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Data Models for Storage and Retrieval
Published in Praveen Kumar, Jay Alameda, Peter Bajcsy, Mike Folk, Momcilo Markus, Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling, 2005
One way to help deal with the heterogeneity, size, and complexity of hydrologic data is to step back and identify common data models. A data model provides a common way to conceptualize the content and use of data. We look at some examples of data that at first seem quite different, but in fact share a great deal in common, and can be described with the same data model. Data models are abstractions that can be implemented in different ways, so it is useful to define common APIs and programming models, which provide a way for software be written to query and access the data. Having common data models, APIs, and programming models can simplify our ability to share data, to combine data from different sources, and to build and share software for working with data.
Static Testing the Logical Design
Published in William E. Lewis, David Dobbs, Gunasekaran Veerapillai, Software Testing and Continuous Quality Improvement, 2017
William E. Lewis, David Dobbs, Gunasekaran Veerapillai
A data model is a representation of the information needed or data object types required by the application. It establishes the associations between people, places, and entities of importance to the application and is used later in physical database design, which is part of the physical design phase. A data model is a graphical technique used to define the entities and the relationships. An entity is something about which we want to store data. It is a uniquely identifiable person, place, object, or event of interest to the user, about which the application is to maintain and report data. Examples of entities are customers, orders, offices, and purchase orders.
Data collection, processing, and database management
Published in Zongzhi Li, Transportation Asset Management, 2018
Beside defining the data models, reference systems, and data standards, a crucial component of database design is the creation of metadata and data dictionaries, which are essentially detailed descriptions of the data. “Metadata” is data about the data. Metadata describes the data's meaning in the real world (e.g., its formal names, definitions, integrity, and accuracy). Metadata also indicates the data's physical nature (e.g., the way it is stored), the data types, structure (e.g., relational, object-oriented), and other properties that may assist the database user to understand and manage the data.
Are NoSQL Databases Affected by Schema?
Published in IETE Journal of Research, 2023
Neha Bansal, Shelly Sachdeva, Lalit K. Awasthi
A data model is a collection of tools used to describe data and its relationships, constraints, and semantics. This section briefly introduces the modelling perspective of three categories of NoSQL databases. a) Document Store, b) Column Store, and c) Key-Value Store. Table 1 presents the terminology translation from the relational database to three different NoSQL data models named Document (MongoDB), Column (Cassandra), and Key-Value (Redis) corresponding to the relational model. Table 1 explains that MongoDB stores the data in a database as a set of collections consisting of entities as documents. Cassandra stores the data in a Key-space as one or more column families. Whereas Redis stores the data in basic key-value pairs where the key for each entity is unique.
Intelligent generation method of 3D machining process based on process knowledge
Published in International Journal of Computer Integrated Manufacturing, 2020
Xuwen Jing, Yuping Zhu, Jinfeng Liu, Honggen Zhou, Peng Zhao, Xiaojun Liu, Guizhong Tian, Hua Ye, Qun Li
In this paper, machining features are used as a bridge between machining parts and process knowledge to achieve the purpose of effective expression and reuse of process knowledge. E-R diagram (Entity Relationship Diagram) is widely used to represent entities, attributes and their relationships, so as to achieve high-level description of conceptual data models. Rennolls and Al-Shawabkeh (2008) used E-R diagrams to improve cohesion and efficacy of the data-mining discipline. Mukherjee and Chakraborty (2016) proposed an automated knowledge provider system (AKPS) where natural language query will be automatically converted to the conceptual form of database using E-R diagram. Machining process knowledge has the characteristics of wide coverage, complex logic relationship and multi-level structure. Therefore, in order to clearly show the hierarchical structure and logical relationship of machining process knowledge, referring to the basic attributes and characteristics of E-R diagram, a concept-attribute-rule (C-A-R) diagram of machining process knowledge is created. C-A-R diagram can express the concepts, attributes, rules and relationship of process knowledge. This paper chooses the machining process of the key parts of marine diesel engine as the object, and creates the C-A-R diagram as shown in Figure 3.
Knowledge integration via the fusion of the data models used in automotive production systems
Published in Enterprise Information Systems, 2019
Rafal Cupek, Adam Ziebinski, Marek Drewniak, Marcin Fojcik
A Digital Factory permits the design (CAD) tools, the product lifecycle management (PLM) tools, the simulation software, analytical applications and control technologies to be integrated (Lu, Morris, and Frechette 2016). Data is the essential basis for a digital factory. The data for heterogeneous automation systems (geometric information, wiring and electrical planning information, functional descriptions) is obtained in many different ways and formats. It becomes increasingly complex and exists in various machine readable formats. Additionally, the semantics of data – the meaning – is not described formally. In order to transform information from one format to another, it is necessary to know each format, which means the formal description and the semantics of the data in both formats. Even if the data is available in a digital form, it may occur in many different data models. A data model represents the abstract mapping of objects, their properties, attributes and relations as well as their possible interactions.