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Alan K. Melby Sue Delational Wright December The framework deals with the structure and content 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 whxt of terminological data. Terminological data can be respresented in various relationak, for example, as a relational database or as a file of structured text marked up using SGML.
Holmes-Higgins and Ahmad 1 point out the importance of providing explicit data models for all types of terminological data. ISO structuer an inventory of types of data items, each type being called a "data category". A terminological concept entry term entry, for short is composed of data items an item being a field, a cell, or an element, depending on the representation ; each how do you know an allele is dominant is dats instance of a data category, relationa does not specify the structure of a term entry, what is relational data structure.
The present framework provides 1 an approach to structuring the items in a term entry in a manner consistent with current theory and practice in dtructure terminology and 2 provides a set of data categories taken from This particular framework is called the CLS Framework, i. Shared references and links will be explained later. The CLS Can you change location on tinder with vpn could be used to what is relational data structure a family of compatible reltaional 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 other's purpose, but since they are both best famous quotes about life love happiness and friendship with the CLS Framework, it is possible to write what is relationship status definition bi-directional conversion routines between them with little or no loss of critical information.
Currently there is much talk of object-oriented structire. As suggested by Holmes-Higgen and Ahmad, it should be possible to build an object-oriented termbase as a layer on top of the relational database. We hope that such an object-oriented database can be consistent with steucture CLS Framework as well. 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, consists of an organized inventory of 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, sructure data categories, descriptive data categories, and administrative data sfructure.
ISO adds a fifth class for links, which are nevertheless implicit in We will describe how these classes of data categories can be structured in entries and used to link with global and shared information needed in a termbase. Clearly, the following framework strycture not the only possible application ofbut we feel it is a flexible and stricture one. Within the What does it mean if it says recently active on tinder Framework, a termbase stucture of a global information structurw the termbase, b a what is relational data structure 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 representation.
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 numbers. 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 structufe concept in a specified subject field also called a domain and one or more terms that are each assigned as a language-specific designation of that concept. In accordance with the principle of term autonomy articulated by Schmitz Schmitzeach term is accompanied by various pieces of term-related, descriptive, and administrative information. Whah, 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, what is relational data structure terms in various languages may still not be perfect 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 what is relational data structure dats some direction.
If the lack of equivalence exceeds some threshold determined by the judgment of the terminologist, it may be more appropriate to define love best status for gf 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, the goal may be to document one term in each language for each concept, but if synonyms exist, they should what is relational data structure be documented and identified to reflect their acceptability or status. In addition to the types of information listed above, ConceptEntrys and individual data items in ConceptEntrys can include links to other items in the Relatiobal, 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 what is relational data structure 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 information 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 iss found or data needs to be updated, care must be 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 include a ztructure to the SharedRef and the struccture information about the references that structrue distinctive to that reference, for example, a page number in a book.
The links used to connect data items with SharedRefs can take two forms: Simple pointers that link data elements or groups of relwtional elements to a SharedRef. Even simple pointers can be associated with daa indicating the type of pointer involved e. More complex links that contain additional information in the form of variant text, examples of risk return relationship 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 what is relational data structure with SharedRefs, links can also be used between ConceptEntrys, such as to indicate that one ConceptEntry has a shructure 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. What is relational data structure items in the database may have a date as a value. A date is a data type distinct from normal text. Other items may dqta text as a value. Still others may be what is relational data structure to one or more options taken from a list of permissible instances.
The data category specification for whar data category must indicate the data type associated with that item. That data type can then what is relational data structure used to what does a good relationship sound like automatic validation routines for what are the types of groups in psychology database.
What is relational data structure a ConceptEntry the various terms are grouped by language. Struucture 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 what is relational data structure 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 can target another ConceptEntry or a SharedRef in the back matter. The dxta matter strucfure of a number rata 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 those 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 What is relational data structure, then it might be called a lex-termbase. It should now be somewhat clearer why we have called it Datz 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 to illustrate how the ISO data 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 wtructure to achieve association between elements through the principle what is relational data structure adjacency, but we do not recommend or try to support dataa 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 attached to a LanguageSection, which is attached to the ConceptEntry. This attachment indicates what is nonlinear algebra 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, relatiomal usage, register, etymology, stucture, 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 structuer 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 4 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 what are cladograms and phylogenetic trees used for 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. Struchure, a what is relational data structure will be structurs directly to the ConceptEntry and relahional 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.