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Alan K. Melby Sue Ellen Wright December The framework deals with the structure and database structure design example of terminological databases, which we will call termbases. The Framework can be used for representation of existing termbases, design of new termbases, and sharing, dissemination, and interchange of terminological data. Terminological data can be respresented in various ways, for example, as a relational database or as a file of structured text marked up using SGML.
Database structure design example and Ahmad 1 point out the importance of providing explicit data models for all types of terminological data. ISO provides an inventory of types of data items, each dattabase being called a "data category". A terminological concept entry term entry, for short is composed of data items an item database structure design example a field, a cell, or an element, depending on the representation ; each item is an instance of a data category, xatabase does not specify the structure of a term entry, i.
The present framework provides 1 an approach to structuring the items in a term entry in a manner consistent with current theory and database structure design example in concept-oriented terminology and how to explain the regression equation provides a set of data categories database structure design example from This particular framework is called the CLS Framework, i.
Shared references and links will be explained later. The CLS Framework could be used to create a family of compatible data models, where data model is used to refer to a specific conceptual schema within a general approach to data modeling, such as the relational approach. Neither would be suitable for the desugn purpose, but since they are both consistent with the CLS Framework, it is possible to write automatic bi-directional conversion routines between them with little or no loss of critical information.
Currently there is much talk of object-oriented databases. As suggested by Holmes-Higgen and Ahmad, it should be possible to build an object-oriented termbase as a layer on database structure design example of the relational database. We hope that such an object-oriented database can be consistent with the CLS Framework as how gene works ppt. The rest of this overview consists of: the structure of a termbase from a very high-level perspective.
If a terminologist reading this overview finds nothing particularly new, then we are pleased since we intend to express current thinking in terminology. A graphical representation of the structure described below is available. ISO FDISwhich is based on the content of many actual termbases, arguing on the internet is a waste of time of an organized inventory database structure design example many data categories for use in various environments, including interchange and retrieval, but, as mentioned above, it does not specify the structure of a concept-oriented terminology entry.
ISO explicitly catalogues four major classes of data categories: terms, term-related data categories, dxample data categories, and administrative data categories. ISO adds a fifth class for links, which are nevertheless database structure design example resign We will describe how these classes of data categories can be structured in entries and database structure design example to link with global and shared information needed in a termbase.
Clearly, the following framework is not the only possible application ofbut we feel it is a flexible and powerful one. Within the CLS Framework, a termbase consists of a global information about the termbase, b a set of concept entries called ConceptEntrys in this documentand c a set of references here called SharedRefs that can be shared among multiple ConceptEntrys or parts of ConceptEntrys, as shown in the graphical wtructure. Global information can include publication information, such as the name of the database, the name of the copyright holder, information about the creators of the database, dates, and version structuure.
In addition, it can include information about the languages and writing systems used in the termbase, which user group the termbase is intended for, and other administrative information. In some cases, some or all of the global information may be external to the termbase itself, but this is not ideal, especially in interchange environments. Each ConceptEntry consists of information about one concept in a specified subject field also structurre a domain and one or more terms that database structure design example each assigned as a language-specific designation of that concept.
In ratabase with the principle of term autonomy articulated by Schmitz Schmitzeach term is accompanied by various pieces of term-related, descriptive, and administrative information. Usually, the bulk of the information in a termbase will reside in the set of ConceptEntrys, which in this context can be called the body of the termbase. It is understood that, ideally, each term in a given ConceptEntry designates the same concept, at least within a particular subject field.
Nevertheless, the terms in various languages may still not be does the red dot on tinder mean active equivalents of each other, since the relevant concepts in various languages may not be identical. Transfer comments may be needed to detail degrees of non-equivalence between certain pairs of terms in some direction. If the lack of equivalence exceeds some threshold determined by the judgment of the terminologist, it may be more appropriate to define two distinct concepts and to split the ConceptEntry into two entries, one for each concept.
The ideal concept entry has the following properties: the entry is based on a single well-defined concept, and all the terms in the entry are equivalent to each other. In collections of standardized terminology, strucutre goal may be to document one term in each language for each concept, but if synonyms exist, they should also be documented and identified to reflect what is speed class 11 acceptability or status.
Daatbase addition to the types of information listed above, ConceptEntrys and individual what is the yellow circle on tinder items in ConceptEntrys can include links to other items in the ConceptEntry, to other ConceptEntrys, and to SharedRefs. SharedRefs consist of pieces of information that are potentially shared by many ConceptEntrys.
An example of a SharedRef would be a complete bibliographic entry or a responsibility entry listing the biodata about a person who created or updated entries in the termbase. Individual items scattered throughout the termbase can include links or pointers to the relevant SharedRefs as needed. SharedRefs can also include graphics, external video or audio resources, charts, tables, and the like.
The use of Shared-Refs is grounded in the well-known principle of database management that redundant desigh should be avoided. There are several reasons for this rule: Economy of storage: A detailed bibliographic reference or other SharedRef can be stored once in the termbase and several ConceptEntrys can point to it.
Consistency: If many complete and separate copies of a reference are stored in various places in a database and subsequently an error is found or data needs to be updated, care must cesign taken to find every occurrence of the reference in order to make the change in all locations. Otherwise the database becomes inconsistent and therefore will be much less useful.
Flexibility: A SharedRef for a, such as a bibliographic reference, may be referenced in different ways with respect to different ConceptEntrys or individual items in ConceptEntrys. Each reference in a ConceptEntry need only what is the meaning of tyndall effect a pointer to the SharedRef and the specific information about the references that is distinctive to that reference, for example, sgructure page number in a book.
The links used adtabase connect data items with SharedRefs can take two forms: Simple pointers that link data elements or groups of exampe elements to a SharedRef. Even simple pointers can be associated with attributes indicating the type of pointer involved e. More complex links that contain additional information in the form of variant text, such as a page number indicator or information on which part of a reference is relevant to the item in question.
SharedRefs may be implemented differently in various data models. In a relational data model, the SharedRefs may be in a separate table or tables. In addition to their association with SharedRefs, links can also be used between ConceptEntrys, such as to indicate that one ConceptEntry has a generic-specific relation to another. For a link to be unambiguous, the targeted item must include an identifier that is unique throughout the database. These three components, i.
Other aspects of data categories implicit in are language and data type. Pieces of textual information in the database require language codes to specify the language and writing system, including the associated computer representation. Some items in the database may have a date as a value. A date is a data type distinct from normal text. Other items may have text as a value. Still others may be restricted to one or more options taken from a list of permissible instances.
The data category specification for each data category must indicate the data type database structure design example with that item. That data type can then be used to write automatic validation dfsign for the database. Within a ConceptEntry the various terms are grouped by language. Each piece of textual information has a language code associated with it. A descripNote can be attached to any descriptive element descripan adminNote can be attached to any administrative element admin and a general note can be attached to any item except another general note.
A link can be attached to any item and exam;le target another ConceptEntry or a SharedRef in the back matter. The back matter consists of a number of expanded SharedRefs or external references to foreign data residing in the system or even on a network, such as the World Wide Web or a proprietary intranet. Traditionally, termbases have exhibited fundamentally different entry structures from database structure design example used in lexical databases, i. Whereas termbase entries are concept oriented, these databases are headword-oriented and list all the meanings associated with a headword.
If a database were extended to include lexicographical information linked to terminological ConceptEntrys, then it might be called a lex-termbase. It should now be somewhat clearer why we have called it CLS framework: because it consists primarily of C oncept-oriented entriesand these entries can be L inked to each other or to S hared references as needed. The following explanations are designed examp,e illustrate how the ISO database structure design example categories fit into the above approach to encoding terminological data.
When we state that an item is "attached" to another item, we leave open how that attachment is implemented. In an SGML representation, attachment may be shown by containment, i. In a relational database, it may be shown by using pointers between tables. Some less stringent data models attempt to achieve association between elements through the principle of adjacency, but we do not recommend or try to support this methodology because it is subject to ambiguity and does not ensure robust behavior, as pointed out by TC 37 French delegate Andre LeMeur.
Section 1 consists of the data category term. Each term is ztructure to a LanguageSection, which is attached to the ConceptEntry. This attachment indicates that the term designates, in a particular language, the concept associated with the ConceptEntry. As noted above, each term is autonomous, but it can be modified and categorized using the items listed in Section 2, term-related information. Section 2 consists of various pieces of term-related information such as term type, part of speech, geographical usage, register, etymology, syllabification, and administrative status.
These data categories are simply attached to a term, indicating that they are properties of the term. Section 3 consists of pieces of information about degrees of equivalence. These data categories are attached to a term and refer to another term in the same entry or a closely-related concept entry. Section structurd consists of data categories that tell how a concept relates to a subject field, also called a domain. There are two methods provided by Section 4.
One method is to simply attach the name of a subject field to a ConceptEntry. The other method is to place a classification system listing the subject fields in the back matter and to attach a link from the ConceptEntry to its respective node in the classification system. Section 5 consists of descriptions of the concept, such as definitions and contextual examples. Often, a definition will be attached directly to the ConceptEntry and apply to all its terms. Sometimes, definitions will be available in multiple languages and will be attached to language sections or individual terms.
Contextual examples will, of course, be attached to the term they exemplify. A graphic image or non-textual item may be used to describe a concept. In such cases, the non-textual item, or at least an external reference to it, will be placed in the back matter and a link to the back matter item will be attached to the ConceptEntry. Section 6 This section consists of relations between conceptEntry s. These data categories have been disallowed for blind interchange because they can be subsumed into Section 7.
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