Integration of biosafety surveillance through Biosafety Surveillance Conceptual Data Model

The global movement of people and goods has increased the risk of biosecurity threats and their potential to induce large economic,social,and environmental harm.Integration of biosafety monitoring networks has become a top priority for addressing biosafety issues.In order to resolve the data standards and integration problems in the field of biosafety in China,the Biosafety Surveillance Conceptual Data Model(BSCDM),which is an object-oriented,hierarchically designed,flexible and scalable biosafety surveillance concept data model,is proposed in this article.This model is based on the integration of business process management and data resources of disease surveillance,animal disease surveillance and potential invasive biological monitoring.In reference to the Public Health Conceptual Data Model(PHCDM)and Federal Enterprise Architecture(FEA),BSCDM conducts a thorough analysis of biosafety monitoring activities,records basic information requirements of biosafety monitoring and provides data set standards for biosafety-related activities.It is developed with the Unified Modeling Language(UML)and could be applied as an open standard for accelerating data analysis and promoting collaboration.This study attempts to integrate biosafety monitoring data and the presented model has been tested in the detection of dengue fever in China and will be applied to other biosafety fields.

Multi-dimensional database design and implementation of dam safety monitoring system

To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design wasachieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

On Detecting and Enforcing the Non-Relational Constraints Associated to Dyadic Relations in MatBase

MatBase is a prototype data and knowledge base management expert intelligent system based on the Relational,Entity-Relationship,and(Elementary)Mathematical Data Models.Dyadic relationships are quite common in data modeling.Besides their relational-type constraints,they often exhibit mathematical properties that are not covered by the Relational Data Model.This paper presents and discusses the MatBase algorithm that assists database designers in discovering all non-relational constraints associated to them,as well as its algorithm for enforcing them,thus providing a significantly higher degree of data quality.