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Building product models, terminologies, and object type libraries
Published in Pieter Pauwels, Kris McGlinn, Buildings and Semantics, 2023
Aaron Costin, Jeffrey W. Ouellette, Jakob Beetz
A data dictionary is a centralised repository of information about data such as meaning, relationships to other data, origin, usage, and format [248]. A data dictionary is used to catalog and communicate the structure and content of data by providing meaningful descriptions for individually named data objects. Essentially, a data dictionary gives context to the data being stored. Data dictionaries can be created using a number of tables to define any information about a data point. Figure 1.3 displays a data dictionary with four tables of metadata, in this case describing the domain, element properties, element classifications, and the associated IFC classification properties.
Data collection, processing, and database management
Published in Zongzhi Li, Transportation Asset Management, 2018
The data dictionary is a subset of the metadata containing an organized catalog of the data files pertaining to the definition, type, structure, and other information of the data. The use of a data dictionary is crucial in the data integration process by ensuring data definition and usage consistency in the databases and by clearly differentiating various data items.
Introduction to the SAS- and R-Based Table-Driven Environment
Published in Tanya Kolosova, Samuel Berestizhevsky, Supervised Machine Learning, 2020
Tanya Kolosova, Samuel Berestizhevsky
The data dictionary is the repository of a variety of information regarding objects related to an application, such as application tables and their columns, users, access privileges, and integrity constraints. In order to define an application, we need to build the set of data dictionary tables that will contain data (metadata) about the application’s objects.
Data Governance Model To Enhance Data Quality In Financial Institutions
Published in Information Systems Management, 2023
The business data dictionary manages both business and technical metadata. The Data Governance Model introduces business metadata as a business definition of business terms/KPIs, a list of applications that serves as a data source for KPIs, a list of reports where KPI is used, and roles management. Each KPI has assigned its respective business-term owner and data stewards. KPI definition contains its calculation formula. The calculation formula is mapped to the data source or various data sources based on which the KPI is calculated. These data are considered as critical data elements. Each data has been assigned to its respective data owner and delegated data stewards. The data source is defined in an application catalog, which can be part of the business data dictionary. For each application, the create, read, update, and delete (CRUD) matrix is defined to have awareness of the basic operations to be done in the data repository for the respective data dimension. Each application has an assigned business system owner.
Basic data management and analysis system for new power energy based on MVC
Published in International Journal of Ambient Energy, 2022
The System Management function includes six sub-modules, i.e. User management, Data dictionary, Data import, Personalised parameter setting, System operation log and Power field data management. The Data Maintenance function includes four sub-modules, which are the Basic data for WPP (Wind Power Plant), Timing data for WPP, Basic data for PPS (Photovoltaic Power Station) and Timing data for PPS. Basic data is divided into two sub-modules, i.e. Basic information and Detail information; Timing data is divided into Actual power data and Predictive power data. Data statistics function includes three sub-modules, i.e. Basic information statistics, Mutual comparison of WPP output and Power prediction error statistics. Since an ordinary statistical chart can not display mass data in the system in a full shot, jQuery Highstock plugin is used to show this run chart. A large number of pie charts, histograms and other graphs are displayed with the jQuery Highcharts plug-in. Highstock and Highcharts are developed based on the front-end svg drawing technology, so more ideal for the statistical charts with bulk data volume. It then interacts with the user via the javascript script (Tables 1 and 2).
A creation method of comprehensive cases and specifications for hardware and software combined test to detect undesirable events of an industrial product using HAZOP
Published in SICE Journal of Control, Measurement, and System Integration, 2022
Masakazu Takahashi, Kouji Ueno, Yunarso Anang, Yoshimichi Watanabe
Figure 2 describes an example of the parameter extraction method when the specifications are written in the structured method. Data is the data flow between a source or sink and a process in a Data Context Diagram (DCD). Output destination and input source of the data are determined by the direction of the data flow in DCD. And the data type is obtained from the data dictionary. The control signal is the control flow in the Control Context Diagram (CCD). The output destination and input source of the control signal are determined by the direction of the control flow in the CCD. Since the control signal type is only on/off, it is a digital type. In addition to these documents, the control signals input or output to the industrial products described in the electrical interface control document are also parameters.