Multidimensional Space Structure for Adaptable Data Model
Oleksandr Terentyev1, Svitlana Tsiutsiura2, Tetyana Honcharenko3, Tamara Lyashchenko4
1Oleksandr Terentyev, Department of Information Technology Designing and Applied Mathematics, Kyiv National University of Construction and Architecture, Kyiv, Ukraine.
2Svitlana Tsiutsiura, Department of Information Technology, Kyiv National University of Building and Architecture, Kyiv, Ukraine.
3Tetyana Honcharenko, Department of Information Technology, Kyiv National University of Construction and Architecture, Kyiv, Ukraine.
4Tamara Lyashchenko, Department of Information Technology, Kyiv National University of Construction and Architecture, Kyiv, Ukraine.
Manuscript received on 13 August 2019. | Revised Manuscript received on 19 August 2019. | Manuscript published on 30 September 2019. | PP: 7753-7758 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6318098319/2019©BEIESP | DOI: 10.35940/ijrte.C6318.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The article presents an adaptable data model based on multidimensional space. The main difference between a multidimensional data representation and a table representation used in relational Database Management Systems (DBMSs) is that it is possible to add new elements to sets defining the axes of multidimensional space at any time. This changes the data model. The tabular representation of the relational model does not allow you to change the model itself during the operation of an automated system. Three levels of multidimensional data presentation space are considered. There are axis of multidimensional space, the Cartesian product of the sets of axis values and the values of space points. The five axes of multidimensional space defined in the article (entities, attributes, identifiers, time, modifiers) are basic for the design of an adaptable automated system. It is shown that it is possible to use additional axes for greater granularity of the stored data. The multidimensional space structure defined in the article for an adaptable data model is a flexible set for storing a relational domain model. Two types of operations in multidimensional information space are defined. Relations of the relational model are formed dynamically depending on the conditions imposed on the coordinates of the points. Thus, an adaptable data representation model based on multidimensional space can be used to create flexible dynamic automated information systems.
Keywords: Multidimensional Space, Adaptable Data Model, Entity, Attribute, Relation, Identifier, Database Management System, DBMS.
Scope of the Article: Concrete Structures