não-lógicos ( in !"#$%&'()*+,-&')$)*$%$*.&', 2006: 50). 61 A XML (eXtended Markup Language) é uma linguagem recomendada pela W3C. É uma linguagem
- 10. Na ilustração que se segue temos a mesma ontologia representada em OWL, i. está assente num formato XML61. De notar que este tipo de representação é, na prátic gerada automaticamente e a informação é geralmente inserida através de um edit gráfico62. Por exemplo, no Protegé, uma das ferramentas usadas para editar ontologia é apresentada automaticamente um editor XML ao mesmo tempo que é apresentado editor gráfico. Ilustração X - A ontologia sobre músicos representada em O W L ( in !"#$%&'()*+,-&')$)*$%$*.&', 2006: 50) 49-50 Gaševic, Djuric and Devedžic, 2006: 3.2.1.4. Vocabulário usado por uma teoria lógica No que respeita à definição 6, uma ontologia é vista não como uma teoria lógi mas simplesmente como o vocabulário usado por essa teoria. O vocabulário de um teoria lógica pode conter símbolos lógicos (por exemplo , , , />, #, {}, ) símbolos não-lógicos (letras minúsculas e letras maiúsculas). 61 A XML (eXtended Markup Language) é uma linguagem recomendada pela W3C. É uma linguagem
- 11. Gaševic, Djuric and Devedžic, 2006: 49-50
- 13. On the differences • “A dictionary does not employ a formal language, but rather an informal one: a human natural language. A dictionary is meant to be read and interpreted by humans.” • “A dictionary is descriptive. [...] In contrast, a formal ontology is prescriptive or normative.” • “A term in an ontology is not a word but a concept.” • “Language, as an organic system, does not conform to ontological principles.” Nickles et al, 2007: 43-45
- 14. Dictionaries Ontologies natural language formal language normative and descriptive prescriptive words/linguistic signs concepts/strings semantic and lexical ontological relations relations (real world)
- 16. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43)
- 17. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) • Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5)
- 18. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) • Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5)
- 19. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) • Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) http://www.jessesword.com/dictionary-guardian.gif
- 20. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) • Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5)
- 21. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) • Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5)
- 22. On the similarities • Language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) • Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) • Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- 23. • “All ontologies in information science contain terms. (...) the experts in the various specialized domains of knowledge generally look through the terms. However, an ontology such as WordNet presents a special case, for (if it is to be called an ontology at all) it is an ontology of terms and meaning; it is like a dictionary, not like a taxonomical textbook (...). It is clear that the term ‘cat’ is mentioned and not used in WordNet. Both the scare quotes around the term ‘cat’ and the fact that it is preceded by the term ‘noun’ makes it clear that WordNet contains no talk of real cats” (Johansson, 2008: 303). • What kind of information is being provided with the expression “usually having thick soft fur and no ability to roar” (WordNet).
- 25. Concluding remarks • As many researchers (e.g.: B. Smith, N. Guarino, P. Giaretta and others) have verified, the terms and concepts needed to the work of an ontologist are not clearly defined in recent research. Terms such as “concept”, “word”, “term”, “class”, “category”, “universal”, need to be clearly defined. • Several important theoretical questions are still unsolved. Some of the questions that still need study are, for instance, the clarification of what are the building blocks of an ontology as an artifact and the difference between conceptual, lexical and ontological relations. • A terminological work in the area is urgent. This work must involve a large interdisciplinary collaboration. The importance of Applied Linguistic and Lexicography for the study of ontology is clear. • “Ontology is a burgeoning field, involving researchers from the computer science, philosophy, data and software engineering, logic, linguistics, and terminology domains.” (Smith, 2006)
- 26. References • Arano, S. (2005). Thesaurus and ontologies. [on-line publication]. URL: http:// www.hipertext.net/english/pag1009.html [Access date: 17 September 2009]. • Grzega, J.; Schöner, M. (2007). English and General Historical Lexicology. [on-line publication]. URL: http://www1.ku-eichstaett.de/SLF/EngluVglSW/OnOnMon1.pdf [Access date: 31 October 2009]. • Nickles et al. (2007). “Ontologies across disciplines”. In Shalley, A. & D. Zaefferer (eds.). Ontolinguistics. Berlin: Mouton de Gruyter. 23-70. • Gaševic, D. D. Djuric & V. Devedžic (2006) Model driven architecture and ontology development. Berlin: Springer. • Lacy, L. (2005). Owl: Representing Information Using the Web Ontology Language. Victoria: Trafford. • Green, J. (1996). Chasing the Sun: dictionary and the dictionaries they made. New York: Hanry Holt and Company, Inc. • Johansson, I. (2008). “Bioinformatics and Biological Reality”. In Munn and Smith (eds.). (2008). • Munn, K.; B. Smith (eds.) (2008). Applied Ontology. Frankfurt: Ontos/Verlag. • Smith, B. (2006) “Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain”. [on-line publication]. URL: http://ontology.buffalo.edu/bfo/ Terminology_for_Ontologies.pdf [Access date: 17 September 2009].
Notes de l'éditeur
- Introducing: - Good Morning everyone. I would like to thank you all for being here. I know that you all had a dificult choise to make between two software demonstrations. Thank you for choosing me. I hope I won’t disapoint you. - My name is Patrícia França. I recently finished my Master Degree at the University of Minho in Braga, Portugal and I am currently a research fellow at the same university working in a project in the area of Psycholinguistics, doing computational lexicography. - First of all I would like to say that I am very glad to be here today. It is an honor. - I would like to thank the organizers of Euralex for the oportunity to speak at such an important event and for having been so efficient and helpfull. Thany you so much. - This presentation has for title “Onomasiological dictionaries and ontologies”. It was taken from a chapter of my Master thesis. - There are a lot of concepts, questions, issiues to debate about this subject, but, as you know, this is a student papper and I had some limitations in the number of pages and the time for presentation. - That being said, I will present what I found to be the most important topics of the subject, giving you, in the end, some questions for future work. - What I would do here today is to build bridges between these two representational artefacts and to bring up some discussion between the differences and similarities between the two.
- - I will start with a brief introduction to the theme, with a small presentation of the state of the art. - Then, I will define briefly the concepts of onomasiology and ontology. - It follows a presentation of the main arguments for distinguishing between onomasiological dictionaries and ontologies, followed by a brief refutation of those arguments. - Finally, I will present some suggestions for future work. - And then the bibliography used in this presentation.
- - Over the last decade, there has been an increasing interest in ontologies by the Computer Science and its related disciplines. - Some of the most important theoretical and practical work has been developed in the area of Biomedicine, with the work of Barry Smith from the University of Buffalo in New York and its associates. His work has been focused on building a theoretical framework, with concepts from Philosophy, that has been used as a top-level ontology (ontology independent of its specific domains) for Natural Sciences. It is, by and large a terminological work and has been used successfully in those areas. It has been built an ontology editor based on the top level concepts from Smith’s theoretical work. - In the specific area of Natural Language Processing, several tools like the Wordnet, has been arisen and computational tools are being developed to convert simple language dictionaries into ontologies (In Portuguese language, for instance, there we have the work of Hugo Oliveira from the University of Coimbra, Portugal, that has made available the result of his PHD: the PAPEL (see Linguateca). - Authors like Arano, Moreira et al, Hirst and others have been building bridges between ontologies and dictionaries, arguing that onomasiological dictionaries are simple ontologies. - As Arano argues, “Among the wide Spectrum of information representation and retrieval tools are thesaurus and ontologies, which are the most often linked in bibliography, even though they come from very different disciplinary areas.” (Arano, 2005)
- - To understand the contribution of onomasiological dictionaries to ontologies, we need to clearly define the concepts. One of the main difficulties that has been pointed out to the work that has been developed within ontologies is the lack of a terminological consensus (Smith and Guarino). - In my Master thesis I have tried to find bridges between different disciplines with the aim of building a terminological consensus that allowed different reserchers from different areas to work towards a common goal. - Onomasiology is field, within Lexicology, that aims “to find the linguistic forms, or the words, that can stand for a given concept/idea/object” (Grzega & Schöner, 2007: 7). - An onomasiological dictionary is an artefact where words are grouped by semantic fields; and where an entry represents a concept. - This kind of dictionary has been classified under different names: ideological dictionary; analogic dictionary; pictorial dictionary; synonym dictionary; conceptual dictionary; semantic dictionary; thesaurus. - Nontheless, one uncontroversial example of an onomasiological dictionary is Roget Thesaurus. - All of these categories have been studied within the field of Lexicography and Lexicology. - As for the concept of ontology...
- - As for the concept of ontology, as you might know, comes from Philosophy (and it has been a good surprise to note that a lot of the work being developed within the area has a huge philosophical influence (eg.: the work of Barry Smith). Ontology started to be known in Philosophy as the study of entities that are part of the world. - Nontheless, in computer science, ontologies are defined as computacional artefacts. - We can resume, by and large (and I call your atention to say that these definitions are general definitions that can be found in recent research), the main concepts within ontology to these four: 1) Ontology with the capital letter ‘O’: multidisciplinary area concern with representational of entities that make up the world. In here we find all the research that has been developed (from practical frameworks to parctical artifacts and tools); 2) ontology with small letter, that can be defined as a specific artefact, be it computacional or not. 3) a formal ontology, defined as a representational artefact built with a high degree of formalism (formal language). 4) linguistic ontology, that can be defined as a specific king of ontology (it can be considdered a top-level ontology) that focus, mainly (and I underline this mainly) on lexical items and presents some kind of linguistic information. - We have this chart (by Ray, cited by Nickles et all) that can gives us an idea of diffferent representational artefacts, from glossaries to thesaurus to formal ontologies, developed with formal languages). At the bottom we have what has been considered by Computer science formal ontologies. - We have to be aware here that, a formal ontology does not necessary means that it has been computed using formal language. In computer science, when we talk about formal ontology we are refering to a particular kind of language (like OWL, UML), but, we have to separate the language from its conceptualization (Gruber and Guarino). - A conceptualization can be formal without being represented in a specific language. Like Guarino says, a conceptualization is independent of the language we use. It is the theoretical level. When we have entered our conceptualization into a ontology editor, we are building an computarized ontology, but our conceptualization of our formal ontology was already built.
- - As for the concept of ontology, as you might know, comes from Philosophy (and it has been a good surprise to note that a lot of the work being developed within the area has a huge philosophical influence (eg.: the work of Barry Smith). Ontology started to be known in Philosophy as the study of entities that are part of the world. - Nontheless, in computer science, ontologies are defined as computacional artefacts. - We can resume, by and large (and I call your atention to say that these definitions are general definitions that can be found in recent research), the main concepts within ontology to these four: 1) Ontology with the capital letter ‘O’: multidisciplinary area concern with representational of entities that make up the world. In here we find all the research that has been developed (from practical frameworks to parctical artifacts and tools); 2) ontology with small letter, that can be defined as a specific artefact, be it computacional or not. 3) a formal ontology, defined as a representational artefact built with a high degree of formalism (formal language). 4) linguistic ontology, that can be defined as a specific king of ontology (it can be considdered a top-level ontology) that focus, mainly (and I underline this mainly) on lexical items and presents some kind of linguistic information. - We have this chart (by Ray, cited by Nickles et all) that can gives us an idea of diffferent representational artefacts, from glossaries to thesaurus to formal ontologies, developed with formal languages). At the bottom we have what has been considered by Computer science formal ontologies. - We have to be aware here that, a formal ontology does not necessary means that it has been computed using formal language. In computer science, when we talk about formal ontology we are refering to a particular kind of language (like OWL, UML), but, we have to separate the language from its conceptualization (Gruber and Guarino). - A conceptualization can be formal without being represented in a specific language. Like Guarino says, a conceptualization is independent of the language we use. It is the theoretical level. When we have entered our conceptualization into a ontology editor, we are building an computarized ontology, but our conceptualization of our formal ontology was already built.
- - We here have an example of a simple ontology for the concept ‘musitian’ built with diferent languages: a simple think built with an image editor, UML and OWL. - As we can see, the more formal is the language, it becames less intuitive for human beings. And, as Nickles et al has put it, the great challange today in building ontologies is to be able to achieve the expressive power of fomal languages and, at the same time, present to the users a tool that can be easily read and is user friendly.
- - We here have an example of a simple ontology for the concept ‘musitian’ built with diferent languages: a simple think built with an image editor, UML and OWL. - As we can see, the more formal is the language, it becames less intuitive for human beings. And, as Nickles et al has put it, the great challange today in building ontologies is to be able to achieve the expressive power of fomal languages and, at the same time, present to the users a tool that can be easily read and is user friendly.
- - We here have an example of a simple ontology for the concept ‘musitian’ built with diferent languages: a simple think built with an image editor, UML and OWL. - As we can see, the more formal is the language, it becames less intuitive for human beings. And, as Nickles et al has put it, the great challange today in building ontologies is to be able to achieve the expressive power of fomal languages and, at the same time, present to the users a tool that can be easily read and is user friendly.
- - We here have an example of a simple ontology for the concept ‘musitian’ built with diferent languages: a simple think built with an image editor, UML and OWL. - As we can see, the more formal is the language, it becames less intuitive for human beings. And, as Nickles et al has put it, the great challange today in building ontologies is to be able to achieve the expressive power of fomal languages and, at the same time, present to the users a tool that can be easily read and is user friendly.
- - So, although we can establish some correlation between dictionaries, specially thesaurus and ontologies, it has been argued by Nickles et al and others that they are very different artefacts. - First, they argue that ... “A dictionary does not employ a formal language, but rather an informal one: a human natural language. A dictionary is meant to be read and interpreted by humans”. “A dictionary is descriptive. [...] In contrast, a formal ontology is prescriptive or normative.” “A term in an ontology is not a word but a concept.” “Language, as an organic system, does not conform to ontological principles.” - These are the arguments used to distinguish dictionaries from ontologies. But, if we take for granted that a onomasiological dictionary is a kind of dictionary (and I assume that that is a uncontroversial issue), we have to make some objections to this four arguments.
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Let me now refute the arguments presented previously: 1) In what concerns language. Both ontologies and dictionaries are made to be read by human beings. As Lacy states, “developers of Owl wanted to make the language intuitive for humans and to have sufficient power to describe machine-readable content”. (Lacy, 2005: 43) - The great challenge we face today when thinking about modelling language is this: how can we obtain the expressive power to describe content that can be processed by machines and, at the same time, allow human beings to understand it? 2) Prescriptive/descriptive. There is some prescriptive character in a dictionary. In theory, a dictionary describes the language used by speakers at a specific time and place, but what can be said to the words of Green, referring to Johnson and Webster: “What both men were doing, although neither articulated as such, was playing God”. (Green, 1996: 5) And what can we say about this image. We all have to agree that a dictionary has a prescriptive character. Although we can agree that a dictionary presents the vocabulary of the language users of a particular tome and place, we have to agree that dictionaries have a prescriptive character. WHen we don’t know how to spell a word or when we don’t know waht a word means, we consult the dictionary. It is like an old wise teacher. 3) Concepts/words. Onomasiological dictionaries focus on concepts and not on words. In the same way, ontologies are not only about concepts, but also words (e.g..: linguistic ontologies). As Nickles et al. state, one of the challenges we are facing today in studying language and ontologies is establishing a relation between formal ontologies and linguistic expressions (Nickles et al, 2007: 44).
- Johansson presents another interesting metaphor to distinguish between ontologies and dictionaries. He says “All ontologies in information science contain terms. (...) the experts in the various specialized domains of knowledge generally look through the terms. However, an ontology such as Wordnet presents a special case, for (if it is to be called an ontology at all) it is an ontology of terms and meaning; it is like a dictionary, not like a taxonomical textbook (...). It is clear that the term ‘cat’ is mentioned and not used in WordNet. Both the scare quotes around the term ‘cat’ and the fact that it is preceded by the term ‘noun’ makes it clear that WordNet contains no talk of real cats” (Johansson, 2008: 303).
- When we look for the word ‘bird’ in the WordNet we are presented with a traditional semantic relation called meronym (meronym means part of a whole). And we have - beak, - feather, - wing, - bird’s foot and so on... And I ask myself “Are we looking at the word ‘bird’ (does the word ‘bird’ has in itself all this caracteristics) or are we looking through the word? This question is exactly the same as the old lexicographic question about linguistic information and enciclopedic infomation. I will leave the answer open.
- To close I would like to leave some remarks. The first remark is that we need to clarify the terms with which an ontology has to work. As many researchers (e.g.: B. Smith, N. Guarino, P. Giaretta and others) have verified, the terms and concepts needed to the work of an ontologist are not clearly defined in recent research. Terms such as “concept”, “word”, “term”, “class”, “category”, “universal”, need to be clearly defined. For instance, Pierre Grenon, an author who works with Barry Smith states that: when looking at recent research within the field of ontology we find that ‘concept’ might be taken to be one of the following: (1) an idea or a mental representation of objects in reality; (2) a general idea under which a multiplicity of things fall (let us call these conceptual universals); (3) a Platonic idea existing as a perfect prototype of things in the world, but itself, in some sense, exterior to the world; (4) a class, a set or collection; (5) a word.” (Grenon, 2008). Several important theoretical questions are still unsolved. Some of the questions that still need study are, for instance, the clarification of what are the building blocks of an ontology as an artifact and the difference between conceptual, lexical and ontological relations. A terminological work in the area is urgent. This work must involve a large interdisciplinary collaboration. The importance of Applied Linguistic and Lexicography for the study of ontology is clear. I will finish my presentation with a quote from Barry Smith, that says “Ontology is a burgeoning field, involving researchers from the computer science, philosophy, data and software engineering, logic, linguistics, and terminology domains.” (Smith et al, 2006).
- Thank you for listening. I think we will now open the floor to questions. I will be around if you would like to ask me further questions.