Conceptual Meta Model for Building Information Modeling
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F20%3A00348625" target="_blank" >RIV/68407700:21110/20:00348625 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1088/1742-6596/1680/1/012037" target="_blank" >https://doi.org/10.1088/1742-6596/1680/1/012037</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1088/1742-6596/1680/1/012037" target="_blank" >10.1088/1742-6596/1680/1/012037</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Conceptual Meta Model for Building Information Modeling
Popis výsledku v původním jazyce
The first meta-concept reflects a specification for data as a whole. We call this a Data Model. Good examples are ontologies or dictionaries. In addition, we have Data Sets that contain individual data according to the Data Model. The next basic meta-concept inside such a data model is a Concept referring to abstract notions as types of things of interest. Next we have Attributes being able to describe intrinsic characteristics and Relations to describe extrinsic characteristics of concepts. Concepts can be instantiated with Individuals referring to real world things you can or could point at. Such instances get lexical or reference Values for attributes respectively relations. Lexical values can be classified according to some Value Type (like string, decimal, integer, boolean etc.). Concepts can have Constraints restricting the amount of values or the values themselves or both. Also attributes and relations can have restrictions with respect to their source or target concepts (in case of relations) or value type (in case of attributes). Finally we have Derivations for concepts that tell us how new values for attributes or relations can be inferred from existing asserted values. We define three mechanisms as specific relations: 1. Classification (inverse: instantiation), from 'concrete' to 'abstract' 2. Generalization (inverse: specialization), from 'specific' to 'generic' 3. Composition (inverse: decomposition), from 'detailed' to 'global' These three mechanisms generate three hierarchy types namely a typology (of concepts), a taxonomy (of concepts, attributes or relations) and a meronomy (of concepts) respectively. Concepts are themselves instances of 'Concept' and can be instantiated in instances; Value Types are themselves instances of 'Value Type' and can be instantiated in values. Concepts can be specialized in other Concepts; attributes can be specialized in other attributes, and relations can be specialized in other relations.
Název v anglickém jazyce
Conceptual Meta Model for Building Information Modeling
Popis výsledku anglicky
The first meta-concept reflects a specification for data as a whole. We call this a Data Model. Good examples are ontologies or dictionaries. In addition, we have Data Sets that contain individual data according to the Data Model. The next basic meta-concept inside such a data model is a Concept referring to abstract notions as types of things of interest. Next we have Attributes being able to describe intrinsic characteristics and Relations to describe extrinsic characteristics of concepts. Concepts can be instantiated with Individuals referring to real world things you can or could point at. Such instances get lexical or reference Values for attributes respectively relations. Lexical values can be classified according to some Value Type (like string, decimal, integer, boolean etc.). Concepts can have Constraints restricting the amount of values or the values themselves or both. Also attributes and relations can have restrictions with respect to their source or target concepts (in case of relations) or value type (in case of attributes). Finally we have Derivations for concepts that tell us how new values for attributes or relations can be inferred from existing asserted values. We define three mechanisms as specific relations: 1. Classification (inverse: instantiation), from 'concrete' to 'abstract' 2. Generalization (inverse: specialization), from 'specific' to 'generic' 3. Composition (inverse: decomposition), from 'detailed' to 'global' These three mechanisms generate three hierarchy types namely a typology (of concepts), a taxonomy (of concepts, attributes or relations) and a meronomy (of concepts) respectively. Concepts are themselves instances of 'Concept' and can be instantiated in instances; Value Types are themselves instances of 'Value Type' and can be instantiated in values. Concepts can be specialized in other Concepts; attributes can be specialized in other attributes, and relations can be specialized in other relations.
Klasifikace
Druh
J<sub>ost</sub> - Ostatní články v recenzovaných periodicích
CEP obor
—
OECD FORD obor
20101 - Civil engineering
Návaznosti výsledku
Projekt
—
Návaznosti
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Journal of Physics: Conference Series (JPCS)
ISSN
1742-6588
e-ISSN
1742-6588
Svazek periodika
1680
Číslo periodika v rámci svazku
1680
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
10
Strana od-do
1-10
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85098597597