Švietimo ir mokslo terminų žodynas ir ontologija

5 6 Irena Markievicz, Erika Rimkutė | Dictionary of Educational and | ir ontologija Scientific Terms Dictionary of Educational and Scientific Terms and Ontology IRENA MARKIEVICZ, ERIKA RIMKUTĖ KEY WORDS: textbook, educational and Vytauto Didžiojo universitetas scientific terms, ontology, dictionary INTRODUCTION In 2010–2012, the Computer Linguistics Centre of Vytautas Magnus University carried out the project Automatic Identification of Educational and Scientific Terms (HUNT 2), funded by the Lithuanian Science Council. The main objective of this project is to test textbook linguistics methods to enable automatic or semi-automatic recognition of terms, automate the selection of information necessary to formulate term definitions in the text and thus facilitate the work of terminologists. The most important results of the research, in addition to the methodologies, are the special textbook of education and science (hereinafter referred to as E&S) (its size – 4 million words), the Dictionary of Education and Science Terms prepared on the basis of this special textbook and the Ontology of Education and Science Terms. The article presents the glossary of ML terms and the ML term ontology. It is written about the structure of the dictionary, its differences from other dictionaries of terms. More attention is paid to the ontology of ML terms. It explains how ontologies are defined in different branches of science, why they are needed, what methods are used to create them. The ontologies of ML terms are discussed in detail, its structure is presented, examples are given, and how this source can be applied is explained. Both works – both the glossary of terms of the ML and the ontologies of terms of the ML – were prepared on the basis of the same material, i.e. the specialized ML textbook, using the methodology of textbooks and computer linguistics. This thesis aims to present the possibilities of textbooks and computer linguistics in the field of terminology, to draw the attention of terminologists, term dictionaries or database creators to the fact that it is possible to at least partially automate the management of terms, that it is possible to harmonize the prescriptive and descriptive method of term analysis. 5 7Terminology | 2013 | 20 STAGES OF THE COMPOSITION OF THE EDUCATION AND SCIENCE TERMINOLOGY DICTIONARY The terms of the Education and Science Terms Dictionary are established in specialized texts by applying linguistic methods (for more details see Grigonytė et al. 2011; Rimkutė 2012). The compilation of the dictionary took two years, i.e. while the project mentioned in the introduction was being carried out, in the following stages: 1) a specialized textbook of 4 million words has been compiled; 2) the text is automatically morphologically annotated; 3) a tool for automatic selection of terms based on linguistic rules has been developed; 4) defined criteria for the selection of possible terms; 5) about 11 thousand possible terms consisting of one to fifteen words have been identified; 6) apply additional criteria for the selection of possible terms1; 7) nustatyta 780 ŠM terminų (1–5 žodžių); 8) methodology for definition of terms based on textbooks; 9) developing the linguistic resources necessary for the definition of terms; 10) define 300 terms of selected groups; 11) the equivalents of the defined terms in English, German, French. There is no doubt that the compilation of each dictionary of terms requires a lot of time and financial resources of specialists. This article presents a glossary of terms of the HM, although it is small – it contains 224 terms (for more details see the next section), but methodologically very complex. As can be seen from the steps described above, even with a specialized textbook2, special tools3 were needed to automatically recognize and identify terms. 1 Analyze terms not longer than seven words; Frequency was also taken into account: the shorter the term, the more frequently it must be used, for example, only one-word terms that were used at least 20 times were analyzed, while seven-word terms had to be used at least twice. 2 Compilation of the textbook – one of the most important and longest stages of the whole research, because in order to compile a representative textbook, in which it would be possible to determine the terms, it was necessary to carefully select the texts, balance them in terms of genre, arrange them technically (transfer from pdf files to text files, change the encoding, etc.). 3 In this project, a tool for the automatic identification of terms was developed for the Lithuanian language, because, as previous experiments (see Grigonytė et al. 2011) show, it is almost impossible to adapt the term recognition tools for other languages to the Lithuanian language due to language structure differences. This tool used linguistic rules: searched for terms with a certain grammatical structure, e.g. adjective + noun, noun's origin + noun, participle + noun, etc. Similar methods are used by Latvian language researchers (see Gornostay et al. 2012; Krugļevskis et al. 2005). According to them, the definition of terms using linguistic methods (morphosyntactic analysis) is more appropriate than statistical methods suitable for analytical languages. 5 8 Irena Markievicz, Erika Rimkutė | Dictionary of Educational and Scientific Terms | ir ontologija It was also difficult to select the terms of the ML from all the automatically determined meaningful and regular grammatical structure compounds. The difficulties arose from the fact that 11 thousand so-called possible terms were identified from a textbook of 4 million words. In the next stage of the research and the compilation of the dictionary it was important to identify the terms of HM from all compounds (Rimkutė 2012 writes about this problem). It should be noted that the presented glossary of terms of the HM is based on the textbook. This means that the traditional, yet still widespread in Lithuania, prescriptive method of terminology management based on the competence of terminologists, which is sometimes quite subjective, was not used, but the descriptive method of terminology analysis and definition based on textbook data is considered superior in modern terminology. Texts for dictionaries are very necessary, because they can identify the most typical, most common patterns of usage of terms, which are important for defining the meaning, for selecting relevant examples. Due to the complexity of the methodology for defining terms, it was decided apibrėžti 300 terminų. Atsirinkti tam tikrų grupių terminai: terminai su to use in detail the word academic (e.g., academic freedom, academic ethics, academic hour), the word work (e.g., thesis, homework, independent work), the word education (e.g., university education, general education, higher education), the word education (e.g., education provider, adult education, non-formal education), etc. Some commonly used terms are also defined: student, scientist, university, etc. As in other dictionaries, most of the terms in the HM dictionaries have equivalents in English, German and French. They are collected from approved sources of the defined field, documents, specialized term databases: English language education term dictionary (Glossary of European Qualifications Educational Terms), Aiškinamojo su studijomis susijusių terminų žodyno, Der Framework for Lifelong Learning, EuroVoc (multilingual thesaurus of the European Union), the term bank of the Republic of Lithuania, etc. The main reference was to the educational terminology of Great Britain, France and Germany, but the meaning of many translation equivalents in the context of the system of these countries is not exactly the same as the original terms used in the Lithuanian education and science field. The equivalents of the terms in the dictionary in foreign languages are applicable to the science and education system of the Republic of Lithuania and may not always (or partially) be applicable to the system of another country. mokslo ir švietimo sistemai apibūdinti. 5 9Terminology | 2013 | 20 THE TERMINOLOGY DICTIONARY OF EDUCATION AND SCIENCE CONVENTION The Ministry of Education and Science dictionary of terms is freely available on the Internet at the address http:// The number of defined kantas.vdu.lt/moksliniai-terminai/. Čia pateikti 224 terminai, nors anksterms differs from the number of terms in the glossary because it has been observed that some terms (e.g. science / research degree; science / scientific output; postgraduate / master's studies; student learning / nimai, they are similar in structure, so such terms are combined. The glossary of terms of the darbo krūvis; valstybės / valstybinis mokslo institutas) vartojami kaip sinoMinistry of Education contains the necessary parts for all glossaries of terms, i.e. the term itself, its definition. As mentioned above, the equivalents in English, German and French are given. Subject areas (e.g. higher education management, higher education policy, higher education administration) and abbreviations of some terms are also provided. The dictionary differs from other dictionaries or databases of terms in that it also lists all the verbal forms of terms with frequencies and the general frequency of terms in the text of the dictionary. All terms are accompanied by at least two examples of usage from the HM textbook (examples are unedited, unchanged, only occasionally abbreviated), left and right collocates4, concordance5. Not all terms were sufficiently defined by the textbook. For those terms for which there was insufficient information to formulate definitions (e.g.: education provider, student basket, basic education), stars marked. Since the terms were chosen from the textbook, it was known how often they were used, so the frequency of all terms is indicated by convention: êêê is shown next to the most common terms, which are used up to 500 times in educational and scientific textbook; êêê is displayed next to less common terms that are used 100–499 times in the text; 4 These are the contextual partners of the analyzed term, which are determined statistically (by frequency) and often appear next to the term from the left and right sides. 5 These are instances of all grammatical forms of the selected term from the textbook, presented in the context of a single line (a concordance line usually includes more than one sentence). Concordance is usually analyzed by reading it first vertically, because this is the only way to highlight the typical usage of the term. The analyzed term is presented in the middle of the concordance line, it is emphasized. For the analyzed term, there are approximately 50-character concordance excerpts from the left and from the right. To see a longer concordance excerpt (approximately 150 characters from left to right), click on the plus sign at the end of the concordance line. 6 0 Irena Markievicz, Erika Rimkutė | Education and Science Terms | ir ontologija Dictionary êêê is displayed next to terms that are used 10–99 times in the text; êêê is shown next to rare terms that are used less than 10 times. The following is a bachelor's study article of the term as an illustration of the glossary of terms. BACHELOR STUDIES Definition First-cycle studies in higher education, providing general university education and the basis of knowledge of the chosen field of study and a qualifying bachelor's degree. Pavyzdžiai It is common in US universities that more gifted students are given the opportunity to combine master's and doctoral studies, more precisely - to enter the doctoral program immediately after bachelor's studies (this to some extent explains why master's and doctoral studies are combined in one term - graduate studies, which are conducted in the so-called graduate school) and to obtain a PhD degree after 8 years of study at the university. Recommended period in conjunction with bachelor's studies - 5 years Bachelor's studies (stage I) usually last 4 years (160 credits, full-time studies). Bachelor’s, Master’s and PhD studies are concluded with the defence of the Bachelor’s thesis, Master’s thesis and dissertation, respectively. Bachelor’s studies are first-cycle studies providing general university education and the basis of knowledge of the chosen field of study. Frequency of bachelor studies 21 bachelor studies 6 bachelor studies 3 bachelor studies 7 bachelor studies 14 Total frequency: 51 Correspondences English: bachelor’s studies In German: Bachelorstudium French: études de licence Subject area Higher Education Administration 6 1Terminology | 2013 | 20 Kolokatai Left Colocates Right Colocates After Bachelor's Degree With Bachelor's Degree TRUMPINTI bakalauro studijas SOFTWARE FOR BACHELOR STUDIES BACHELOR STUDIES I. LEVEL BACHELOR STUDIES MASTER AND DOKTORANTURE Concordance6 [1] work activity or continue and complete their studies. Education representativeor circulated a message, + Bachelor of Higher [2] in countries offering such bachelor's degrees. Bachelor’s 4th year autumn studies o postgraduate semester, [3] theology study studies + programme – 5 years); to study it, and in 2009 Universities + Bachelor were admitted 1,870 students [4] universities decided to 3 and 3, 5 years to shorten Science and the study, the study law + bachelor informs that the [5] universities have agreed to shorten studies to 3 and undergraduate US 3.5 years. to start bachelors, aiming to postgraduate + [6] Commission requirements: must be a enrolled in research graduate, oriented program, + bachelor if [7] In 2005, universities agreed to shorten the Several universities study period to 3 years. 3 commit to and 3, 5 years + bachelor [8] credits (4, 5 years) undergraduate studies. bachelor lasting 4 years studies, (catholic theology studies + [9] Recommended by the submitting study. riodas combined with bachelor - + 1, studies 5; 4 + 5 years (3 + 2; 3, 5 1). Bachelor's + [10] Asked to compare these studies with his own studies that here much easier. + bachelor in the USA, a foreigner noted, 6 Here are only the first ten lines of the concordance. Clicking on the plus sign on the website shows a longer concordance. 6 2 Irena Markievicz, Erika Rimkutė | Dictionary of Educational and Scientific Terms | ir ontologija Several thousands of concordance lines are provided for some terms. It takes a lot of time to review this amount of information, not everyone is interested in this data. For those who want to learn more about the usage of the term, the context in which the selected term is used, perhaps to make another definition, to choose the necessary examples, to form an objective opinion, concordance provides many benefits. This and the following chapters describe the ontology of the terms of the ML, the principles of its composition, the possibilities of using this and other ontologies. To make it clearer, some visualized ontological classifications and results of the ML terms are presented. Ontologies are formal tools for conceptualizing knowledge that summarize natural language knowledge into a structured, hierarchical model of related concepts. Due to the problems of information processing quality and terminology ambiguity, there is a need to create structured term databases with which computer programs can process natural language processing and interpret its semantics. For this reason, ontologies are created. A person who knows a particular language easily understands the meaning of the natural language text presented to him, and a computer program interprets the same information as a set of textual symbols and associated metatags. Ontologies are the link that converts natural language written information into a conceptual knowledge model that can be easily interpreted by information gathering and processing robots. The creation of ontologies is an interdisciplinary process that encompasses the fields of philosophy, linguistics and computer science (see Grigonytė 2010). In philosophy, ontology is perceived as a discipline that examines being, and in eggvistics – a network of individual concepts and terms that describe them. zistenciją. Tokią ontologijos apibrėžtį papildo lingvistai; ontologija linIn computer science, ontology is a logical and formal representation of reality. The largest and most readily available source of natural language texts is the Internet, and therefore ontologies are often seen as a tool for the semantic web and semantic search. The W3C, the organization that develops web standards, describes ontologies as a set of terms that describe knowledge in a particular field: “Ontologies are used by people, databases and applications that seek to share knowledge in a particular field. 6 3Terminology | 2013 | 20 information <...>. Ontologies link the concepts of a particular field and the relationships between them that are applied to computer applications" (W3C). The Education and Science Terms Ontology (hereinafter referred to as the ETS Terms Ontology) was created in order to formalize the ETS term set created during the project mentioned in the introduction and to supplement it with semantic links that can be interpreted by application programs. The main works of creating ontology: cocific their kybiškai aprašyti pasirinktos srities terminus bei sąvokas ir formaliai spemeanings. These works are important in solving the problem of ambiguity of terms and creating a structural model of terms in the field of HM. The SM terms ontology was created not only as a taxonomy of SM terms, but also as one of the possible semantic search resources. The ontologies of the terms of the HM are available online at http://meta.vdu.lt/ webprotege/, visualized using the WebProtege tool, which allows to view the hierarchical tree of classes, their attributes and examples of the essentials of the concepts. The user, opening or hiding new cards and blocks, can arrange a convenient graphical interface. We recommend using Chrome or Mozilla Firefox browsers. In order to better visualize the relationships between terms, it is recommended to use Protege 4.3 with OntoGraf plugin. The generalized concept of creation of ontologies is ŠVIETIMO IR MOKSLO TERMINŲ ONTOLOGIJOS described by the following metamodel of processes (see Cimiano 2006 for more details): M={D, LA, T, S, C, TR}, where D stands for document collection, LA – linguistic tags, T – term selection, S – synonyms identification, C – terms and their synonyms linking to concepts, and TR – definition of semantic relationships between concepts. Using different methodologies for creating ontologies, various strategies for creating ontologies are applied: based on some methodologies, many (Cyc, TOVE, Methontology, On-To-Knowledge), in others, the use of ontologies in application programs is more emphasized (KAKTUS). In some giau dėmesio skiriama ontologijos gyvavimo ciklui ir prototipų kūrimui methods, ontologies are created from accumulated texts (TOVE, On-ToKnowledge), kitais – iš didelių bendrinių žinių ontologijų (SENSUS, Cyc) (for more, see Corcho et al. 2003). Ontologies are simply created in the following stages: field of knowledge is selected, information is processed (concepts, terms, limitations are defined), 6 4 Irena Markievicz, Erika Rimkutė | Dictionary of Educational and | ir ontologija Scientific Terms Methods of ontology extension and evaluation criteria are specified, and ontology documentation is prepared (for more details see Uschold et al. 1996). When creating ontologies using this method, it is not foreseen that prototypes of ontologies will be created or that ontologies will be used as additional sources of information. Applying this methodology, several ontologies of farming activities have been created, but they are not expected to be used in application programs. The On-To-Knowledge project proposed a methodology focusing on knowledge management and the possibility of using the future ontology in information systems (see Staab et al. 2001). After the feasibility study, the sources of information, potential users of the ontology and ways of use were defined. Experts in the selected field participated in the development of the On-To-Knowledge ontology, information collected from texts and other knowledge bases was processed. Ontology quality was assessed by checking whether the ontology meets the requirements and applicability. All these stages of the creation and development of the ontology can be considered as recommendations for the creation of other ontologies. The methodologies presented focus on methods of creating ontologies from textual information sources. The SENSUS ontology methodology proposes the use of general knowledge ontologies in the process of creating a special field ontology (see Gomez-Perez et al. 2004). The methodology envisages grouping of terms from the OntoSaurus knowledge base into a concept tree. When attempting to link two concept classes, the root class is searched. When choosing the methodology for the creation of the SM term ontology, the available information resources and the possibilities of adapting language technologies and ontologies creation tools were taken into account. It was decided to use the experience gained in the Methontology project (for more see. Mariano et al. 2004; Gomez-Perez et al. 2004; Corcho et al. 2003). The application of Methontology to create the SM term ontology and the ontology creation resources are shown in Figure 1. The specification specifies the purpose and scope of creating the ontology. The conceptual mas atsižvelgiant į specifikacijos metu išgrynintą sritį, vėliau jis formaliontology model is curated – transformed into a formal ontology model. During the creation process, the formal model is implemented according to the requirements of the chosen ontologies creation language. Even the created ontology is often changed, expanded or updated. 7 1Terminology | 2013 | 20 with the same characteristics. For example, if the ontology indicates that the rector leads the university, then the entity of this concept – Zigmas Lydeka – leads VDU, i.e. the entity of the concept of university (see Figure 7). Ontology of educational and scientific terms created in OWL language with Protege 4.3 ontologies creation tool, visualized using WebProtege tool or OntoGraf plugin9. ŠVIETIMO IR MOKSLO TERMINŲ ONTOLOGIJOS At present, the ontology of terms in the ML contains 29 abstract classes of concepts and 465 general concepts, 87 concepts, classes of concepts and their essential properties, 141 entities, 296 classes of ontological concepts, concepts and their essential relations. Formally, the complexity of an ontology can be measured using description logic metrics (see Corcho et al. 2003; Baader 2003). The ontologies of SM terms are evaluated at ALCHON(D) complexity level, here: – AL – attribute language; with it it is possible to associate concepts, write universal restrictions on them; – C – indicates that it is possible to deny the relationships of concepts; – H – indicates that it is possible to create a hierarchy of roles; – O – quantity limitations (relations: exactly one, one of many); – N – quantity restrictions (relations: less, more); – (D) – Properties of data types. In addition to the vocabulary of ontology, taxonomy and semantic relationships, the possibilities of its use and application are evaluated. The chosen OWL ontologies creation language is suitable for semantic inferences, filling the ontology with new concepts or linking several ontologies from different fields. The structural term model in the field of ML is prepared in such a way that each ontological concept is described by a unique set of properties and semantic connections – such a solution helps to solve the problem of ambiguity of terms. This resource was created not only as a taxonomy of terms in the field of ML, but also as one of the possible means of semantic search and natural language processing. 9 For more information: http://protege.stanford.edu. 7 2 Irena Markievicz, Erika Rimkutė | Dictionary of Educational and Scientific Terms | ir ontologija So far, a lot of attention has been paid to how ontologies can be applied in computerizing natural language, systematizing it, making it understandable to computer programs. It should be emphasized that ontologies are kuo ontologijos gali būti pravarčios lingvistams ar kitų sričių specialistams. particularly useful for terminologists, because, using the tools of ontological visualization, the interrelationships of terms are clearly visible. In order to illustrate the terms, specific words (called essentials in the ontology) can be selected from the ontology. Both the glossary of terms and the ontology can help participants in the field of education: lecturers, teachers, administrative staff, students, pupils, because these sources show how, for example, students are classified, what types of studies are available, what the higher education administration consists of, etc. The article presents the Vocabulary of Educational and Scientific Terms and the Ontology of Educational and Scientific Terms. Both vocabulary and ontology are improved. The greatest advantage and uniqueness of both sources is that they are prepared using the principles of textbooks and computer linguistics, which are still scarcely applied by Lithuanian terminologists. The HM Terms Dictionary is available online and consists of 224 terms of one to five words. This differs from other dictionaries of terms in that, in addition to the usual parts of the dictionaries of terms (the terms themselves, definitions, equivalents in foreign languages), it contains all the variation forms of the term with frequencies, examples from the textbook of the Ministry of Education, collocates and concordance. This data is important in that the dictionary users can get a complete picture of the usage of a particular term, the context; can find important characteristics of the term that may not be mentioned in the definition. On-line ontologies of MS terms reveal the semantic relationships between MS terms and make this information understandable to computer programs. Ontologies can be particularly useful for terminologists, classifying, describing terms in a particular field, providing specific examples. It is expected that both the glossary of terms and the ontology will be methodologically important resources and will encourage Lithuanian terminologists to make more use of the possibilities offered by textbooks to research, describe and classify terms. 7 3Terminology | 2013 | 20 LITERATŪRA Baader F. 2003: Appendix: description logic terminology. – The description logic handbook: theory, implementation, and applications, Cambridge: Cambridge university press. Bielinskienė A., Boizou L., Kovalevskaitė J., Utka A. 2012: Towards the Automatic Extraction of Termdefining Contexts in Lithuanian. – Human Language Technologies. The Baltic Perspective: Proceedings of the Fifth International Conference Baltic HLT 2012, Amsterdam, Berlin, Tokyo, Washington, DC: IOS Press, 18–26. Cimiano P. 2006: Ontology Learning and Population from Text: Algorithms, Evaluation and Applications, Karlsruhe: Springer. Corcho O., Fernández-López M., Gómez-Pérez A. 2003: Methodologies, tools and languages for building ontologies. Where is their meeting point? – Data & knowledge engineering 46(1), 41–64. Gomez-Perez A., Corcho O., Fernandez-Lopez M. 2004: Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web, London: Springer-Verlag. Gornostay T., Ramm A., Heid U., Morin E., Harastani R., Planas E. 2012: Terminology Extracion from Comparable Corpora for Latvian. – Human Language Technologies. The Baltic Perspective: Proceedings of the Fifth International Conference Baltic HLT 2012, Amsterdam, Berlin, Tokyo, Washington, DC: IOS Press, 66–73. Grigonytė G. 2010: Building and Evaluating Domain Ontologies: NLP Contributions, Logos Verlag Berlin GmbH. Grigonytė G., Rimkutė E., Utka A., Boizou L. 2011: Experiments on Lithuanian Term Extraction. – Proceedings of the 18th Nordic Conference of Computational Linguistics NODALIDA 2011. NEALT Proceedings Series 11, 82–89. ISO 10241: 1992 International terminology standards – Preparation and layout, Geneva: ISO. ISO 9001: 2000 Quality management systems – Requirements, Geneva: ISO. Krugļevskis V., Vancāne I. 2005: Term Extraction from Legal Texts in Latvian. – Proceedings of the Second Baltic Conference Human Language Technologies, 155–159. LST ISO 1087-1: 2005 Terminologijos darbas. Aiškinamasis žodynas. 1 dalis. Teorija ir taikymas (tpd ISO 1087-1: 2000). Mariano F., Gomez-Perez A., Juristo N. 2004: Methontology: From Ontological Art Towards Ontological Engineering. – AAAI-97 Spring Symposium. Series on Ontological Engineering, Stanford: AAAI Press, 33–40. Mayr E. 1987: The ontological status of species: scientific progress and philosophical terminology. – Biology and Philosophy 2(2), 145–166. Rimkutė E. 2010: Lietuvių kalbos terminų automatinio nustatymo galimybės. – Kalbų studijos 16, 71–78. Rimkutė E. 2012: Automatinis švietimo ir mokslo terminų nustatymas lingvistiniais metodais. – Terminologija 19, 54–69. Staab S., Studer R., Schnurr H. P. 2001: Knowledge Processes and Ontologies. – Intelligent Systems 16(1), 26–34. Uschold M., Gruninger M. 1996: Ontologies: Principles, methods and applications. – Knowledge engineering review 11(2), 93–136. Uschold M., Gruninger M. 2004: Ontologies and semantics for seamless connectivity. – ACM SIGMod Record 33(4), 58-64. W3C – OWL Web Ontology Language Use Cases and Requirements. Prieiga internete http://www.w3.org/ TR/2002/WD-webont-req-20020307/ (žiūrėta 2013-10-14). ONTOLOGY AND DICTIONARY OF SCIENCE AND EDUCATION TERMS The paper presents the dictionary and the ontology of science and education terms. The proposed approach of ontology and dictionary building uses the following Natural Language Processing techniques: linguistic pattern recognition, collocation extraction, morphological analysis, POS tagging, and others. The dictionary of science and education is available online and contains 224 one word and multiword terms (their length is up to 5 words). The dictionary contains the 7 4 Irena Markievicz, Erika Rimkutė | Švietimo ir mokslo terminų žodynas The dictionary | ir ontologija contains all necessary dictionary fields (terms, definitions, translations to other languages), as well as some additional fields such as declined forms of terms with their frequencies, examples of term usage, collocations and concordances from the special science and education corpus. The main focus of the paper is the ontology of terms in the domain of science and education. Authors present, how different research areas define ontologies, what are the possibilities of their use, what are ontology building methods. The structure of the ontology is illustrated by multiple examples. The hierarchical structure of concepts, their properties and relationships make this information readable and understandable for knowledge-based information systems. Ontologies can be particularly useful for terminology experts, who try to classify and describe terms, concepts and their instances in a domain specific field. It can be used by students, teachers, and government bodies. While using the ontology, they can define and conceptualize the processes of studying, teaching or learning. The paper introduces the possibilities of semi-supervised term extraction with mixed prescriptive and descriptive term analysis methods, which can be useful for terminology experts, lexicographers, and creators of lexical databases. Retrieved 2013-10-29. Irena Markiewicz Vytauto Didžiojo universitetas K. Donelaičio g. 52, LT-44248 Kaunas, Lithuania E-mail [email protected] Erika Rimkutė Vytauto Didžiojo universitetas K. Donelaičio g. 52, LT-44248 Kaunas, Lithuania E-mail: [email protected]