Data Model and Relational Database Design for Highway Runoff Water-Quality Metadata

2001 ◽  
Author(s):  
Gregory E. Granato ◽  
Steven Tessler
Keyword(s):  
Water Quality ◽  
Relational Database ◽  
Data Model ◽  
Database Design ◽  
Runoff Water ◽  
Highway Runoff

scholarly journals Using the REA Data Model in Order to Reduce Design Complexity in an Inventory Management Relational Database, and the Need for a Relational Database Complexity Metric.

2021 ◽  
Vol 9 (7) ◽  
pp. 71-78
Author(s):  
Ian Adamson
Keyword(s):  
Inventory Management ◽  
Relational Database ◽  
Data Model ◽  
Relational Databases ◽  
Database Design ◽  
Business Environment ◽  
Design Complexity ◽  
Data Inconsistency ◽  
A Company

With the extensive use of relational databases in the business environment there is a need to reduce database complexity in order to avoid data inconsistency and redundancy, which can provide a company with unreliable and/or meaningless data and information. The use of the REA Data Model in database design can significantly help with this problem.  The model can eliminate the need for unnecessary data artifacts which should only be generated by the system when needed. This paper also addresses the need for a Relational Database Complexity Metric. A simple and easy to understand metric is presented.

scholarly journals A Data Model Validation Approach for Relational Database Design Courses

10.28945/2797 ◽  
2004 ◽  
Author(s):  
Kevin R. Parker
Keyword(s):  
Model Validation ◽  
Relational Database ◽  
Data Model ◽  
Database Design ◽  
Instructional Method ◽  
Design Data ◽  
Critical Step

This paper presents an instructional method for validating a relational database design. Data model validation is often overlooked in course projects involving relational database design, in part because while most database texts stress the importance of validation, few provide an instructional method for performing validation. Validation is a critical step, especially for students. A flawed data model may omit non-key attributes or even the foreign keys required to join tables. This can make the design of SQL queries, forms, and reports a frustrating experience. This approach requires the designer to determine which attributes account for the field values on forms and reports, which entities are associated with those attributes, and how those entities are linked to an integral or primary entity. Such an approach serves to validate the completeness of the data model.

Formalized Approach in Relational Database Design

2016 ◽  
Vol 685 ◽  
pp. 930-933 ◽  
Author(s):  
Victoria V. Osipova ◽  
Igor L. Chudinov ◽  
Aysel S. Seidova
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Database Design ◽  
Domain Model ◽  
Relational Data ◽  
Conceptual Information ◽  
Suggested Approach ◽  
Database Development ◽  
Relational Data Model ◽  
Information Domain

Design of the conceptual information domain model is a significant and complicated stage in database development that influences its quality and can be considered as a skill. The suggested approach is based on analysis of attribute domains and relationships between them and uses the relational data model to determine the availability and the type of relationships between model entities.

Pollution retention capabilities of roadside soils

1999 ◽  
Vol 39 (2) ◽  
pp. 201-208 ◽  
Author(s):  
C. Dierkes ◽  
W. F. Geiger
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Drinking Water ◽  
Groundwater Recharge ◽  
Drinking Water Quality ◽  
Traffic Density ◽  
Roadside Soils ◽  
Highway Runoff ◽  
Lead And Cadmium ◽  
Lead Zinc

Runoff from highways contains significant loads of heavy metals and hydrocarbons. According to German regulations, it should be infiltrated over embankments to support groundwater-recharge. To investigate the decontaminating effect of greened embankments, soil-monoliths from highways with high traffic densities were taken. Soils were analyzed to characterize the contamination in relation to distance and depth for lead, zinc, copper, cadmium, PAH and MOTH. Lysimeters were charged in the field and laboratory with highway runoff to study the effluents under defined conditions. Concentrations of pollutants in roadside soils depend on the age of embankments and traffic density. Highest concentrations were found in the upper 5 cm of the soil and within a distance of up to two metres from the street. Concentrations of most pollutants decreased rapidly with depth and distance. Lead and cadmium could not be detected in lysimeter effluent. Zinc and copper were found in concentrations that did not exceed drinking water quality limits.

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