Best Practices for Termbase Design

Transcription

1 Best Practices for Termbase Design Klaus Dirk Schmitz Institute for Translation and Multilingual Communication Technische Hochschule Köln TH Köln Germany koeln.de

2 Klaus Dirk Schmitz Diploma in computer science & mathematics at Saarbrücken University Dr. phil. in applied linguistics & information science at Saarbrücken University research assistant, senior researcher and project leader at Saarbrücken University (machine translation, language technology, CAT tools, teaching) Since 1992, full professor for terminology science and language technology at Technische Hochschule Köln TH Köln

3 Klaus Dirk Schmitz Managing Director of the Institute of Terminology and Multilingual Communication (ITMK) and the Institute of Information Management (IIM) Head of DIN NAT (German standards committee for terminology) and Chairman of DIN NAT AA5 (Systems for managing terminology, knowledge and content) Vice President of DTT e.v., TermNet, Member of several advisory boards Author and editor of numerous articles and books Dirk_Schmitz koeln.de/personen/klaus.schmitz/

4 Motivation Terminology work and terminology management is essential for techwriters, translators, languages service providers, companies and organizations Terminology management supports consistent document creation, reduces translation costs, and improves communication within a company, but also between company and customers as well as service providers and suppliers Specific tools for terminology management are available on the market The design of a termbase is a very diligent task; design errors are painful if the termbase contains many terms, and bad for data exchange and interoperability

5 The wardrobe model From unorganized chaos

6 The wardrobe model to useful structured organization

7 Data modelling for termbanks

8 Data modelling for termbanks

9 Designing a termbase Before designing a terminology management solution and choosing, adapting or programming a terminology management application: Analyze the needs and objectives Specify the user groups, tasks and workflow Define terminological data categories needed Take into account the basic modeling principles Model the terminological entry Select, adapt, develop the software

10 12 important aspects for termbase design 1. Specify languages 2. Select data categories 3. Follow the granularity principle 4. Specify the type of data categories 5. Use closed data categories 6. Choose the right level 7. Model the terminological entry 8. Follow the concept orientation approach 9. Implement term autonomy 10.Support users by templates, layouts etc. 11.Test prototype in real life for a defined period 12.Be prepared to re design the termbase

11 1. Specify languages Select the termbase user interface language Select the language of the software

12 1. Specify languages Select the termbase user interface language Select the language of the data categories

13 1. Specify languages Select the language(s) of the termbase content

14 1. Specify languages Select the language(s) of the termbase content

15 2. Select data categories Analyze in detail which type of information you have to deal with Consult ISO or ISOCAT (data categories) for getting ideas and matching your needs with standardized categories Not only important for an adequate and perfect solution but also for future data exchange with others

16 2. Data categories First comprehensive analysis of terminological data categories used in term bases for the preparation of ISO and ISO First standard for terminological data categories: ISO 12620:1999 Completely new version of ISO 12620:2009 (currently new working draft for in ISO) Data Category Registry ISOcat ( Old: Max Planck Institute for Psycholinguistics, Nijmegen, NL New: Implemented in TermWeb (Interverbum)

17 2. Data categories (ISO 12620: 1999)

18 2. Data categories (ISOcat old)

19 2. Data categories (ISOcat new)

20 3. Follow the granularity principle The degree of detail that can be achieved by using the available data categories to document terminological information Low granularity: e.g.: grammar = m,n,s (masculine noun singular) High granularity e.g.: part of speech = noun grammatical gender = masculine number = singular Advantage: better retrievability

21 4. Specify the type of data categories Complex data categories Open data categories content not predictable and defined by specification e.g.: term, definition, note Closed data categories content defined by a limited set of possible values e.g.: gender, part of speech, geographical usage Simple data categories content only yes or no; values of closed data categories e.g.: masculine, noun, DE

22 4. Specify the type of data categories

23 5. Use closed data categories Closed data categories (picklists): Allow faster creating and editing of data Ensures consistency Necessary for correct filtering and export Improves interoperability Use picklists whenever possible!

24 6. Choose the right level Typology of data categories: Concept oriented data categories e.g.: subject field, figure Language oriented data categories e.g.: definition? Term oriented data categories e.g.: part of speech, context Administrative data categories e.g.: author, date, note Special data categories e.g.: term, language, (structural elements), (shared resources)

25 6. Choose the right level The typology of data categories gives some hints, on which level of the data model the data categories are attached (concept, language or term oriented datcats) Very often, the level is exactly defined: e.g.: part of speech at term level But in some cases, the choice of level depends on the objective & philosophy of the termbase: e.g.: definition at concept, language, term level e.g.: working status at concept, language, term level

26 (S.E.Wright)

27 (S.E.Wright)

28 7. Model the terminological entry After selecting the necessary data categories, and specifying the type of data categories, and choosing the right level, the data model for the terminological entry of the termbase is defined! New data categories and picklist values can easily be added But: deleting or changing data categories or re allocated levels in the data model is not possible! (only via export, new termbase creation and import)

29

30 concept level metadata language level term level

31 Metamodel in MultiTerm entry = concept language term

32 8. Follow concept orientation All terminological information belonging to one concept including all terms in all languages and all term related and administrative data must be store in one terminological entry concept = terminological entry

33 8. Follow concept orientation Lexicographical or semasiological view / entry meaning word meaning meaning meanding meaning meaning

34 8. Follow concept orientation Terminological or onomasiological view / entry term term concept term term term term descriptive terminology management

35 8. Follow concept orientation Terminological or onomasiological view / entry term (term) concept term term term term prescriptive terminology management

36 Lexicographical entry

37 Terminological entry

38 Terminological entry

39 9. Implement term autonomy All terms belonging to one concept should be managed (in one terminological entry) as autonomous (repeatable) blocks of data categories without any preference for a specific term Therefore all terms can be documented with the relevant term related data categories Term autonomy is necessary for the main term, all synonyms, all variants, and all short forms Term autonomy is not explicitly discussed in theoretical literature

40 Concept orientation & term autonomy TermEntry Concept represented by ID-No. and/or notation + Metadata Language 1 + Metadata Language 2 + Metadata Language 3 + Metadata... Term 1 + Metadata Term 1 + Metadata Term 1 + Metadata Term 2 + Metadata Term 2 + Metadata Term 3 + Metadata

41 Terminology Metamodel (ISO) concept orientation metadata term autonomy

42 Metamodel in MultiTerm entry = concept language term

43 10. Support user by templates, etc. In most cases, the termbase is not used only by one well defined user (group) Different users have different tasks to do, different knowledge, different views, and different needs By user rights management and user specific templates and layouts: data will be more consistent less errors and misuse will happen user specific tasks are better supported e.g. read only, mandatory fields, mono lingual view,

44 11. Test prototype in real life After designing the termbase (and installing the tool), use the termbase in real life environment will all intended users and for all intended tasks Do this for a defined period of time (e.g. three month) Monitor the process and document all user complaints, problems and errors that occur Evaluate the user experience, the quality of data, and the interaction with other tools

45 12. Re design the termbase After experiences with the prototype testing, be prepared and willing the start new and re design the termbase Many users have skipped this step because of the e.g. 150 entries they have already elaborated and entered They are complaining about that missed opportunity every day and it is a great pain working with a not ideal termbase with entries and more In most cases, the 150 entries are not lost although the termbase design has to be changed

46 Conclusion For (computerized) terminology management and termbase design: Consult literature and guidelines for terminology management (e.g. Kockaert/Steurs (eds.)(2015): Handbook of Terminology; Drewer/Schmitz (2017): Terminologiemanagement) Follow (ISO) terminology standards (e.g. ISO 704, ISO 1087, ISO 12620, ISO 26162, ISO 30042) Create guidelines and quality procedures for your own terminology work and your own terminology management solution!

47 Conclusion Specific tools for terminology management are available on the market, allowing all necessary tasks and features for terminology management Not all tools will have the features you need and will support the important transactions of your organizational environment Choose the right tool! Don t use Excel tables as termbase! Don t program your own software!

48 Thank you for your attention Prof. Dr. Klaus Dirk Schmitz Technische Hochschule Köln Fakultät 03 ITMK Ubierring Köln koeln.de