Multilingual legal terminology databases: Workflows and roles
1.Introduction
Multilingual legal terminology databases (MLTDBs) are terminology databases (TDBs) containing legal terminology in more than one language. This chapter focuses on the specific features related to the legal domain and their influence on user expectations and usage scenarios, database structure, workflows, roles, and quality aspects of MLTDBs.
We provide a brief introduction to TDBs (Section 2) and address the specific features influencing the structure of MLTDBs, i.e., the number of legal systems catered for, different usage scenarios, target users, and user-database interaction (Section 3). Several activities and processes are required to create and populate MLTDBs. These are presented in a typical workflow: needs analysis, design and implementation of MLTDBs, documentation, term extraction, compilation of terminological entries, revision and quality assurance, maintenance, and dissemination (Section 4). As terminology work and the creation of MLTDBs are typically collaborative practices, the following section outlines the roles involved in terminology work in the legal domain: terminologists, revisers, terminology coordinators, legal experts, IT experts, and users (Section 5). The role of machines is discussed not only as tools supporting various steps in the workflow (e.g., term extraction, maintenance, dissemination) but also as tools that exploit terminological data for other purposes. The different users, their needs and requirements are also reflected in the quality aspects of MLTDBs. The concepts of quality and quality management are discussed in Section 6, outlining quality planning, quality assurance (QA), and quality control (QC), including relevant standards. The chapter concludes with an outlook on how tools might be further integrated into workflows and on synergies with natural language processing (NLP) and machine learning.
2.Terminology databases
A terminology database or termbase is “a database comprising a terminological data collection” (ISO 26162–1 2019ISO 26162-1 2019 Management of Terminology Resources – Terminology Databases – Part 1: Design. Geneva: International Standardization Organization., Clause 3.2.1),11.The same definition is also present in ISO 30042 (2019)ISO 30042 2019 Management of Terminology Resources – TermBase eXchange (TBX). Geneva: International Standardization Organization.
,
Clause 3.28, where it was taken from.
i.e., comprising “a resource consisting of concept entries with associated metadata and documentary information”
(ISO 26162–1 2019ISO 26162-1 2019 Management of Terminology Resources – Terminology Databases – Part 1: Design. Geneva: International Standardization Organization.
, Clause 3.2.4). According to Melby (2012Melby, Alan K. 2012 “Terminology in the Age of Multilingual Corpora.” The Journal of Specialised Translation 18:7–28.
, 8) a termbase is “a computer database consisting primarily of
information about domain-specific concepts and the terms that designate them”. It provides “a structured repository of
linguistic data, enriched with metadata and structured according to particular classification schemes and concept
based analysis” (Steurs et al. 2015Steurs, Frieda, Ken De Wachter, and Evi De Malsche 2015 “Terminology Tools.” In Handbook of Terminology, Vol. 1, 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 222–249. Amsterdam: John Benjamins.
, 224). Unlike lexicographic products
that follow a semasiological approach (e.g., legal dictionaries), terminographic products follow an onomasiological
approach and are concept-oriented. The basic units of TDBs are terminological entries, which contain a set of related
terminological data elements on a specific concept (Drewer, and Schmitz
2017Drewer, Petra and Klaus-Dirk Schmitz 2017 Terminologiemanagement. Grundlagen – Methoden – Werkzeuge. Berlin: Springer Vieweg.
, 128). This is reflected in the definition by Támas and Sermann (2019Tamás, Dóra Mária and Eszter Sermann 2019 “Evaluation System for Online Terminological Databases.” Terminologija 26(1):24–46.
, 113), who see TDBs as a collection of electronically stored terminological data that was created
following an onomasiological approach by mapping the conceptual system of a subject field and which contains terms and
their definitions relating to one or several subject fields in one or more languages.
TDBs are essential for managing terminology, as they are used for collecting, handling, structuring,
sharing, publishing, and re-using terminology. They may serve different purposes, such as supporting the drafting of
texts and technical writing, translation and localization, terminology planning and standardization, knowledge
representation and management. According to their purpose and intended user group, they will be conceived differently
and present different functionalities and user interfaces (Steurs et al.
2015Steurs, Frieda, Ken De Wachter, and Evi De Malsche 2015 “Terminology Tools.” In Handbook of Terminology, Vol. 1, 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 222–249. Amsterdam: John Benjamins. , 227). We may distinguish between ad
hoc personalized “termbases” that do not strictly follow the onomasiological approach, and which are
generally created for translation purposes and integrated into translation environments, vs. large-scale, mainly
thematic, strictly controlled stand-alone resources maintained by large institutions that are often known as “term
banks” (Bowker 2015Bowker, Lynne 2015 “Terminology and Translation.” In Handbook of Terminology, Vol. 1, 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 304–323. Amsterdam: John Benjamins.
, 306–307). The complexity of TDB structure may vary
from quite basic to very complex, with additional features such as links to texts or visualization of concepts maps
(Tamás, and Sermann 2019Tamás, Dóra Mária and Eszter Sermann 2019 “Evaluation System for Online Terminological Databases.” Terminologija 26(1):24–46.
, 28). The more sophisticated TDBs are
developing into TKBs, terminological knowledge bases, i.e., “knowledge repositories represented in a formal language
that can be accessed by users via an expert system based on terminological units, which are organized into a
conceptual network containing various types of relations” (Cabré Castellví
2006Cabré Castellví, M. Teresa 2006 “From Terminological Data Banks to Knowledge Databases: the Text as the Starting
Point.” In Lexicography, Terminology and Translation. Text-based Studies in Honour of Ingrid Meyer, edited by Lynne Bowker, 93–106. Ottawa: Ottawa University Press.
, 98). TKBs provide direct access to corpus data and ontologies, and often make data readable by
machines besides human users.
Today, there is a wide choice of commercial or proprietary solutions to manage terminology in databases
(Drewer, and Schmitz 2017Drewer, Petra and Klaus-Dirk Schmitz 2017 Terminologiemanagement. Grundlagen – Methoden – Werkzeuge. Berlin: Springer Vieweg. , 142–143), including cloud-based solutions
(Varga 2013Varga, Cristina 2013 “Virtualization of Research in Terminology. Cloud-based Terminology Management Tools.” Scientific Bulletin of the Politehnica University of Timişoara Transactions on Modern Languages 12(1–2):27–42.
), which may partly influence or constrain database
structure (Kageura, and Marshman 2020Kageura, Kyo and Elizabeth Marshman 2020 “Terminology Extraction and Management.” In The Routledge Handbook of Translation and Technology, edited by Minako O’Hagan, 61–77. Abingdon: Routledge.
, 66–67). Some allow smooth
integration with authoring tools, CAT-tools, localization tools, knowledge management tools, etc.
TDBs may cover one or more languages, including language varieties and dialects (Matteucci 2006Matteucci, Alessandra 2006 “La terminologia dei componenti strutturali della motocicletta Aprilia: uno studio sulla variazione
linguistica aziendale.” Mediazioni 3:1–10.), thus being monolingual, bilingual, or multilingual (Melby 2012Melby, Alan K. 2012 “Terminology in the Age of Multilingual Corpora.” The Journal of Specialised Translation 18:7–28.
, 8). They may collect diverse types of concepts and terms, either focusing on one
specific subject or domain (e.g., law, industrial automation) or on a wider range of content relevant to a given
organization (e.g., EU terminology, company terminology) or activity (e.g., translation of legal documents,
terminology development in a minority language, protection of intellectual property).
3.Multilingual Legal Terminology Databases
This chapter addresses multilingual – including bilingual – TDBs containing legal terminology. The salient characteristics of legal terminology, which influence (multilingual) terminology management in the legal domain, such as indeterminacy, variation, the relation to general language and other LSPs have been addressed in other chapters in this publication (see Biel, Jopek-Bosiacka, Mouritsen). In this section, we will focus on the specific features of MLTDBs. These may have specific characteristics according to the number of legal systems considered, their purpose, and target users.
3.1MLTDBs dealing with one legal system
A single legal system may be multilingual (e.g., the Swiss, South African, and EU legal systems).
In this case, the legal concepts stored and organized in the TDB are expressed by designations in two or more
languages. The conceptual level, i.e., legal institutions, rules, bodies, and the relations between them, is the
same but is conveyed through more than one language (Gambaro, and Sacco
2009Gambaro, Antonio and Roberto Sacco 2009 Sistemi giuridici comparati, 3rd ed. Milano: UTET., 10). Conceptual characteristics and concept relations are shared across languages so that, for
example, there will be only one reference concept system.
As all designations in a terminological entry refer to the same concept, in principle, most
challenges reside at the language level (e.g., differences in designation length, complexity, transparency,
connotation, etc.). For example, legal concepts may be first designated – or borrowed from another legal system –
in one official language of a multilingual system and finding a designation in other official languages may not be
straightforward. This may apply to EU concepts adapted from originally national concepts that need designations in
the languages of all member states (e.g., “Advocate General” in EU law was originally taken from French law (Gombos 2014Gombos, Katalin 2014 “EU Law Viewed Through the Eyes of a National Judge.” Accessed July 13, 2022. https://ec.europa.eu/dgs/legal_service/seminars/20140703_gombos_speech_en.pdf, 1)). It is also common in minority languages which must
express legal concepts and rules usually developed in the majority language (Chiocchetti, and Ralli 2016Chiocchetti, Elena and Natascia Ralli 2016 “Ein Begriff, zwei Sprachen, unterschiedliche (Rechts)Kulturen.” In Terminologie und Kultur. Akten des Symposions, Mannheim, 3.-5. März, edited by Petra Drewer, Felix Mayer, and Klaus-Dirk Schmitz, 103–112. München: Deutscher Terminologie-Tag e.V.). Challenges may also reside in managing or reducing synonymy and polysemy
to foster unambiguous communication and in coping with intrinsic linguistic and structural differences between the
languages of a legal system (e.g., while custodia, custody, in Italian law of obligations, can
refer to both animate and inanimate entities, the official German designations in the province of Bolzano, where
Italian and German are co-official languages, distinguish Verwahrung, referring to objects, from
Beaufsichtigung, referring to living creatures such as livestock).
3.2MLTDBs dealing with two or more legal systems
MLTDBs may cover more than one legal system. In this case, the conceptual level will necessarily
diverge to a smaller or greater extent, according to how close the legal systems are to each other and to possible
harmonization efforts. A concept existing in one legal system may be totally unknown in another system. Concepts
from different legal systems may have more or less comparable characteristics. The further apart the legal systems
dealt with, the more challenging it is to find equivalent legal concepts (Cao
2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters. , 30–31; Pommer 2006Pommer, Sieglinde 2006 Rechtsübersetzung und Rechtsvergleichung. Frankfurt: Peter Lang.
, 43). There are systemic,
linguistic, and cultural differences (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters.
, 23).
This is a consequence of every national and supranational legal system having its own specific set
of rules and conceptual structures developed over time. Legal language and terminology express and reflect such
specificities and are therefore system-bound (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters. , 23–24; de Groot 1999Groot, Gerard-René de 1999 “Das Übersetzen juristischer Terminologie.” In Recht und Übersetzen, edited by Gerard-René de Groot and Rainer Schulze, 11–46. Baden Baden: Nomos.
, 12–17; 2002 2002 “Rechtsvergleichung als Kerntätigkeit bei der Übersetzung juristischer Terminologie.” In Sprache und Recht, edited by Ulrike Haß-Zumkehr, 222–239. Berlin: de Gruyter.
, 222;
Pommer 2006Pommer, Sieglinde 2006 Rechtsübersetzung und Rechtsvergleichung. Frankfurt: Peter Lang.
, 18–19; Šarčević
1997Šarčević, Susan 1997 New Approach to Legal Translation. The Hague: Kluwer Law International.
, 13). “[D]ifferent legal languages have their own
unique legal vocabulary” (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters.
, 20). While issues of missing or
partial equivalence between concepts are not rare in the terminologies pertaining to the hard sciences, which are
essentially universal, every country has its own legal system that differs to a lesser or greater extent from that
of other countries (Arntz et al. 2014Arntz, Reiner, Heribert Picht, and Klaus-Dirk Schmitz 2014 Einführung in die Terminologiearbeit, 7th ed. Hildesheim: OLMS.
, 162; Drewer, and Schmitz 2017Drewer, Petra and Klaus-Dirk Schmitz 2017 Terminologiemanagement. Grundlagen – Methoden – Werkzeuge. Berlin: Springer Vieweg.
, 20). Consequently, full equivalence between concepts from
distinct legal systems is definitely not a given rule (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters.
, 29; de
Groot 1999Groot, Gerard-René de 1999 “Das Übersetzen juristischer Terminologie.” In Recht und Übersetzen, edited by Gerard-René de Groot and Rainer Schulze, 11–46. Baden Baden: Nomos.
, 21; Pommer
2006Pommer, Sieglinde 2006 Rechtsübersetzung und Rechtsvergleichung. Frankfurt: Peter Lang.
, 147; Sandrini 2014 2014 “Multinational Legal Terminology in a Paper Dictionary.” In Legal Lexicography. A comparative perspective, edited by Máirtín Mac Aodha, 141–152. London: Routledge.
, 147; Šarčević 1997Šarčević, Susan 1997 New Approach to Legal Translation. The Hague: Kluwer Law International.
, 232). Therefore, when working with legal terminology, the notion of
conceptual equivalence must necessarily be relativized (Arntz et al.
2014Arntz, Reiner, Heribert Picht, and Klaus-Dirk Schmitz 2014 Einführung in die Terminologiearbeit, 7th ed. Hildesheim: OLMS.
, 162; Pommer 2006Pommer, Sieglinde 2006 Rechtsübersetzung und Rechtsvergleichung. Frankfurt: Peter Lang.
, 147; Sandrini 2014 2014 “Multinational Legal Terminology in a Paper Dictionary.” In Legal Lexicography. A comparative perspective, edited by Máirtín Mac Aodha, 141–152. London: Routledge.
, 148).
This implies that the legal conceptualization behind terms from two legal systems may differ even
when it is expressed in the same natural language (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters. , 33; de
Groot 1999Groot, Gerard-René de 1999 “Das Übersetzen juristischer Terminologie.” In Recht und Übersetzen, edited by Gerard-René de Groot and Rainer Schulze, 11–46. Baden Baden: Nomos.
, 12; Gambaro, and
Sacco 2009Gambaro, Antonio and Roberto Sacco 2009 Sistemi giuridici comparati, 3rd ed. Milano: UTET.
, 8; Sandrini 2014 2014 “Multinational Legal Terminology in a Paper Dictionary.” In Legal Lexicography. A comparative perspective, edited by Máirtín Mac Aodha, 141–152. London: Routledge.
, 144). Arabic, English, French,
German, Spanish are examples of languages that are used by more than one legal system in the world and thus have
developed a set of legal languages where terminologies may vary or where the same terms may even designate
completely distinct concepts. There are as many legal languages as there are legal systems using a specific
natural language (de Groot 2002 2002 “Rechtsvergleichung als Kerntätigkeit bei der Übersetzung juristischer Terminologie.” In Sprache und Recht, edited by Ulrike Haß-Zumkehr, 222–239. Berlin: de Gruyter.
, 225–226) and the relation of legal
terminology with its legal system is more crucial than that with its language (Sandrini 2014 2014 “Multinational Legal Terminology in a Paper Dictionary.” In Legal Lexicography. A comparative perspective, edited by Máirtín Mac Aodha, 141–152. London: Routledge.
, 143). It is possible to create monolingual legal TDBs addressing more than one legal
system, but the geographical and jurisdictional constraints of legal terminology must be specified even when
working with a single natural language (see Section 4.2).
Consequently, terminology work for MLTDBs encompassing more than one legal system poses not only
linguistic but primarily conceptual challenges. Working with legal terminologies from various legal systems is not
just a linguistic task but also a legal task (Arntz et al. 2014Arntz, Reiner, Heribert Picht, and Klaus-Dirk Schmitz 2014 Einführung in die Terminologiearbeit, 7th ed. Hildesheim: OLMS.,
163–170; de Groot 1999Groot, Gerard-René de 1999 “Das Übersetzen juristischer Terminologie.” In Recht und Übersetzen, edited by Gerard-René de Groot and Rainer Schulze, 11–46. Baden Baden: Nomos.
, 20) and requires a comparative legal and
linguistic analysis (Prieto Ramos 2014Prieto Ramos, Fernando 2014 “Parameters for Problem-Solving in Legal Translation: Implications for Legal Lexicography and
Institutional Terminology Management.” In The Ashgate Handbook of Legal Translation, edited by Le Cheng, King Kui Sin & Anne Wagner, 121–134. Farnham: Ashgate.
, 125). MLTDBs must highlight not
only linguistic but also conceptual similarities and differences, so that these can be considered in international
communication (Sandrini 2009Sandrini, Peter 2009 “Der transkulturelle Vergleich von Rechtsbegriffen.” In Legal Language in Action: Translation, Terminology, Drafting and Procedural Issues, edited by Susan Šarčević, 151–165. Zagreb: Globus.
, 163) and translators have enough
information to decide whether any differences are relevant for their specific target readership (de Groot 2002 2002 “Rechtsvergleichung als Kerntätigkeit bei der Übersetzung juristischer Terminologie.” In Sprache und Recht, edited by Ulrike Haß-Zumkehr, 222–239. Berlin: de Gruyter.
, 230–231; Sandrini
2009Sandrini, Peter 2009 “Der transkulturelle Vergleich von Rechtsbegriffen.” In Legal Language in Action: Translation, Terminology, Drafting and Procedural Issues, edited by Susan Šarčević, 151–165. Zagreb: Globus.
, 153), to name just two examples. This is generally achieved by applying methods borrowed from
legal comparison to terminology work (inter alia Chiocchetti, and Ralli
2016Chiocchetti, Elena and Natascia Ralli 2016 “Ein Begriff, zwei Sprachen, unterschiedliche (Rechts)Kulturen.” In Terminologie und Kultur. Akten des Symposions, Mannheim, 3.-5. März, edited by Petra Drewer, Felix Mayer, and Klaus-Dirk Schmitz, 103–112. München: Deutscher Terminologie-Tag e.V.
; Künnecke 2013Künnecke, Martina 2013 “Translation in the EU: Language and Law in the EU’s Judicial Labyrinth.” Maastricht Journal of European and Comparative Law 20(2):243–260.
; Peruzzo 2014Peruzzo, Katia 2014 “MuLex: a Proposal for a Legal Translation-oriented TKB with Graphical
Representation.” Informatica e diritto 23(1):251–274.
; Pontrandolfo 2018Pontrandolfo, Gianluca 2018 “TERMitLEX al servizio della traduzione giuridica tra spagnolo e italiano.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 107–124. Trieste: EUT.
), especially
micro-comparison (Ajani et al. 2018Ajani, Gianmaria, Domenico Francavilla, and Barbara Pasa 2018 Diritto comparato. Lezioni e materiali, 2nd ed. Torino: Giappichelli.
, 4; Del Giudice 2014Del Giudice, Federico 2014 Manuale di diritto pubblico comparato, 7th ed. Napoli: Simone.
, 19; Pommer 2006Pommer, Sieglinde 2006 Rechtsübersetzung und Rechtsvergleichung. Frankfurt: Peter Lang.
, 85; Zweigert and Kötz 1996Zweigert, Konrad and Hein Kötz 1996 Einführung in die Rechtsvergleichung auf dem Gebiete des Privatrechts, 3rd ed. Tübingen: Mohr.
, 4–5).
Micro-comparison enables us to spot analogies and discrepancies between legal norms or concepts
from different legal systems (Ajani et al. 2018Ajani, Gianmaria, Domenico Francavilla, and Barbara Pasa 2018 Diritto comparato. Lezioni e materiali, 2nd ed. Torino: Giappichelli., 8; Del Giudice 2014Del Giudice, Federico 2014 Manuale di diritto pubblico comparato, 7th ed. Napoli: Simone.
, 19) and thereby supports the process of finding
equivalents, i.e., concepts with the same conceptual characteristics or – more commonly in legal and
terminological practice – narrower, broader, or overlapping concepts (Arntz
et al. 2014Arntz, Reiner, Heribert Picht, and Klaus-Dirk Schmitz 2014 Einführung in die Terminologiearbeit, 7th ed. Hildesheim: OLMS.
, 145–148). The comparison may be
systematic, i.e., concerning the concepts of an entire legal subdomain (e.g., contract law, family law), or
ad hoc, i.e., focusing on a specific legal concept in a given communicative situation or text
(Sandrini 2009Sandrini, Peter 2009 “Der transkulturelle Vergleich von Rechtsbegriffen.” In Legal Language in Action: Translation, Terminology, Drafting and Procedural Issues, edited by Susan Šarčević, 151–165. Zagreb: Globus.
, 158–159). The more legal systems that are
considered, the more complex becomes the task of finding a common conceptual core for the legal concepts from each
legal system, so that termbase content might have to be limited to a relatively narrow set of wider or rather
generic concepts. Furthermore, to reduce the number of comparative analyses, one legal system may be defined as
the reference or source legal system in an MLTDB and others as target systems.
Terminological entries in an MLTDB show the overlapping areas between legal concepts, possible
differences at conceptual level (e.g., broader or narrower intension) and at linguistic level (e.g., differences
in register or use) and also warn against false friends, i.e., designations that only superficially seem to refer
to comparable concepts. One particular challenge is dealing with the multidimensionality of legal terms that may
be embedded in several national and supranational legal systems and show significant variation at the designation
level (Peruzzo 2014Peruzzo, Katia 2014 “MuLex: a Proposal for a Legal Translation-oriented TKB with Graphical
Representation.” Informatica e diritto 23(1):251–274., 262). Another challenge is the lack of conceptual
equivalence. When there are no sufficiently overlapping concepts in the target legal system or when there is no
designation for the concept under analysis, a loan word is used or a new term is coined and proposed (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters.
, 55–56; de Groot
1999Groot, Gerard-René de 1999 “Das Übersetzen juristischer Terminologie.” In Recht und Übersetzen, edited by Gerard-René de Groot and Rainer Schulze, 11–46. Baden Baden: Nomos.
, 27). In this context, it is important that MLTDBs collect established terms (Biel 2008Biel, Łucja 2008 “Legal Terminology in Translation Practice: Dictionaries, Googling or Discussion
Forums?” SKASE Journal of Translation and Interpretation 3(1):22–38.
, 26; Molina, and Hurtado Albir 2002Molina, Lucía and Amparo Hurtado Albir 2002 “Translation Techniques Revisited: A Dynamic and Functionalist Approach.” Meta. Translators’ Journal 47(4):498–512.
,
510) to foster unambiguous communication by presenting terminology that is already routinely used and understood
by the speech community.
Due to all these specific challenges, terminological entries in MLTDBs may contain data categories such as geographical usage or legal system, degree of equivalence, notes with comparative information, etc., and picklist values such as proposed term, translingual borrowing, etc., or exploit them more than TDBs in other domains. There may also be more than one reference concept system or ontology, one per each legal system considered (Id-Youss 2016Id-Youss, Lahousseine 2016 Concept System Construction: a Step toward Better Legal Communication. PhD diss., Katholieke Universiteit Leuven.).
3.3Usage scenarios
MLTDBs can be employed in different scenarios and for a range of purposes. They make practitioners
of the law and language mediators aware of the differences between legal systems at linguistic and/or conceptual
level and keep them up to date with changes, thereby informing (multilingual) text drafting and translation. They
support the growing harmonization efforts in a globalized world (Ajani et al.
2018Ajani, Gianmaria, Domenico Francavilla, and Barbara Pasa 2018 Diritto comparato. Lezioni e materiali, 2nd ed. Torino: Giappichelli., 10; Gambaro, and Sacco 2009Gambaro, Antonio and Roberto Sacco 2009 Sistemi giuridici comparati, 3rd ed. Milano: UTET.
, 27–28; Grass 2014Grass, Thierry 2014 “Principes terminologiques pour la constitution d’une base de données pour la traduction
juridique.” In Legal Lexicography. A Comparative Perspective, edited by Máirtín Mac Aodha, 103–114. London: Routledge.
, 104–105) and an increasingly globalized legal discourse
(Gotti 2009Gotti, Maurizio 2009 “Globalizing Trends in Legal Discourse.” In Translation Issues in Language and Law, edited by Frances Olsen, Alexander Lorz & Dieter Stein, 55–75. Houndmills: Palgrave Macmillan.
). They can also be employed to structure legal
knowledge and optimize monolingual and multilingual content management and information retrieval or serve as a
knowledge repository for Artificial Intelligence (AI) applications or the Semantic Web (see Section 4.8). They may represent a reference point for language standardization, e.g., as a support tool for developing a minority language and/or for
disseminating the results of official standardization bodies.
As a consequence, the structure and content of MLTDBs may vary according to their intended
purpose. For example, legal phraseology is considered important in translation-oriented termbases, as it is a
major aspect of difficulty for language mediators (Biel 2014 2014 “Phraseology in Legal Translation.” In The Ashgate Handbook of Legal Translation, edited by Le Cheng, King Kui Sin, and Anne Wagner, 177–192. Farnham: Ashgate., 182;
Chromá 2014Chromá, Marta 2014 “Translation and the Law Dictionary.” In Legal Lexicography. A Comparative Perspective, edited by Máirtín Mac Aodha, 115–140. London: Routledge.
, 134; Grass
2014Grass, Thierry 2014 “Principes terminologiques pour la constitution d’une base de données pour la traduction
juridique.” In Legal Lexicography. A Comparative Perspective, edited by Máirtín Mac Aodha, 103–114. London: Routledge.
, 108–109) but is likely to be absent from termbases intended mainly for knowledge structuring and
knowledge representation. Data categories such as grammatical gender may not be needed in MLTDBs focusing on
concept harmonization, while such information may be desirable for work on some minority languages. Information on
term frequency may be relevant for translation or language standardization work but not for knowledge structuring,
while concept relations will be essential for the latter and additional information for the former. There might be
one definition or reference concept system per each legal system considered or just a single one when aiming, for
example, to standardize a minority language within a single legal system.
3.4Target users
The target users of MLTDBs influence the choice and structuring of termbase content. Therefore,
detailed analyses of expectations and requirements should be performed for every user group (Nielsen 2014Nielsen, Sandro 2014 “Database of Legal Terms for Communicative and Knowledge Information Tools.” In Legal Lexicography. A Comparative Perspective, edited by Máirtín Mac Aodha, 153–175. London: Routledge., 154–160; see Section 4.1).
Traditionally, there are three main target user groups: language mediators, legal experts, and the general public
(Sandrini 2014 2014 “Multinational Legal Terminology in a Paper Dictionary.” In Legal Lexicography. A comparative perspective, edited by Máirtín Mac Aodha, 141–152. London: Routledge.
, 144). Further non-human applications as
users of termbase content have emerged in recent years (see Section 5.7).
Language mediators like translators and interpreters have different needs and expectations
compared to legal experts in terms of the content and functions of an MLTDB (Chromá 2014Chromá, Marta 2014 “Translation and the Law Dictionary.” In Legal Lexicography. A Comparative Perspective, edited by Máirtín Mac Aodha, 115–140. London: Routledge., 130; Peruzzo 2018 2018 “Risorse terminologiche su misura: indagine e riflessione sulle necessità e le preferenze degli
studenti di Giurisprudenza.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 87–106. Trieste: EUT.
). Professional language
mediators mainly need to understand the meaning of a term, look for equivalents, check the adequacy of presumed
equivalents, or look for alternative translations (Nord 2002Nord, Britta 2002 Hilfsmittel beim Übersetzen: eine empirische Studie zum Rechercheverhalten professioneller
Übersetzer. Frankfurt: Peter Lang.
, 133–134).
For them, essential features of TDB content are the presence of (clear) definitions, possibly in all languages, of
examples of use, possibly from real text, of phraseology, of abbreviations and acronyms. Domain labels, semantic
information (e.g., synonyms), usage labels, images, and a range of equivalents with related explanations are
desirable features (Durán Muñoz 2012Durán Muñoz, Isabel 2012 La ontoterminografía aplicada a la traducción. Propuesta metodológica para la elaboración de recursos
terminológicos dirigidos a traductores. Frankfurt: Peter Lang.
, 144). They also consider lookup
speed, number of precise hits, and a wide range of entries top features (Vasiljevs et al. 2010Vasiljevs, Andrejs, Signe Rirdance, and Tatjana Gornostay 2010 “Reaching the User: Targeted Delivery of Federated Content in Multilingual Term Bank.” In Proceedings of the Terminology and Knowledge Engineering Conference “Presenting Terminology and Knowledge
Engineering Resources Online: Models and Challenges” (TKE 2010), 12–13 August 2010, Dublin, 38–39. Dublin: Fiontar.
).
Quite differently, an analysis on what legal experts value most in MLTDBs lists information on
reliability, the presence of one or more definition(s) and context(s), the possibility of selecting a specific
(sub)domain, the level of specialization and precision of information, a clear layout, the presence of links to
reliable and official sources, and information on the last update (Peruzzo
2018 2018 “Risorse terminologiche su misura: indagine e riflessione sulle necessità e le preferenze degli
studenti di Giurisprudenza.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 87–106. Trieste: EUT., 97). Legal experts also appreciate defining contexts that contain additional conceptual information. Regular checks on whether contents are still valid as
well as many references to legal sources are of paramount importance for them (Peruzzo 2018 2018 “Risorse terminologiche su misura: indagine e riflessione sulle necessità e le preferenze degli
studenti di Giurisprudenza.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 87–106. Trieste: EUT.
, 98–99).
Legal experts may expect linguistic information that a linguist would not need, e.g., information
on the use of loan words and on pronunciation (Peruzzo 2018 2018 “Risorse terminologiche su misura: indagine e riflessione sulle necessità e le preferenze degli
studenti di Giurisprudenza.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 87–106. Trieste: EUT., 100).
Conversely, information on language register might be superfluous for a domain expert but essential for a
translator. Finally, the type and depth of definitions required by linguists and legal experts may diverge. While
legal experts value legal definitions from normative texts or official sources, language mediators would probably
opt for more explanatory and less technical or less obscure definitions (Peruzzo 2018 2018 “Risorse terminologiche su misura: indagine e riflessione sulle necessità e le preferenze degli
studenti di Giurisprudenza.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 87–106. Trieste: EUT.
, 102–103; Vanden Bulcke, and De Groote 2016Vanden Bulcke, Patricia and Carine De Groote 2016 “JuriGenT, un banco de datos jurídico neerlandés/español diferente.” CLINA 2(2):15–38.
,
27).
Consequently, Bestué (2019Bestué, Carmen 2019 “A matter of Justice. Integrating Comparative Law Methods into the Decision-making Process in Legal
Translation.” In Research Methods in Legal Translation and Interpreting. Crossing Methodological Boundaries, edited by Łucja Biel, Jan Engberg, M. Rosario Martín Ruano, and Vilelmini Sosoni, 130–147. London: Routledge. , 140–141) proposes an entry
structure targeted at legal translators based on the functions of the target text while Peruzzo (2018 2018 “Risorse terminologiche su misura: indagine e riflessione sulle necessità e le preferenze degli
studenti di Giurisprudenza.” In La banca dati TERMitLEX: un nuovo modello interdisciplinare per la terminografia giuridica, edited by Marella Magris, 87–106. Trieste: EUT.
, 101–102) describes one better suited for legal experts. When MLTDBs
address both language and domain experts, one of the challenges is striking a balance between the needs of diverse
user groups. This may be solved, as the example of TDBs in other domains show (Vezzani et al. 2018Vezzani, Federica, Giorgio Maria Di Nunzio, and Geneviève Henrot 2018 “TriMED: A Multilingual Terminological Database.” In Proceedings of the 11th Edition of the Language Resources and Evaluation Conference, Miyazaki,
2018, 4367–4371. Luxemburg: European Language Resources Association (ELRA).
), by granting access to targeted types of data and a growing depth of information
through different interfaces.
3.5Interaction with users
A good way of ensuring that MLTDBs cater for users’ needs (see Section 4.1) is encouraging their direct involvement in terminology work or regular input and
feedback. A traditional approach to user involvement is providing a terminology query service that answers user
questions and may exploit these to direct terminology work to specific subject fields or just update existing
entries after ad hoc searches triggered by user questions, a clear “win-win situation” (Dobrina 2010Dobrina, Claudia 2010 “Terminology on Demand.” In Terminology in Everyday Life, edited by Marcel Thelen and Frieda Steurs, 81–95. Amsterdam: John Benjamins. , 93) for both parties. Feedback and input forms on published
entries provide another way of interacting with users (Ralli, and Andreatta
2018Ralli, Natascia and Norbert Andreatta 2018 “
bistro – ein Tool für mehrsprachige Rechtsterminologie.” trans-kom 11(1):7–44.
, 30) and may be a way of collecting information or terms that need to be inserted in the termbase
(see Section 4.4). Collaborative terminology work between language and
legal experts (Chiocchetti, and Wissik 2018Chiocchetti, Elena and Tanja Wissik 2018 “Kollaborative und kooperative Terminologiearbeit im Bereich Recht. Die Funktion der
Rechtsfachleute.” Parallèles 30(1):137–153.
) or wiki-style
collaborative content creation enabling multiple users to create, edit, search, and consult term entries (Kageura, and Marshman 2020Kageura, Kyo and Elizabeth Marshman 2020 “Terminology Extraction and Management.” In The Routledge Handbook of Translation and Technology, edited by Minako O’Hagan, 61–77. Abingdon: Routledge.
, 72) are more direct approaches to user
involvement.
Collaboration in terminology work (see Section 5)
reflects the growing popularity of peer-to-peer resources in all domains, including translation. For example,
forums in websites like ProZ22.
https://www.proz.com/ask (Accessed July 13, 2022) or Translators Café33.
https://www.translatorscafe.com/tcterms (Accessed
July 13, 2022) are widely used by language mediators (Biel
2008Biel, Łucja 2008 “Legal Terminology in Translation Practice: Dictionaries, Googling or Discussion
Forums?” SKASE Journal of Translation and Interpretation 3(1):22–38., 32). Gathering contributions from users has significant advantages, as it potentially allows large-scale content creation and may reach otherwise
inaccessible experts of a very specific domain. There are disadvantages, however, as the quality, consistency, and
coverage of the contributed data may not be constant or sufficient (Kageura,
and Marshman 2020Kageura, Kyo and Elizabeth Marshman 2020 “Terminology Extraction and Management.” In The Routledge Handbook of Translation and Technology, edited by Minako O’Hagan, 61–77. Abingdon: Routledge.
, 73), while traditional approaches leave terminologists in full control of the data.
There are also some crowdsourcing approaches in terminology (e.g., Cauna
2018Cauna, Eduards 2018 “The Wisdom of Crowds in Terminology Creation: Is it Working?” In Proceedings of the EAFT Terminology Summit 2018 “3M4Q Making, Managing, Measuring Terminology. In the
pursuit of Quality”, edited by UZEI, 51–52. Donostia: UZEI.
, 51; Karsch 2015Karsch, Barbara Inge 2015 “Terminology Work and Crowdsourcing. Coming to Terms with the Crowd.” In Handbook of Terminology, Vol. 1, 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 291–303. Amsterdam: John Benjamins.
). Overall, user participation and
interaction is considered to be insufficiently integrated into the design of TDBs in general (Vasiljevs et al. 2010Vasiljevs, Andrejs, Signe Rirdance, and Tatjana Gornostay 2010 “Reaching the User: Targeted Delivery of Federated Content in Multilingual Term Bank.” In Proceedings of the Terminology and Knowledge Engineering Conference “Presenting Terminology and Knowledge
Engineering Resources Online: Models and Challenges” (TKE 2010), 12–13 August 2010, Dublin, 38–39. Dublin: Fiontar.
). In other words:
We are facing […] a general dilemma in terminology management. On the one hand, we need mechanisms to catch up with the rapid growth of terminologies. Manual and/or in-house elaboration is not sufficient. On the other hand, we have not yet established proper quality control in terminology management that can work in large-scale automatic or collaborative environments.(Kageura, and Marshman 2020Kageura, Kyo and Elizabeth Marshman 2020 “Terminology Extraction and Management.” In The Routledge Handbook of Translation and Technology, edited by Minako O’Hagan, 61–77. Abingdon: Routledge.
, 73)
Finally, the growing role played by machines as new types of terminology users (see Section 5.7) implies that MLTDBs must also fulfill specific technical requirements to ensure data interoperability and reusability.
4.Workflows
Terminology work is complex and consists of a series of steps that may be carried out in sequence or in
various loops. What we call workflow in this chapter – a “specified way to carry out an activity or a
process” – is also known as procedure (ISO 9000 2015ISO 9000 2015 Quality Management Systems – Fundamentals and Vocabulary. Geneva: International Organization for Standardization.,
Clause 3.4.5).
There are many ways to systematize the different activities and processes involved in terminology work
because they depend highly on factors such as the type of terminology work and the setting where they are performed
(institution vs. company). Consequently, there are many models for terminology workflows described in literature, from
very generic ones to specific ones (inter alia Arndt et al. 2020Arndt, Tamara, Silvia Cerrella Bauer, Mark Childress, Klaus Fleischmann, Beate Früh, Regine Hellerich, Rachel Herwartz, Ana Hoffmeister, François Massion, Peter Oehming, Uta Schmitt, Ayten Turhan, Ulrich Wachowius, Annette Weiland, Cecil A. Woas, and Wolfgang Zenk 2020 “Module 5. Project and Process Management.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 1–24. Köln: Deutscher Terminologie-Tag e.V.; COTSOES 2002COTSOES – Conference of Translation Services of European States 2002 Recommendations for Terminology Work, 2nd ed. Bern: Federal Chancellery.
; Lušicky, and Wissik
2015Lušicky, Vesna and Tanja Wissik 2015 Procedural Manual on Terminology: Translation-oriented Terminology Work. Skopje: Secretariat for European Affairs.
; Popiołek 2015Popiołek, Monika 2015 “Terminology Management within a Translation Quality Assurance Process.” In Handbook of Terminology, Vol. 1, 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 341–359. Amsterdam: John Benjamins.
). Since legal terminology work has its own
particular features (see Section 3.1 and 3.2), there are also specific workflow models describing this type of terminology work
(Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC.
, 2017Chiocchetti, Elena, Tanja Wissik, Vesna Lušicky, and Michael Wetzel 2017 “Quality Assurance in Multilingual Legal Terminological Databases.” The Journal of Specialised Translation 27:164–188.
). A prototypical terminology workflow in the legal domain comprises the following steps: needs
analysis, design, documentation, term extraction, compilation of terminological entries (with contrastive analysis and
micro-comparison), revision and QA, maintenance, and dissemination (Chiocchetti
et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC.
, 2017Chiocchetti, Elena, Tanja Wissik, Vesna Lušicky, and Michael Wetzel 2017 “Quality Assurance in Multilingual Legal Terminological Databases.” The Journal of Specialised Translation 27:164–188.
).
Most workflow descriptions focus on collecting (legal) terminology and do not include the
conceptualization and creation of the termbase. This step happens prior to the terminology workflows described above
(inter alia Drewer, and Schmitz 2017Drewer, Petra and Klaus-Dirk Schmitz 2017 Terminologiemanagement. Grundlagen – Methoden – Werkzeuge. Berlin: Springer Vieweg. , 99ff;
Simonnæs 2018Simonnæs, Ingrid 2018 “Terminologische Datenbanken als Verstehens- und Formulierungshilfe beim Übersetzen von
Rechtstexten.” Parallèles 30(1):120–136.
, 126ff; Schmitz 2020Schmitz, Klaus-Dirk 2020 “Konzeption und Einrichtung von Terminologiedatenbanken. 12 Schritte zum Erfolg.” Edition 1:11–17.
, 11) or after the needs analysis step. Several decisions regarding the design,
data model, and data categories have to be made (Schmitz 2020Schmitz, Klaus-Dirk 2020 “Konzeption und Einrichtung von Terminologiedatenbanken. 12 Schritte zum Erfolg.” Edition 1:11–17.
, 11–17). Most
of them concern all types of termbases (e.g., applying the concept-oriented approach and the principle of granularity
of data categories, testing the prototype, and revising the data model) but some features, that are addressed in Section 3, are specific to legal termbases. These are reflected in the data
model of MLTDBs and the data categories used. In Section 4.2 we describe
the steps that are specific to MLTDBs.
4.1Needs analysis
The first step in the workflow is the needs analysis. Needs analyses can be described as the
systematic process of identifying and assessing needs in a certain community or situation. A need can be defined
as a gap between the current situation and the desired situation. The following actions are essential for
assessing the needs in legal terminology work: describing the current situation or problem, determining the
desired situation, defining one or more possible approaches to the problem, and implementing one or more solutions
(Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 14–16). During this step, the type of
terminology work (e.g., ad hoc, proactive, systematic) and the specific activities within the
terminology workflow required to solve the current problem must be defined. The time frame must also be set. A
possible need for systematic multilingual legal terminology work is the translation of the EU’s
acquis by an accession candidate. Another possible need triggering the revision of
multilingual legal terminology is a legal reform in a specific subdomain, e.g., criminal procedure law, within a
bilingual country. The needs analysis can also include an analysis of the requirements (see Section 6) regarding the design and implementation of an MLTDB, as described in Section 4.2, if the database does not exist yet.
4.2Design and implementation of MLTDBs
Before a termbase can be filled with legal terms, decisions on the design and data model have to
be taken according to the results from the requirements analysis in the previous step. The first decision is
choosing the legal systems and languages considered in the MLTDB. Since different legal systems may use the same
official language (e.g., German is used in Germany, Austria, Switzerland, Luxembourg, Lichtenstein, Belgium, and
Italy), it is important that MLTDBs specify their geographical and jurisdictional constraints (Nielsen 2014Nielsen, Sandro 2014 “Database of Legal Terms for Communicative and Knowledge Information Tools.” In Legal Lexicography. A Comparative Perspective, edited by Máirtín Mac Aodha, 153–175. London: Routledge., 161). This is often realized through the data category
geographical usage or legal system at term level.
The next decision consists in selecting the relevant data categories. Information in an MLTDB is recorded in terminological entries, which are subdivided into data categories. Data categories, e.g., definition, source, context, etc., can be seen as a “generalization of the notion of a field in a database” (ISO 12620-1 2022ISO 12620-1. 2022 Management of terminology resources – Data categories – Part 1: Specifications. Geneva: International Standardization Organization., Clause 3.2). Data category specifications for terminological resources are standardized according to ISO 12620-1 (2022)ISO 12620-1. 2022 Management of terminology resources – Data categories – Part 1: Specifications. Geneva: International Standardization Organization.. Due to the specific challenges outlined in Section 3.1 and 3.2, an MLTDB might need specific data categories that do not feature in other termbases such as legal system, degree of equivalence or notes with comparative information. After having decided on the data categories, their type has to be established (e.g., open or closed data category) and they must be associated to one of the three levels (concept level, language level, and term level). According to terminological principles, the definition should be at the concept level, since it describes the concept. However, owing to the specific features of legal terminology, definitions are often present at language level in MLTDBs. There can be one definition for each legal system with the associated source.
Once the data model has been created and implemented, the prototype can be tested with real data and real users and, if necessary, the data model can be reviewed and adapted.
4.3Documentation
Terminology work is mainly document-based (if sources are available as digital corpora, it is
called corpus-based terminology work), even though domain experts – legal experts in case of legal terminology
work – can also be used as a source of information. In legal terminology work, the rules applying to collecting
sources might deviate from standard rules in terminology work in other domains. First, the legal hierarchy of
sources, which is country dependent, must be considered separately for every domain in question, as not all types
of sources might be equally relevant in all domains (cf., e.g., the importance of international treaties for
international trade terminology vs. local legislation for childcare facilities terminology). In addition, texts
with different positions in the legal hierarchy (e.g., constitution vs. codices vs. decrees) might use different
terminology to regulate the same issue. Therefore, the legal hierarchy of a document is not necessarily the only
crucial aspect when deciding whether a document should be included into the source collection, its relevance for
the specific aim of the terminological project should also be considered. Even though the terminology project
might concern recent terminology, in legal terminology work texts written several decades ago might still be
fundamental as a terminological reference (e.g., the ABGB, i.e., the Austrian Civil Code, dates from 1812 and is
still in force). Additionally, translated texts with an official status such as international treaties or EU
legislation might need to be included into the source collection (Chiocchetti
et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 17–20).
4.4Term extraction
A crucial task in terminology work is to identify and record the potential terms, i.e., candidate terms, for later input into the terminological resource in question. Term extraction can be done in different ways: manually, by reading the source material and excerpting candidate terms, or via (semi-)automatic term extraction from electronic documents, including corpora and translation memories, for example (on automatic term extraction, see also Marín Pérez in this volume).
Different approaches are used for (semi-)automatic term extraction: statistical, linguistic, and
hybrid. The statistical approach applies statistical criteria to define the degree of termhood of candidate terms;
the linguistic approach applies linguistic filtering techniques to identify specific syntactic term patterns
(Heylen, and De Hertog 2015Heylen, Kris and Dirk De Hertog 2015 “Automatic Term Extraction.” In Handbook of Terminology, Vol. 1, 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 203–221. Amsterdam: John Benjamins. ; Pazienza et al. 2005Pazienza, Maria Teresa, Marco Pennacchiotti, and Fabio Massimo Zanzotto 2005 “Terminology Extraction: An Analysis of Linguistic and Statistical Approaches”. In Knowledge Mining, edited by Spiros Sirmakessis, 255–279. Berlin: Springer.
). A prerequisite for the linguistic approach is a part of speech tagged corpus.
Hybrid approaches combine different methods to recognize terms (Pazienza
et al. 2005Pazienza, Maria Teresa, Marco Pennacchiotti, and Fabio Massimo Zanzotto 2005 “Terminology Extraction: An Analysis of Linguistic and Statistical Approaches”. In Knowledge Mining, edited by Spiros Sirmakessis, 255–279. Berlin: Springer.
). There are several term extraction tools – open source or commercial – that require
different degrees of computational skills. Some tools can be used without programming skills (inter alia Kilgarriff et al. 2014Kilgarriff, Adam, Miloš Jakubíček, Vojtěch Kovář, Pavel Rychlý, and Vít Suchomel 2014 “Finding Terms in Corpora for Many Languages with the Sketch Engine.” In Proceedings of the Demonstrations at the 14th Conference the European Chapter of the Association for
Computational Linguistics, Sweden, 2014, 53–56. Gothenburg: Association for Computational Linguistics.
).
Extracting legal terminology contains a number of challenges that derive from the nature of the
process itself. One challenge is that some legal terms might not occur very frequently in a legal text. Sometimes
they only occur once in the title of a law, or in one paragraph, but they are still key terms in the specific
domain (Wissik 2014Wissik, Tanja 2014 Terminologische Variation in der Rechts- und Verwaltungssprache. Deutschland – Österreich –
Schweiz. Berlin: Frank & Timme., 127–129). Usually, statistical term extraction
methods have problems extracting such rare terms. Another challenge consists in disambiguating legal terms from
general language words, as some terms may be used in their ordinary meaning or with a legal meaning (Cao 2007Cao, Deborah 2007 Translating Law. Clevedon: Multilingual Matters.
, 21; Mattila 2012Mattila, Heikki E. S. 2012 “Legal Vocabulary.” In The Oxford Handbook of Language and Law, edited by Peter M. Tiersma and Lawrence Solan, 27–38. Oxford: Oxford University Press.
,
31). If manual term extraction is not done by a legal expert, some key terms might not be identified as legal
terms. Also automatic term extraction methods based on a comparison between specialized and general language
corpora might fail to extract relevant terminology. If term extraction is (semi-)automatic, the lists of candidate
terms have to be validated by terminologists or legal experts. Furthermore, information on terms to be included
into a terminological resource might also come from other input, e.g., automatic captures of unsuccessful searches
in the MLTDB or requests and feedback from users through a user feedback system (Arndt et al. 2020Arndt, Tamara, Silvia Cerrella Bauer, Mark Childress, Klaus Fleischmann, Beate Früh, Regine Hellerich, Rachel Herwartz, Ana Hoffmeister, François Massion, Peter Oehming, Uta Schmitt, Ayten Turhan, Ulrich Wachowius, Annette Weiland, Cecil A. Woas, and Wolfgang Zenk 2020 “Module 5. Project and Process Management.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 1–24. Köln: Deutscher Terminologie-Tag e.V.
, 13; Chiocchetti et al.
2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC.
, 21–22; Ralli, and Andreatta 2018Ralli, Natascia and Norbert Andreatta 2018 “
bistro – ein Tool für mehrsprachige Rechtsterminologie.” trans-kom 11(1):7–44.
, 30; see Section 3.5).
4.5Compilation of terminological entries
During this step, all the collected information, the terms, the definitions, the equivalents in other languages, etc., are inserted into their respective fields for the different data categories in the terminological entry as defined in the data model. In this phase, the methods borrowed from legal comparison as previously described (see Section 3.2) play an important role.
4.6Revision and QA
Revision can be divided into formal revision (e.g., check whether the entry is complete, all the
information is in the appropriate data category, hyperlinks are working), linguistic revision (e.g., spelling, new
term suggestions), and content revision (e.g., correctness of the definition, equivalence). Formal revision is
usually performed by terminologists or terminology database managers, linguistic revision by native speakers, and
content revision by legal experts (Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 28–30).
When developing new legal terms (e.g., when translating the acquis communautaire into the
language of an accession candidate), legal experts are also often involved in linguistic revision, as they
validate new term suggestions (Chiocchetti, and Wissik 2018, 144).
The quality assurance framework for MLTDBs considers the QA of the following four aspects:
persons, processes, products, and services supported by dedicated technology (Chiocchetti et al. 2017Chiocchetti, Elena, Tanja Wissik, Vesna Lušicky, and Michael Wetzel 2017 “Quality Assurance in Multilingual Legal Terminological Databases.” The Journal of Specialised Translation 27:164–188., 168–179). For more detailed information on QA see Section 6.4.
4.7Maintenance
To keep an MLTDB serving its purpose, a set of proactive activities have to be performed. These
activities can be classified as IT-related activities and as content-related activities. Among the IT-related
activities, there are software updates, server updates, user interface enhancements, bug fixes, data back-ups,
etc. Some content-related activities are improving single terminological entries, deleting duplicate terms,
merging terminological entries, performing global changes (e.g., after a spelling reform or a legal reform) as
well as reorganizing terminological resources (e.g., adding new data categories) (Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 30–31).
4.8Dissemination
Terminological data can be disseminated in different ways. Typically, terminological data are published in databases that are publicly available on the internet or only to a restricted audience, e.g., in an intranet. Furthermore, terminological data are also published as dictionaries or glossaries, online as well as in print format. Dissemination should take the different usage scenarios and target users of MLTDBs into consideration (see Section 3.3 and 3.4 respectively), so that terminological data can be structured according to the needs of specific user categories and shared in line with target user expectations.
With these forms of publication, the data can be accessed and looked up by human users, but they
often have the disadvantage that the data cannot be further processed. Since collecting, compiling, and
maintaining terminological resources is a very resource intensive work, already existing resources should be
(re)used as well for applications in other domains, e.g., Natural Language Processing (NLP). An obstacle in
reusing existing terminological data is that they are not findable, accessible, or interoperable. A way of
enhancing the findability and interoperability of language resources such as terminological resources is
publishing terminological datasets in standardized formats, e.g., TermBase eXchange (TBX) (ISO 30042 2019ISO 30042 2019 Management of Terminology Resources – TermBase eXchange (TBX). Geneva: International Standardization Organization.), Simple Knowledge Organization System (SKOS)44.
https://www.w3.org/TR/skos-primer/ (Accessed July 13,
2022) or OntoLex-Lemon,55.
https://www.w3.org/2016/05/ontolex/ (Accessed July 13,
2022) with their respective
metadata in repositories and catalogs (inter alia CLARIN ERIC 2021CLARIN ERIC 2021 Glossaries – Lexical Resources Family. Accessed July 13, 2022. https://www.clarin.eu/resource-families/lexical-resources-glossaries;
Lušicky, and Wissik 2019 2019 “Language Resources in Repositories and Catalogues: Pilot Study on their Potential for LSP Teaching
and Training.” In New Challenges for Research on Language for Special Purposes, edited by Ingrid Simonnæs, Øivin Andersen and Klaus Schubert, 327–342. Berlin: Frank & Timme.
, 330–332).
Another possibility is using methods coming from the field of Linked Data (LD) in the context of
the Semantic Web to publish terminological resources (Cimiano et al.
2020Cimiano, Philipp, Christian Chiarcos, John P. McCrae, and Jorge Gracia 2020 Linguistic Linked Data: Representation, Generation and Applications. Berlin: Springer. ; Martin-Chozas et al. in this volume). Linked Data “refers to interlinked collections of datasets
published on the Web” (Cimiano et al. 2020Cimiano, Philipp, Christian Chiarcos, John P. McCrae, and Jorge Gracia 2020 Linguistic Linked Data: Representation, Generation and Applications. Berlin: Springer.
, 4). The subset concerned
with linguistic data is called Linguistic Linked Data (LLD). In recent years, a number of approaches have been
proposed to publish terminological resources as LLD (Cimiano et al.
2015Cimiano, Philipp, John P. McCrae, Víctor Rodriguez-Doncel, Tatiana Gornostay, Asunción Gomez-Perez, Benjamin Siemoneit, and Andis Lagzdins 2015 “Linked Terminologies: Applying Linked Data Principles to Terminological Resources.” In Proceedings of the eLex 2015 Conference, edited by Iztok Kosem, Miloš Jakubíček, Jelena Kallas and Simon Krek, 504–517. Ljubljana: Trojina/Lexical Computing.
; Di Buono et al. 2020Di Buono, Maria Pia, Philipp Cimiano, Mohammad Fazleh Elahi, and Frank Grimm 2020 “Terme-a-LLOD: Simplifying the Conversion and Hosting of Terminological Resources as Linked
Data.” In Proceedings of the 7th Workshop on Linked Data in Linguistics (LDL-2020), edited by Maxim Ionov, John P. McCrae, Christian Chiarcos, Thierry Declerck, Julia Bosque-Gil and Jorge Gracia, 28–35. Paris: European Language Resources Association.
; McCrae et al. 2015McCrae, John P., Philipp Cimiano, and Víctor Rodriguez-Doncel 2015 Guidelines for Linguistic Linked Data Generation: Multilingual Terminologies (tbx). Accessed July 13, 2022. https://www.w3.org/2015/09/bpmlod-reports/multilingual-terminologies/; Montiel-Ponsoda et al.
2015Montiel-Ponsoda, Elena, Julia Bosque-Gil, Jorge Gracia, Guadalupe Aguado de Cea, and Daniel Vila-Suero 2015 “Towards the Integration of Multilingual Terminologies: an Example of a Linked Data
Prototype.” In Proceedings of the 11th International Conference on Terminology and Artificial Intelligence, Granada,
2015, 205–206. https://ceur-ws.org/Vol-1495/paper_31.pdf; Rodriguez-Doncel et al. 2015Rodriguez-Doncel, Víctor, Cristiana Santos, Pompeu Casanovas, Asunción Gomez-Perez, and Jorge Gracia 2015 “A Linked Data Terminology for Copyright Based on Ontolex-lemon.” In AI Approaches to the Complexity of Legal Systems, edited by Ugo Pagallo, Monica Palmirani, Pompeu Casnovas, Giovanni Sartor, and Serena Villata, 410–423. Berlin: Springer.
). Applying the LD
principle to publish (legal) terminological resources generally means using unique resource identifiers (URIs) so
that a particular terminological resource as well as a single term entry in the resource can be unambiguously
identified. Consequently, people can look the resource up, get useful information for it, and also discover
related resources (Cimiano et al. 2020Cimiano, Philipp, Christian Chiarcos, John P. McCrae, and Jorge Gracia 2020 Linguistic Linked Data: Representation, Generation and Applications. Berlin: Springer.
, 4–5). Furthermore, the data can
be processed and used in further applications; for example, terminological resources can be integrated into
knowledge bases to provide the reader of a legal text directly with a definition of terms used in the specific
legal text or to annotate legal texts, to classify them, and in question answering systems (Rehm et al. 2019Rehm, Georg, Julián Moreno-Schneider, Jorge Gracia, Artem Revenko, Víctor Mireles, Maria Khvalchik, Ilan Kernerman, Andis Lagzdins, Marcis Pinnis, Artus Vasilevskis, Elena Leitner, Ján Milde, and Pia Weißenhorn 2019 “Developing and Orchestrating a Portfolio of Natural Legal Language Processing and Document Curation
Services.” In Proceedings of the Natural Legal Language Processing Workshop 2019, 55–66. Minneapolis: Association for Computational Linguistics.
).
5.Roles
Legal terminology work includes cooperative as well as collaborative aspects.66.Cooperation focuses on reaching a common goal or creating a product through the division of labor,
while collaboration implies a more intense and regular interaction in the form of group work (Chiocchetti and Wissik 2018Chiocchetti, Elena and Tanja Wissik 2018 “Kollaborative und kooperative Terminologiearbeit im Bereich Recht. Die Funktion der
Rechtsfachleute.” Parallèles 30(1):137–153., 140). Thus, we can identify different roles in the workflow, those with
terminology/language-related expertise, those with management-related expertise, those with legal expertise, and those
with IT-related expertise (Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC.
, 40–53; Chiocchetti, and Wissik 2018; Lušicky,
and Wissik 2015Lušicky, Vesna and Tanja Wissik 2015 Procedural Manual on Terminology: Translation-oriented Terminology Work. Skopje: Secretariat for European Affairs.
, 31–37). However, not only humans play a crucial role in the terminology workflow. In the
last decade, machines (e.g., tools, machine learning algorithms and other AI applications) became increasingly
important, which is why this section will look at the roles of humans and machines within the terminology
workflow.
Regarding the roles of humans, be aware that a specific role is not necessarily bound to a single person but can be shared among more people in the team and a person can be involved in terminology work in different roles (e.g., as terminologist and reviser).
5.1Terminologists
Terminologists are experts in compiling, maintaining, and disseminating monolingual and multilingual specialized vocabularies. They are familiar with terminology theory and practical terminology work and are involved in several steps in the terminology workflow. They compile monolingual or multilingual terminologies, they are involved in terminology planning activities, and they provide consulting and training activities. Furthermore, they define workflows in terminology work and evaluate terminology related tools and software products. They draft requirements and specifications for these tools and software products, and they can be involved in their further development as well as in the data modeling of MLTDBs.
Terminologists may perform the following tasks (inter alia Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC.; RaDT 2004RaDT – Rat für Deutschsprachige Terminologie 2004 Professional Profile For Terminologists. Bern: Rat für Deutschsprachige Terminologie.
, 2020 2020 Berufsprofil 2.0 Terminologin – Terminologe, 2nd ed. Köln: Rat für Deutschsprachige Terminologie.
):
-
Collecting relevant source materials (in one or more languages) and study them;
-
Creating concept systems;
-
Extracting relevant designations from texts or corpora;
-
Conducting contrastive analyses with other languages/legal systems to find equivalents;
-
Compiling terminological entries (i.e., fill out all the required data categories and, if necessary, make translation proposals);
-
Updating existing terminological entries;
-
Reviewing terminological entries;
-
Modeling and defining workflows;
-
Cooperating in the planning, data modeling, and evaluation of terminology databases;
-
Disseminating terminological resources;
-
Assisting in standardization activities;
-
Assessing the quality of terminological resources.
Furthermore, terminologists can work closely with legal experts in all or some of these activities.
Terminologists may also carry out the role of terminology (database) managers and are responsible for the terminology management system and/or database, managing access rights, importing and exporting data, and backing up and archiving the data.
5.2Revisers
Revisers, also called reviewers,77.According to ISO 17100 (2015) reviser and reviewer are not
synonyms. A reviser is “a person who revises target language content against source language
content” (i.e., comparing source and target) while a reviewer is “a person who reviews target
language content” (i.e., monolingually). However, this distinction is not made in all contexts systematically. QA specialists, or QA
evaluators, can be language experts (e.g., translators), legal experts, or terminologists, depending on the type
of revision or quality assurance they are involved in. They may perform formal quality checks, revise the
terminology linguistically or from a legal point of view. They may give feedback on the quality of terminological
resources and document the revision or QA (inter alia Chiocchetti et al.
2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 2017Chiocchetti, Elena, Tanja Wissik, Vesna Lušicky, and Michael Wetzel 2017 “Quality Assurance in Multilingual Legal Terminological Databases.” The Journal of Specialised Translation 27:164–188.
; Drewer
et al. 2020Drewer, Petra, Ursula Fähndrich, Christina Kriele, Regula Miesch, Anna-Katharina Pantli, Donatella Pulitano, Peter Sandrini, Klaus-Dirk Schmitz, and Florian Simmen 2020 “Module 6. Professional Profile, Required Skills, Training Content.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 3–10. Köln: Deutscher Terminologie-Tag e.V.
, 5). For details on QA see Section 6.4.
5.3Terminology coordinators
Terminology coordinators, also called terminology project managers or terminology managers, have
management-related expertise and project management skills and are familiar with terminology work. They are in
charge of managing and coordinating terminology projects, terminology units, or language units. They are
responsible for a team of people and oversee the whole terminology workflow. Furthermore, they coordinate all
relevant activities throughout the entire workflow, facilitate the collaboration and cooperation between
terminologists and legal experts, and are the main contact for external stakeholders (Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 44–46; Drewer et al.
2020Drewer, Petra, Ursula Fähndrich, Christina Kriele, Regula Miesch, Anna-Katharina Pantli, Donatella Pulitano, Peter Sandrini, Klaus-Dirk Schmitz, and Florian Simmen 2020 “Module 6. Professional Profile, Required Skills, Training Content.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 3–10. Köln: Deutscher Terminologie-Tag e.V.
, 5).
5.4Legal experts as domain experts
Legal experts, as domain experts, can have different roles in the terminology workflow (Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 46–48; Chiocchetti, and Wissik 2018, 142–146).
They can act as consultants in various steps throughout the terminology workflow, participate as revisers in the
review and QA phase, be part of standardization committees, and are often the end users of legal terminology
products. Rarely do they act as terminologists, creating terminological entries on their own (Chiocchetti, and Ralli 2014 2014 “Experts and Terminologists: Exchanging Roles in the Elaboration of the Terminological Dictionary of
the Brenner Base Tunnel (BBT).” In Proceedings of the XVI EURALEX International Congress: The User in Focus, edited by Andrea Abel, Chiara Vettori & Natascia Ralli, 609–620. Bolzano: EURAC.
).
5.5IT experts
IT experts have expertise in information technology and are responsible for taking care of
administering, maintaining, developing, and enhancing tools for terminology work and related tasks (Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC., 49–51; Drewer et al. 2020Drewer, Petra, Ursula Fähndrich, Christina Kriele, Regula Miesch, Anna-Katharina Pantli, Donatella Pulitano, Peter Sandrini, Klaus-Dirk Schmitz, and Florian Simmen 2020 “Module 6. Professional Profile, Required Skills, Training Content.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 3–10. Köln: Deutscher Terminologie-Tag e.V.
, 5). Increasingly they are not only database experts but also come from the fields
of NLP, machine learning, Semantic Web, and AI. They develop new tools and methods to enhance the terminology
workflow, to enrich terminological resources automatically, and to explore new ways to disseminate terminological
data.
5.6Users of legal terminology
Besides traditional users like translators, interpreters, legal experts, legal drafters, people working in public administrations or international organizations, and the general public (see Section 3.4), IT experts from the fields of NLP, machine learning, Semantic Web, and AI are increasingly becoming users of terminology with the aim to enhance algorithms and develop new tools and applications in different domains (e.g., text mining, machine translation, question answering, robotics).
5.7Machines
AI and machine learning methods play an increasing role in different areas of the terminology
workflow, e.g., enhancing automatic term extraction (Marín Pérez in this volume), automatic definition extraction,
or automatic enrichment of terminological resources. They also facilitate the automatic creation of ontologies and
concept systems, as it is implemented, for example, in the WIPO Pearl termbase (Reininghaus 2018Reininghaus, David 2018 “WIPO Pearl – Patentwissen mit Struktur.” Edition 1:11–16., 15–16). They can also play a role in streamlining revision, e.g., by
predicting whether a candidate term will be approved based on previous data (Fleischmann 2021Fleischmann, Klaus 2021 “More Efficiency, New Opportunities, and Greater Benefits.” In #AskTheExperts – Terminology and Artificial Intelligence. Accessed July 13, 2022. https://www.gala-global.org/knowledge-center/professional-development/blogs/asktheexperts-terminology-and-artificial). Furthermore, terminological data can be used by machines in other areas such as
machine translation, text mining, and robotics. In this context it has to be stressed that terminological data
used by machines might have different requirements (e.g., data in machine readable form, data elementarity,
explicit data disambiguation) and also other quality criteria (e.g., veracity of metadata) than terminological
data used by humans.
6.Quality and MLTDBs
Since MLTDBs are embedded in multilingual legal communication with the intention to help harmonize
terminology and to avoid misunderstandings that may result from the different terms and their interpretations by
various stakeholders in these processes, the quality of MLTDBs is of
uttermost importance. Quality is neither an absolute nor entirely objective variable but is ultimately determined by
the stakeholders, users, and applications of MLTDBs. Quality refers to the “degree to which a set of inherent
characteristics […] of an object […] fulfils requirements” (ISO 9000 2015ISO 9000 2015 Quality Management Systems – Fundamentals and Vocabulary. Geneva: International Organization for Standardization.,
Clause 3.6.2). Requirements are expectations that can be generated by different stakeholders and can be a combination
of implied, stated, and obligatory requirements. The requirements in the scope of the quality of an MLTDB are informed
by the general methods of terminology management, quality management, translation quality management, and data quality
management.
Multilingual legal communication is usually supported by translation services that can be provided internally or outsourced to external contractors. In both cases, MLTDBs play a crucial role in assuring the quality of the translation services. By adequately deploying an MLTDB, it can be ensured that terminology is used correctly and consistently in translations. The terminology rendered in the scope of translation services is often fed back into MLTDBs and therefore depends on translation quality management. Given that MLTDBs are data-comprised products, data quality management principles should be considered as well.
6.1Quality management
Quality management refers to the development of policies, goals, and processes to achieve these
objectives (ISO 9000 2015ISO 9000 2015 Quality Management Systems – Fundamentals and Vocabulary. Geneva: International Organization for Standardization., Clause 3.3.4). In practice, MLTDBs are
embedded into multilingual legal communication and are therefore influenced by the quality management deployed by
the organization in which they take place. This means that the quality policy of MLTDBs should be consistent with
the overall quality policy of the organization.
Quality objectives are usually established for relevant functions or processes. MLTDBs are outputs of processes of an organization or several organizations (e.g., in the case of IATE, the European Union’s terminology database). On the one hand, they are products (databases) that implement requirements formulated along the lines of process quality, database data quality, and data model quality. On the other hand, they are also services, allowing for example querying, filtering, collaborative work, etc. Quality objectives ideally address both functions of MLTDBs.
The quality objectives regarding MLTDBs can be defined either as part of another product or
service (e.g., translation service) or as specificities of an MLTDB. In both cases, the quality objectives are
achieved through numerous sub-processes that follow the quality management framework outlined in ISO 9000 (2015ISO 9000 2015 Quality Management Systems – Fundamentals and Vocabulary. Geneva: International Organization for Standardization., Clause 3.3.4): quality planning, quality assurance, quality
control, and quality improvement.
6.2MLTDB and international standards
The primary purpose of standards is to define transparent and widely acknowledged conformity requirements. They increase the reliability, effectiveness, consistency, and efficacy of the product or service. It should be noted that there are neither international nor national standards that explicitly standardize legal terminology databases.
However, international collaboration on the standardization of terminology and terminology work in
general enjoys a long history and has produced several international standards that are applicable to MLTDBs. At
the international level, ISO Technical Committee ISO/TC 37 – Language and terminology oversees
terminology standards. In the following, we give a short overview of the most relevant standards (for more
information, see Kockaert, and Steurs 2015Kockaert, Hendrik and Frieda Steurs eds. 2015 Handbook of Terminology, Vol. 1, 2nd ed. Amsterdam: John Benjamins. ).
The core principles and methods of terminology and terminology work are specified in ISO 704 (2022)ISO 704 2022 Terminology Work – Principles and Methods. Geneva: International Organization for Standardization.
Terminology work – Principles and methods, and in ISO 860
(2007)ISO 860 2007 Terminology Work – Harmonization of Concepts and Terms. Geneva: International Organization for Standardization.
Terminology work – Harmonization of concepts and terms. Data categories for terminological
entries are specified in ISO 12620-1 (2022)ISO 12620-1. 2022 Management of terminology resources – Data categories – Part 1: Specifications. Geneva: International Standardization Organization.
Management of terminology resources – Data categories – Part 1: Specifications, and more in
detail in ISO 12616–1 (2021)ISO 12616-1 2021 Terminology Work in Support of Multilingual Communication – Part 1: Fundamentals of Translation-oriented
Terminography. Geneva: International Organization for Standardization.
Terminology work in support of multilingual communication – Part 1: Fundamentals of translation-oriented
terminography, including data categories relevant for the translation process and also for the
deployment of MLTDBs. Specific requirements regarding terminology products and services are addressed in ISO 22128 (2008)ISO 22128 2008 Terminology Products and Services – Overview and Guidance. Geneva: International Organization for Standardization.
Terminology products and services. Another useful standard dealing with terminology
standardization is ISO 15188 (2001)ISO 15188 2001 Project Management Guidelines for Terminology Standardization. Geneva: International Organization for Standardization.
Project management guidelines for terminology standardization. The requirements regarding data
modeling and the realization of terminological data interoperability are outlined in ISO 30042 (2019)ISO 30042 2019 Management of Terminology Resources – TermBase eXchange (TBX). Geneva: International Standardization Organization.
Management of terminology resources – TermBase eXchange (TBX). All published standards and
standards under development are listed in the ISO catalog.88.
https://www.iso.org/committee/48104/x/catalogue/p/0/u/1/w/0/d/0 (Accessed July 13, 2022).
6.3Quality planning
Quality planning entails setting the quality objectives and processes that are needed to achieve these objectives. Quality planning can be strictly focused on MLTDBs (e.g., a certain number of entries that will be checked by legal experts), but can also be implemented in the vertical quality planning of the organization (e.g., the technical infrastructure that will be available). Quality planning is ideally performed simultaneously and in combination with the overall terminology planning process. The planning should be adapted to the requirements of legal terminology work and workflows (see Section 4.2) and to specific MLTDB requirements.
The scope and depth of quality planning generally depends on the complexity and number of
requirements, as well as on the outputs of other processes. Requirements of preceding outputs should be formulated
and planned in consideration of subsequent processes. For example, if terminological ontologies have been deployed
as a means for concept clarification and conceiving concept definitions (Madsen, and Erdman Thomsen 2015Madsen, Bodil Nistrup and Hanne Erdman Thomsen 2015 “Concept Modeling vs. Data Modeling in Practice.” In Handbook of Terminology, Vol., 2nd ed., edited by Hendrik J. Kockaert and Frieda Steurs, 250–275. Amsterdam: John Benjamins. , 269), the conformity requirements and the quality characteristics of
terminological ontologies may influence the quality of MLTDBs.
The output of the quality planning process is a quality plan that includes a quality manual with detailed specifications, procedures (e.g., how to carry out a terminological activity), and qualitative and quantitative characteristics of an MLTDB, etc.99.A quality manual is often used or realized as a user manual, e.g., IATE’s User’s Handbook.
The characteristics of an MLTDB can be organized along the following categories into quality
criteria (Arndt et al. 2020Arndt, Tamara, Silvia Cerrella Bauer, Mark Childress, Klaus Fleischmann, Beate Früh, Regine Hellerich, Rachel Herwartz, Ana Hoffmeister, François Massion, Peter Oehming, Uta Schmitt, Ayten Turhan, Ulrich Wachowius, Annette Weiland, Cecil A. Woas, and Wolfgang Zenk 2020 “Module 5. Project and Process Management.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 1–24. Köln: Deutscher Terminologie-Tag e.V., 22–23; Chiocchetti et al. 2013Chiocchetti, Elena, Barbara Heinisch-Obermoser, Georg Löckinger, Vesna Lušicky, Natascia Ralli, Isabella Stanizzi, and Tanja Wissik 2013 Guidelines for Collaborative Legal/Administrative Terminology Work. Bolzano: EURAC.
, 28–29; Lušicky, and Wissik 2015Lušicky, Vesna and Tanja Wissik 2015 Procedural Manual on Terminology: Translation-oriented Terminology Work. Skopje: Secretariat for European Affairs.
,
69–71):
-
Linguistic (e.g., correctness of term creation, appropriateness of the terms in the given context or domain, misspellings);
-
Data-related (e.g., veracity, correctness of definitions, reliability, concept duplicates);
-
Formal (e.g., formal duplicates, number of entries, completeness of entries, language attribution, correct legal system attribution (see Section 3.2));
-
Data model-related (e.g., granularity of data categories, elementary nature of data categories, closed and open data categories);
-
Temporal (e.g., updates after a legal reform, availability of entries, timeliness of data entries);
-
Functional (e.g., query responsiveness, role management, querying, and filtering).
The documentation (e.g., records) of activities and results achieved should be part of quality planning. The documentation can be used later to monitor the effectiveness and efficiency of the quality measures and activities and to ensure traceability (e.g., the information provided by legal experts), verification of specific requirements met (e.g., the termbase covers specific legal systems and subdomains, provides for collaborative work, etc.), implementation of preventive actions to avoid nonconformity with the requirements, and corrective actions in case of nonconformity.
6.4Quality assurance and quality control
Quality assurance is “focused on providing confidence that the quality requirements will be
fulfilled” (ISO 9000 2015ISO 9000 2015 Quality Management Systems – Fundamentals and Vocabulary. Geneva: International Organization for Standardization., Clause 3.3.6). It entails the operations
taking place before, during and after devising, setting up, populating, and using an MLTDB. Quality control
is focused on fulfilling quality requirements (ISO 9000 2015ISO 9000 2015 Quality Management Systems – Fundamentals and Vocabulary. Geneva: International Organization for Standardization.
, Clause 3.6.5), making sure that the termbase complies with
the requirements for the intended use.
Some quality requirements can be objectively and quantitatively fulfilled (e.g., completeness of entries). On the other hand, several quality requirements, e.g., data-related criteria, such as the correctness of definitions, may be characterized by a degree of vagueness and interpretation in the scope of legal terminology.
QA should be conducted both routinely in each and through all production cycles but can be defined
as a stand-alone project in case of larger amounts of terminological entries. QA can focus routinely on all new
entries, on already existing entries for which feedback or requests have been received, or on random samples.
Routine maintenance of older entries is recommended, in particular to ensure that they do not contain obsolete
concepts or terms, that hyperlinks are still working, etc. (Arndt et al.
2020Arndt, Tamara, Silvia Cerrella Bauer, Mark Childress, Klaus Fleischmann, Beate Früh, Regine Hellerich, Rachel Herwartz, Ana Hoffmeister, François Massion, Peter Oehming, Uta Schmitt, Ayten Turhan, Ulrich Wachowius, Annette Weiland, Cecil A. Woas, and Wolfgang Zenk 2020 “Module 5. Project and Process Management.” In Terminology Work. Best Practices 2.0, edited by Deutscher Terminologie-Tag e.V., 1–24. Köln: Deutscher Terminologie-Tag e.V., 21). Terminologists should also regularly check duplicates at the concept and term level.
Ideally, each entry and data category is checked by a terminologist and a reviser (see Sections 5.1 and 5.2 respectively) against predefined quality criteria. Depending on the set of quality criteria that are being checked, several revisers may be involved: a legal expert may check the quality of data in terms of veracity and reliability, while a language expert may check the linguistic correctness of a term and its linguistic attributes. QA is supported by role and workflow management components of the terminology management tools which streamline the terminology processes and keep track of ongoing or finished tasks, thereby also documenting the process.
The operationalization and the precise moment during which QA is performed also depends on the
setting and the purpose of the terminology work (descriptive, prescriptive, normative). For example, if an MLTDB
is used as part of a translation process, it may be deployed as a prescriptive requirement of translation quality,
for instance as a quality gate. Quality gates are milestones that require that predefined criteria be met before
proceeding to the next step. In such settings, an MLTDB is used before and during translation as well as in the
revision stage as an instrument of translation quality assurance (ISO 17100
2015ISO 17100 2015 Translation Services – Requirements for Translation Services. Geneva: International Organization for Standardization.). This means that the QA of the termbase or the relevant entries may need to be finalized before
the translation process.
7.Conclusions and outlook
In this chapter, we have described the specific features of MLTDBs and illustrated the steps within a typical workflow for creating MLTDBs, i.e., needs analysis, design, documentation, term extraction, compilation of terminological entries, revision and QA, maintenance, and dissemination, the roles involved, and the users of MLTDBs. We have shown that users, workflow, roles, and QA partly differ in MLTDBs from TDBs in other domains. We have also discussed that there is a need for more flexibility within MLTDBs in consideration of different and/or new users and usage scenarios (e.g., different access to the same data by humans and machines, different data visualizations for various user categories, navigation via concept systems/ontologies and not just through designations, etc.). Moreover, we have covered the topic of quality, which is of uttermost importance to avoid misunderstanding in a multilingual communication setting, and discussed how to implement quality planning, assurance, and control in MLTDBs. Database quality is a particularly challenging aim when dealing with the legal domain, which is also difficult to define, due to the unique linguistic and system-bound aspects of this domain. Furthermore, we raised the issue that terminological data used by machines might have different requirements and also other quality criteria than terminological data used by humans.
We argue that some of the activities within the workflow and some of the roles have changed following the development of recent technologies and methods. For example, the role of IT experts changed from that of pure database experts, who are involved in implementing the database and maintaining it, to that of experts in the fields of NLP and machine learning, who are involved in developing new methods to enhance the terminology workflow, to enrich terminological resources automatically, and to explore new ways of disseminating terminology.
Finally, we have touched on the issue of machines being increasingly involved in the legal terminology workflow. They can support quite labor-intensive terminology work (e.g., term extraction, automatic ontology creation) as well as streamline the revision process. Furthermore, terminological data can have application scenarios in areas such as machine translation, text mining, or smart systems.