Terminology and Terminological Databases

578 Terminology and Terminological Databases

Terminology and Terminological Databases K-D Schmitz, Fachhochschule Ko¨ln, Ko¨ln, Germany ß 2006 Elsevier Ltd. All rights reserved.

What Is Terminology? Terminologists, maybe even more so than other subjectfield specialists, have problems agreeing on the terminology that they use within their own discipline. (Wright and Budin, 1997: 325)

This statement of Wright and Budin was both well put and accurate, for terminology scientists and terminology workers don’t use the term terminology with an unequivocal definition. In its first meaning, terminology is the ‘‘set of designations belonging to one special language’’ (ISO 1087–1, 2000). This definition is used when we refer, e.g., to the terminology of mechanical engineering or the terminology of medicine. Some experts also differentiate between the set of terms itself and the publication of these terms in (terminological) dictionaries. A second interpretation of terminology refers to the scientific discipline that studies ‘‘the structure, formation, development, usage and management of terminologies in various subject fields’’ (ISO 1087–1, 2000). A clear distinction between these two meanings of terminology is necessary, not just for the purpose of this article. Following the definitions in the German terminology standard DIN 2342 (2003), of Wright and Budin (1997: 325) and other authors, ‘terminology’ is the (structured) set of concepts and their representations in a specific subject field. The second meaning of terminology is called ‘terminology science’ (or terminology studies, but not terminology) and is defined as the scientific discipline dealing with concepts and their representations in special languages.

Why is Terminology so Important Today? The present age is characterized by an increase in knowledge in almost all technological, economic, political, and cultural fields. Modern communication and publication methods and media allow the swift and broadscale transfer of this knowledge. But the spread of knowledge is not limited to a closed group of specialists or to one language community. Translators and interpreters play an important role in this multilingual communication process across language boundaries. Since a high percentage of specialized knowledge is documented and published by means of language, correct terminology is a prerequisite for efficient knowledge transfer. All people who are involved in

any way with special language texts must deal with the terminology of the domain in question, whether they function as experts who must read and understand texts, as technical writers who produce texts, or as technical translators who transfer their content into another language.

Historical Development of Terminology Science The need to define and compile terminologies was recognized at the time when special and professional languages were developing. Individual scientists, researchers, and engineers from the 15th century onward have been concerned with the definition and ordering of the knowledge of their respective domain, and with the preparation of terminologies, such as Leonardo da Vinci in engineering, Gottfried Wilhelm Leibniz in mathematics, Albrecht Du¨ rer in geometry, Antoine Laurent Lavoisier in chemistry, Carl Linnaeus in biology, and others. Another pioneer in developing multilingual terminological dictionaries was Alfred Schlomann, who published systematically arranged vocabularies for 17 different subject fields between 1907 and 1932. Each of these comprehensive technical dictionaries was developed by a team of subject field specialists, applying ‘terminological’ guidelines defined by Schlomann. Also at the beginning of the 20th century, national and international standards organizations were founded to support technical cooperation by defining and specifying properties of parts and tools. Soon after the establishment of technical committees for standardization, terminological subcommittees were founded to define and standardize the technical vocabulary of the different domains. The dissertation of the young Austrian engineer Eugen Wu¨ ster, published in 1931 under the title ‘Internationale Sprachnormung in der Technik’ (‘International standardization of language in technology’), provided the impetus for the foundation of ISA’s Technical Committee TC 37 ‘Terminology and the preparation of terminological principles’, which was re-founded after World War II as ISO/TC 37. Wu¨ ster was not only the founder of the General Theory of Terminology (see Wu¨ ster, 1991 and Picht and Schmitz, 2001), but he was also engaged very much in the creation of the first international terminology standards, improving and testing the standards by elaborating and compiling his systematic terminological dictionary The machine tool. Wu¨ ster is often called the founder of the Vienna School of Terminology. Felber (1984) also described the Prague School of Terminology (developed from the

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Prague School of functional linguistics) and the Soviet School of Terminology (D.S. Lotte and E.K. Drezen). Basic research in terminology principles and theory took place in Canada, Germany, the United Kingdom and in the Nordic countries in the second half of the 20th century. Today we find terminological activities also in other parts of the world, especially in Spain, France, North and South America, and in China. Figure 1 The terminology triangle.

The Basic Theoretical Background for Terminology Management This section will present the basic principles and fundamental concepts treated in terminology science, focusing on those aspects that are essential for performing practical terminology management activities and establishing terminological databases. Of course, this article cannot cover all theoretical and practical aspects. For more detailed treatments of the entire field of terminology studies and terminology management activities, see in particular Arntz et al., 2002; Dubuc, 1992; Felber and Budin, 1989; Sager, 1990; Wright and Budin, 1997, 2001; and Wu¨ ster, 1991. Over time, people who have to deal with terminology have developed methods and procedures for managing terminology. These basic principles governing terminology activities and management have developed into a scientific discipline, which has itself been called ‘terminology science’ or ‘terminology studies’. Both the definition of terminology and the general principles of terminology science deal with concepts and terms. Originally, terminology theorists and researchers adapted the so-called ‘‘semiotic triangle’’ introduced by Ogden and Richards (1923) to explain the relationship between concepts and terms (Figure 1). The triangle has undergone a long history of modifications and interpretations, and has also been attacked from several quarters as an oversimplification or misrepresentation of the complex relationships that exist between concepts and terms, concepts and concepts, and terms and terms. Despite the criticisms that have been leveled against the triangle, its simplicity makes it an excellent tool for illustrating conceptterm relationships to people who are just beginning to identify terms in texts, and to create terminological data entries to document them. Consequently, we will use the triangle to discuss these three elements, bearing in mind that it is just a useful tool and does not necessarily address complex linguistic, cognitive, or philosophical issues. Object

An object as represented in the triangle in Figure 1 is an entity existing in the world in which we live.

Objects don’t have to be concrete objects, e.g., things you can touch, smell, or see. They can also include abstract objects that are not part of the perceivable world, but that are nonetheless real components of human thought. (1) Example of a concrete object: a computer keyboard. (2) Example of an abstract object: hyphenation.

It is useful to cast a wide definition for the concept of an object and to include more complex states of affairs and even processes within the notion of an object. In this sense, objects can even have a sort of propositional nature and be represented by collocations and phrases, such as: ‘hyphenation of the current text’ or ‘format a new diskette’. Wu¨ ster (1991) clarified the notion of the object by talking about individual objects. He explained that it is not the computer keyboard as such that exists in the world, but rather that there exist numerous individual computer keyboards. The overall class represented by computer keyboard comprises a conceptual ‘type’, for which individual instances of keyboards are ‘tokens’. Concept

Concepts are ‘‘cognitive representatives’’ (Felber and Budin, 1989) for objects, stand-ins, as it were, that arise out of the fact that humans recognize the common characteristics that exist in a majority of individual objects of the same type, and then store these characteristics (e.g., remember them) and use them to impose order on the world of objects, in order to achieve mutual understanding when they communicate with other people. ISO 1087–1 (2000) defined a concept as a ‘‘units of knowledge created by a unique combination of characteristics’’. Characteristics, as they are understood in this definition, are those properties of the objects in the given class of objects that are used to form and delimit the concept. Modern cognitive science and neuroscience are not in agreement on precisely how concepts are generated or stored in the brain, nor is it totally clear how they come to be associated with specific terms or other conceptual representations. However,

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even the strictest empirical research supports the thesis that cognitive units (concepts) are formed in our minds, and we associate these concepts with verbal or nonverbal representations (terms, symbols, etc.). Concepts are not necessarily bound to specific languages, but the cultural and social background of the human beings who generate the concepts and the environments in which they are used affect the way they manifest themselves in any given situation. Variations in conceptual orientation can reflect cultural and social differences; these are derived from regional differences within a language community, or differences between communities where different languages are spoken, or even different ethnic and class differences between individuals who may only speak variant dialects of the same language, and who live in close contact with one another. We should also note that one can distinguish between individual concepts and general concepts. An individual concept refers to an individual object, such as the Starship Enterprise or the Cologne Cathedral, while general concepts comprise the characteristics of a class of objects (spaceship, cathedral). Relationships between Concepts and Concept Systems

Concepts can be related to one another based primarily on the characteristics with which they are associated. These conceptual relations can be of a hierarchical or nonhierarchical nature. Hierarchical concept relations can be further divided into generic relations and part-whole relations. Some writers in English speak of hyperonymic or meronymic concept systems. Generic relations, which are also called logical or abstract relations, are characterized by the fact that a relation can be defined between a broader (superordinate) concept and a narrower (subordinate) concept, such that the subordinate concept contains all the characteristics covered by the superordinate concept, with the addition of at least one additional characteristic. The term designating the superordinate concept is often called a ‘hyperonym’, and the term designating the subordinate concept is called a ‘hyponym’. Concepts that occur at the same level are called ‘coordinate concepts’, and their terms are called ‘co-hyponyms’. Let us take an example from the evolution of computer hardware. (3) Example: printer and laser printer. A printer can be any one of several types of devices that creates an image on paper (or perhaps some other medium, like a T-shirt) representing text or graphics created in a computer program; a laser printer is a device that can be defined in precisely this way, with the addition of the characteristic that it uses laser technology to create the image.

Meronymic relations (part-whole, partitive relations) are characterized by the fact that the broader concept (superordinate concept) in this case can be conceptually broken down into its individual components. (4) Example: A printer consists of the print head, the paper tray, the paper feed, the control panel, the housing, etc.

Nonhierarchical conceptual relations are defined less frequently than hierarchical ones. These can include, for instance, sequential relations that represent chronological sequences or cause-and-effect relations. Going beyond comparing just two concepts and looking at many of the concepts or even all of the concepts in a subject field, a conceptual field is created. For these terms to form a concept system, it is necessary to identify a certain order among the concepts. In a closed concept system, i.e. one where all the concepts intended to document a given subject field have been collected, the concepts can be arranged in order according to their concept relation, then each concept is assigned a position number within the system. These systems order concepts according to superordinate and subordinate positions within generic or partitive systems (x is a y, or x has a y), and they even assign rules for concept behavior at certain nodes in the system. In dynamic systems, meaningful position numbers become problematic because new items are constantly being added at different intersection nodes within the system. In such cases, new views of concept structures can be generated as needed ‘at run time,’ based on socalled ‘parent-child’ relationships. If the intention is to represent a concept system and the concept relations contained in it, it is common to use either a graphical representation or a numerical code. In Europe, it has been common to use tree diagrams to represent generic systems and bracket diagrams for part-whole relations. This distinction has not necessarily been followed in North America, where tree diagrams are commonly used to represent both types of hierarchical relations. When numerical codes are assigned for closed concept systems, the different hierarchical levels (sometimes referred to as levels of abstraction) are assigned different numerical levels. This practice produces numbers where decimal points represent the levels of abstraction. Sometimes dashes are used in part-whole systems to represent levels of meronymic relations. Figure 2 is an example of a generic system using tree diagrams and notation. Figure 3 is an example of a part-whole system with a bracket diagram. Sometimes it is useful to create hybrid diagrams showing both generic and part-whole relationships in a graphical or notational system (Figure 4).

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Figure 4 Hybrid concept system for mouse. Figure 2 Tree diagram for a generic concept system.

We use the word ‘designation’ as a superordinate concept when we talk about terms because there are also other ways to represent terms, e.g., ones that aren’t necessarily made up of words, such as symbols, formulas, pictograms, etc.

Figure 3 Bracket diagram for part-whole concept system.

Today in many companies and government agencies, information specialists and knowledge engineers are creating what are often called ‘ontologies’, or ‘taxonomies’, showing all the major terms and data objects that are managed in the enterprise’s databases and documents. These resources look very much like the concept systems mentioned above because they are usually arranged according to generic or part whole principles. They are generally ‘open systems’ that are constantly under development and consequently don’t have position numbers. One special feature of many ontologies is that the individual nodes in the conceptual structure can be associated with rules. For instance, in a concept system for vehicles, there might be an axiom (a rule) that states: All cars with a crankcase year of 1965 or later are subject to emission control regulations in the state of California. A computer program or intelligent agent on the World Wide Web could use this kind of axiom to find information and even ‘make decisions’ based on the ontology and the rules embedded in it. Term

The third corner of the terminology version of the semiotic triangle is represented by the ‘term’. ISO 1087-1 defined the term as a ‘‘verbal designation of a general concept in a specific subject field’’. The term serves as the representation of the concept. We can write it down, think it, say it out loud, use it for communication.

Example: H2SO4 Sulfuric acid TM Õ Trademark, registered trademark Telephone Poisonous, dangerous 1 Infinity

Some terms consist of more than one word. These terms are called multiword terms or compounds. In Germanic languages such as in English and German, multiword terms usually consist of several nouns or adjective noun combinations. The way words combine to form terms varies from language to language. Example: Single-word terms: Multiword terms:

printer (Eng); Laserdrucker (Ger) laser printer (Eng); CentronicsSchnittstelle (Ger) printer with single-sheet feed (Eng) Drucker mit Einzelblatteinzug (Ger) serial port (Eng); serielle Schnittstelle (Ger)

Terms always designate class concepts, e.g., skyscraper designates all objects that can be defined as buildings that are more than 20 stories tall. Verbal representations of individual concepts (a specific object) are called names, e.g., the Empire State Building is one specific skyscraper. There is no other building with this name. There are any number of rules and precedents for forming terms, which we will not outline here (see Arntz et al., 2002; Felber and Budin, 1989; Sager, 1990; Wu¨ ster, 1991). As noted above, typical multiword formation patterns differ from language to language (Typeraddrucker, daisy wheel printer, imprimante a` marguerite); consequently, the distinction of single and multiword terms is often a fluid one in multilingual terminology management.

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Figure 5 Synonymy.

Relationships between Terms and Concepts

We have seen that the term is the verbal representation of the concept. In special or technical language, it is highly desirable that this relationship be unambiguous, even without contextual reference, which means that one term should be assigned to one concept, creating a condition called univocality. When this condition prevails, the meaning of terms is completely clear, even if the term appears without any explanatory context. Of course, this ideal situation is difficult to achieve or enforce. Two problems involving term-concept assignment recur frequently, even in technical and scientific texts: ‘Synonymy’ exists if two or more terms in a given language represent the same concept. Thus a synonym is a term used to designate the same concept as another term (Figure 5). (5) Example: enter key, input key, return key, carriage return.

Even though synonymy can compromise communication between experts, it occurs quite frequently in practice. This can happen especially in subject fields where many objects and concepts are still undergoing development. In these kinds of dynamic fields, competing terms are used in parallel until unambiguous terms are gradually established, either through a natural selection process or by conscious standardization. Even when people are aware of these problems, variants can remain in use for long periods of time, based on such factors as natural regional variation or, quite intentionally, company or product-specific efforts to use terminological differences as one means of positioning a product in the market. In some cases, two or more terms are similar in many ways but don’t quite totally cover the same concept. Such terms are call quasi-synonyms and are mutually interchangeable only in certain contexts. ‘Homonymy’ involves the opposite situation from synonymy: here a term or several terms that have the same external form refer to several concepts. ISO 1087–1 (2000) defined homonymy as a relation between designations and concepts in a given language,

Figure 6 Homonymy and polysemy.

in which one designation represents two or more unrelated concepts (Figure 6). (6) Examples: mouse (animal) vs. mouse (input device for computers) stud (horse) vs. stud (fastener) vs. stud (architectural framing member)

In English linguistics and grammar, what we are calling ‘homonymy’ is frequently viewed either from the standpoint of ‘polysemy’ (words having multiple meanings) or ‘homonymy’ (concepts having ‘homogenized’ names). The same word used metaphorically to designate two different things is a polyseme (e.g., mouse (animal) and mouse (of a computer), or stud (fastener) and stud (framing member), which come from the same original linguistic root. Stud (horse) and the two examples of stud as fastener or framing member are, according to this view, ‘true homonyms’, because the two usages come from different etymological roots. The top section of Figure 6 illustrates the condition of ‘polysemy,’ i.e., one term represents several concepts, whereas the second half of the illustration reflects true homonymy, where the same word form just happens to represent different concepts (which is what happens with stud the horse and stud the fastener). Although the distinction between polysemy and homonymy is considered important in linguistics, in terminology management it is not viewed as highly important, because the two phenomena result in the same pragmatic word behavior: the same word form represents more than one concept. In termbases, we often call these duplicate terms ‘doublettes’, because the same word may occur as an index two or more times in a concept-oriented termbase, each time with a different meaning.

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Homonyms pose huge problems for technical communication. As a consequence, experts are constantly striving to avoid homonyms in technical subject fields. Nevertheless, when new concepts evolve, people like to form new terms for them by combining familiar existing terms or by adopting established terms from general language (e.g., mouse for a computer input device), from other related subject fields (e.g., the use of terminology taken from steelmaking and glass-making, applied to plastics), and from other (foreign) languages (e.g., the widespread use of English terminology in other languages for various computer applications and in the World Wide Web). Consequently, homonymy frequently occurs at the interface between specialist domains. The third phenomenon involving the relationship between concepts and terms that plays a role in multilingual terminology management comprises the transition from one language to another. ‘Equivalence’ is the relation between designations (e.g., two different terms) in different languages, representing the same conceptual characteristics, and thus the same concepts. Of course, as we have already noted, concepts are influenced by social and cultural conditions, and it is not always possible to establish full equivalence. The problem of incomplete equivalence occurs frequently in general language and in certain specialist domains, such as the language of the law when different language communities possess different legal systems. This is even apparent, for instance, when we compare the legal language used in the United States and in Great Britain: sometimes the same terms are used to mean different things, but in other cases, different terms may be used to designate essentially the same concepts. Old technologies like steelmaking and glass-making tend sometimes to designate dissimilar concepts in different languages, because practice and terminology evolved independently in different language communities; but in newer fields like computer science, AIDS research, and genetic engineering term-concept pairs tend to be much more symmetrical between languages, because scientific and technical development in today’s world moves ahead in parallel in most major languages. There is a great deal of borrowing and loan translation, which makes it much easier to establish true equivalence between languages. Essentially, equivalence constitutes the same phenomenon on an interlingual level (e.g., between two or more languages) that we see intralingually (within the same language) when we talk about synonymy. Equivalence problems can also occur if we draw up concept systems in two or more languages and then try to just transfer concepts from one language to the other or to compare them without taking potential

conceptual or systematic differences into account. Sometimes, hierarchical relations manifest themselves differently in different languages or some concepts are missing in some languages (so-called ‘terminological lacunae’). For instance, in the area of toolmaking and die-making, German divides tools and processes into spannende and spannlose Fertigung: chip-forming and non-chip-forming manufacturing. English, in contrast, thinks of these processes as involving cutting and shaping, and consequently creates hierarchies for tools and processes that may look very different from concept systems created for the same basic subject field in German. Whenever a new object is invented in the real world, lacunae exist until someone decides what to call the new object in a given language. Frequently, terms will be borrowed from other languages to fill these conceptual holes, but just as frequently, the concept covered by the new term in Language B may not be quite the same as the original concept in Language A. Terminological Databases

The first attempts to use computer technology for managing terminological data started in the early ’60s of the last century. There was an urgent need for national and international institutions and for multinational companies with large translating and interpreting services, because very often a great number of translators had to co-operate in large projects under great time pressure, in order to meet deadlines. Due to the restrictions resulting from the hardware and software components available at that time and due to the organizational infrastructure needed for operating mainframe computers, only economically strong organizations and institutions could afford to implement and maintain their own terminological databases. It is therefore not surprising that the first terminological data banks were set up in large language services belonging to governmental organizations and big enterprises, in standards bodies and in language planning institutions, e.g.: . LEXIS (Federal Office of Languages, Germany) . TERMIUM (Language service of the Canadian government) . EURODICAUTOM (Commission of the European Community) . TEAM (Siemens AG, Germany) . AFNOR (French Association for Standardisation) . BTQ (Office de la langue franc¸ aise, Canada) Most of these large terminological data banks (term banks) have been maintained and used within their respective institutions down to the present day, so that they contain hundreds of thousands of entries. The terminological data in some of the large data

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Figure 7 Eurodicautom terminology database.

banks are also accessible for external users on CD-ROM or via the Internet (Figure 7). The first generation of term banks with their pragmatic and often institution-specific design was succeeded by a research-oriented development which, on the one hand, helped reveal the conceptual weakness of the individual data banks and, on the other hand, created new concepts, which again led to the development of corresponding software. Examples of this trend are the DANTERM database, developed at the University of Copenhagen, and the Ericsson CAT system, used in the language departments of some German companies and governmental organizations. Both systems are based on a concept-oriented approach to terminology management and run on midsized computers. But with the breakthrough of microelectronics and the burgeoning population of (networked) personal computers even in the environment for terminology work, these systems were replaced by PC-oriented terminology management

systems. Today, we find client-server terminology databases that allow web-based cooperative terminology work by terminologists and terminology users across the world. But terminology databases are not just used as stand-alone applications for terminology management, they are also integrated into workbench systems and communicate with word processors, publication systems, translation memories, and machine translation systems. Professional features and additional components for project management, data interchange, and term extraction facilitate comprehensive application in larger language, translation, or terminology services (Figure 8). Design and Implementation of Terminological Databases

The needs of the different user groups involved in developing and retrieving terminology, as well as the organizational environment in which terminology management takes place, have a strong impact on the

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Figure 8 MultiTerm iX web-based sample terminology database.

conceptual design of a terminological database. It is very important to specify the types of data (terminological data categories) that should be managed, and to define the data model (terminological entry structure) that will form the basis of the termbase. The selection and specification of ‘terminological data categories’ should be based on ISO 12620 (1999), which lists and describes more than 200 data categories useful for terminology management. According to this standard and other publications dealing with terminology management, terminological data categories can be grouped under various headings, depending on whether they are conceptrelated or term-related, or contain administrative data. Concept-related terminological data categories comprise those data elements that refer to the concept underlying a terminological entry or describing

the relationship between this concept and other concepts. Typically used concept-related data categories are: . . . . . . .

Definition Subject field/domain Illustration/symbol/formula Classification/notation Superordinate concept Subordinate concept Co-ordinate concept.

Term-related terminological data categories contain those data elements that refer to one particular term representing the concept. The set of term-related data categories must be repeated for each term assigned to the concept, within one language (e.g., for synonyms) or for several languages (e.g., equivalents). Useful term-related data categories are:

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Figure 9 Term autonomy realized in MultiTerm ‘95 Plus.

. Term (including synonyms, abbreviated form, and orthographical variants) . Term type . Context/example . Grammatical information (gender, part of speech, number) . Geographical restriction . Linguistic restrictions . Register . Project code/company code. Administrative data categories refer to the entry as a whole, or to individual concept-related or termrelated data categories within this entry. Administrative data categories include: . . . . . .

Identification number (entry number) Date (creation/last update) Author (creator/checker/editor) Source Reliability Note/annotation/comment.

The selection and specification of terminological data categories is a very important step in the design of a terminological database. Modifications and re-specifications of data categories are very labor- and costintensive when the database is already filled with data. The next step in designing terminological data bases is the definition of the ‘terminological entry structure’, i.e., a systematically hierarchical arrangement of data categories. ISO 704 (2000), ISO 12200 (1999) and ISO 16642 (2003) provided good guidance for this data modeling process. Two major principles should be mentioned in this context. Per definition, a terminological entry has to contain all terminological data related to a given concept (ISO 1087–1, 2000). Therefore, the entry structure has to reflect the principle of ‘concept orientation’, thus allowing for the maintenance not only of all concept-related information, but also of all terms in all languages with all term-related information within a particular terminological entry. Terminological entries designed according to the principle of term

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orientation, which we very often find in bilingual glossaries or dictionaries, are not appropriate for meticulous terminology management and will quickly lead to inconsistent terminology collections that are not very useful, especially if multilingual terminology management is required. The second important principle of terminological entry modeling is ‘term autonomy’. Term autonomy guarantees that all terms including synonyms, abbreviated forms and spelling variants can be documented with all necessary term-related data categories. This approach can be realized by designing the data model in a way that allows the user to create an unlimited number of term sections, or term blocks, containing individual terms and all additional data categories describing the term and its use. Figure 9 shows an example of a monolingual terminological entry following the principle of term autonomy. See also: Bilingual Lexicography; Definition; Lexicogra-

phy: Overview; Thesauruses.

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