一种面向领域的虚拟视图语义集成方法*

针对油井工程领域异构数据源,提出了一种基于语义的虚拟视图集成方法。通过本体抽取和本体合并分别构造数据源局部本体和全局本体实现基于语义的数据访问视图,并利用全局本体、局部本体和数据源模式之间的映射关系,将基于语义的查询转换为底层数据源的访问请求,提供统一、透明的数据访问视图,以避免数据加载和更新等问题。通过油井决策支持数据集成平台,该方法取得了很好的应用效果。     

基于Web Services的商业智能系统研究与设计

针对传统商业智能存在移植性、集成性和可扩展性差等弱点,研究基于Web Services的商业智能平台.在分析商业智能当前应用状况和商业智能体系结构的基础上,给出了整个系统比较完善的解决方案,构建了基于Web服务的新型的数据ETL和前端展现方式,引入语义层作为数据仓库到商业智能服务器的连接中间层,增强了可理解性和可扩展性.     

基于轻映射的数据集成系统

数据集成系统提供了一个针对多数据源的统一查询接口。GAV和LAV两种集成映射方法均难以适应数据源和全局视图变化频繁的情况。对此,文章提出一种基于轻映射的数据集成方法来解决这一问题。首先定义了最小视图作为映射的基础,利用函数依赖关系把关系模型分解为最小视图集合,从而把关系映射转换为基本属性的映射。基于该方法,构造了查询重构算法,把基于全局模式的查询转换到基于数据源模式的查询,并通过一些实例加以说明。     

一种基于本体的数据仓库开发模型

数据仓库开发过程中面临需求获取和异构数据处理两大难题，这两大难题的背后实际是人和人之间理解一致性以及机器和机器之间理解一致性的问题，以及一致性基础上的重用问题。本体是关于事物本质的模型，它为达到这两种一致性提供了坚实的基础，也为重用提供了坚实的基础。该文根据科学问题正确求解的两个核心问题——正确定义问题域和正确的求解手段，把本体分为领域本体和任务本体，在此基础上提出一种基于本体的数据仓库开发模型。这个模型具有过程视图和交流视图两个视图。     

基于原语-模式的体系结构作战活动模型建模方法

为了理解、比较和集成由不同框架、不同工具及建模方法开发的体系结构,更好地支持以数据为中心的体系结构开发策略,提出了基于原语-模式的军事信息系统体系结构建模方法;依据XML的模型转换实现,重点研究了基于建模原语-模式的体系结构元模型与建模方法之间的语义映射规则;基于国际国防企业体系结构规范构建了作战活动模型(OV-5)的元模型,分别研究了OV-5的IDEF0建模和UML活动图建模的具体实现,构建了IDEF0及UML活动图与OV-5元模型数据元素严格的语义映射规则,规范了体系结构建模方法并保证了体系结构语义的精确性和一致性。     

数据仓库技术在物流信息系统中的应用

传统的操作型数据库存在数据分散、数据规范不统一、数据可分析能力较差等缺点,所以论文引入数据仓库技术,在分析其系统体系结构的基础上,提出基于数据仓库的物流信息系统。该系统利用数据挖掘技术和专家系统的推理模式,设计提出了物流决策支持系统的体系结构,将为物流管理的信息化提供强大的决策支持。     

数据仓库技术在智能电力信息系统中的应用

传统的操作型数据库存在数据分散、数据规范不统一、数据可分析能力较差等缺点,所以论文引入数据仓库技术,在分析其系统体系结构的基础上,提出基于数据仓库的智能电力信息系统。该系统利用数据挖掘技术和专家系统的推理模式,设计提出了电力生产决策支持系统的体系结构,将为电力生产管理的信息化提供强大的决策支持。     

结构图ETL概念模型的设计方法

ETL过程是数据仓库获得高质量数据的重要环节,是任何数据仓库工程不可缺少的成功因素。为了便于ETL过程的设计和维护,降低ETL过程的设计、维护代价,提出一种基于结构图的ETL概念模型设计方法,给出一个用于描述ETL过程的模型,并基于CWM完成用以存储元数据的ETL元模型的设计。通过图形化ETL过程中的元素和关联,该模型清晰直观地反映了各个源数据库与目标数据仓库的内部结构和组成、数据的来源与流向、源数据和目标数据之间的映射和转换关系,辅助设计人员更好地进行ETL过程的设计和编码实现,使整个ETL的设计与维护过程更加方便、灵活、有效。     

面向企业的混合型分布式数据仓库的数据集成方法

混合型分布式数据仓库是一种适合集团型企业特点的数据仓库解决方案,但它数据分层存储的结构使得总部决策支持系统访问子公司细节数据发生困难.文章分析了混合型分布式数据仓库的体系结构,结合JW-DSS项目提出了一种借助远程视图从总部决策支持系统直接访问局部数据仓库细节数据的方法,最后还提出了一种通过分层映射数据解决连接远程视图导致总部数据仓库访问效率降低的方法.     

IIE环境下数字民航的虚拟数据仓库研究

本文结合现代企业信息网的特点,通过研究数据仓库体系结构和数据仓库层次数据模型,将数据库中数据以XML的形式,通过虚拟网络视图完成局域数据的集成与共享.进而通过建立基于虚拟网络视图的虚拟数据仓库,提供了数字民航在IIE环境下分布异构数据源的集成平台,介绍了虚拟数据仓库的体系结构和特点,并提出了分布异构环境下数字民航的数据集成框架结构.     

Web数据仓库的异步迭代查询处理方法

数据仓库信息量的飞速膨胀对数据仓库提出了巨大挑战.如何提高Web环境下数据仓库的查询效率成为数据仓库研究领域重要的研究问题.对Web数据仓库的体系结构和查询方法进行了研究和探讨.在分析几种Web数据仓库实现方法的基础上,提出了一种Web数据仓库的层次体系结构,并在此基础上提出了Web数据仓库的异步迭代查询方法.该方法充分利用了流水线并行技术,在Web数据仓库的查询处理过程中不同层次的结点以流水线方式运行,并行完成查询的处理,提高了查询效率.理论分析表明,该方法可以有效地提高Web数据仓库的查询效率.     

一种数据仓库的多维数据模型

数据模型是数据仓库研究的核心问题之一.很多研究表明,传统数据模型(如实体联系模型和关系模型)不能有效地表示数据仓库的数据结构和语义,也难以有效地支持联机分析处理(on-line analysis processing,简称OLAP).最近,人们提出了几种多维数据模型.但是,这些多维数据模型在表示数据仓库的复杂数据结构和语义以及OLAP操作方面仍显不足.该文以偏序和映射为基础,提出了一种新的多维数据模型.该数据模型能够充分表达数据仓库的复杂数据结构和语义,并提供一个以OLAP操作为核心的操作代数,支持层次结构间的复杂聚集操作序列,能够有效地支持OLAP应用.该数据模型支持聚集函数约束的概念,提供了表示层次结构间聚集函数约束的机制.     

Recency-based storage assignment and warehouse configuration for recurrent demands

Storage assignment is an important decision problem in warehouse operation management. In conventional problem settings of distribution warehouses, stock items are stored in bulk but retrieved in small quantities. Storage assignment methods typically make use of demand attribute information of order quantity, order frequency and correlation between demands. In this paper, we address a different problem in which the request for the same stock items is stochastically recurrent. The problem arises when the items are needed in production and, after production, are returned to warehouses for later reuse. Examples of such items include tooling in factory, books in library and digital objects in data warehouses. Utilizing the recurrent characteristics, a salient recency-based storage assignment policy and an associated cascaded warehouse configuration are proposed and analyzed in this paper. This paper has four parts. In the first part, a model of recurrent demand is described. In the second part, the efficiency of the recency-based policy and a traditional ID-based policy is analyzed. In the third part, a mathematical programming model for optimal configuration of cascaded warehouses is presented. Finally, a case study of hospital visits is presented. This paper concludes with recommendations on cascading and zoning the warehouse for applying the recency-based policy.     

Using object deputy model to prepare data for data warehousing

Providing integrated access to multiple, distributed, heterogeneous databases and other information sources has become one of the leading issues in database research and the industry. One of the most effective approaches is to extract and integrate information of interest from each source in advance and store them in a centralized repository (known as a data warehouse). When a query is posed, it is evaluated directly at the warehouse without accessing the original information sources. One of the techniques that this approach uses to improve the efficiency of query processing is materialized view(s). Essentially, materialized views are used for data warehouses, and various methods for relational databases have been developed. In this paper, we first discuss an object deputy approach to realize materialized object views for data warehouses which can also incorporate object-oriented databases. A framework has been developed using Smalltalk to prepare data for data warehousing, in which an object deputy model and database connecting tools have been implemented. The object deputy model can provide an easy-to-use way to resolve inconsistency and conflicts while preparing data for data warehousing, as evidenced by our empirical study.     

混合架构下ORACLE数据快速查找方法研究

为了提高对混合架构下ORACLE数据的挖掘和查找速度,提出一种基于频繁项目集关联规则挖掘的数据快速查找方法;构建ORACLE数据的内部关联属性映射关系模型,在异质网络混合构架模式下,采用Graph OLAP数据仓库模型进行数据库检索的关系维度表,提取表达ORACLE数据属性信息的特征参量,通过同态标签检索方法,实现对目标数据的快速查找定位;仿真结果表明,采用该方法进行ORACLE数据查找的查准率和查全率较高,计算速度较快,性能优于传统方法。     

An intelligent XML-based multidimensional data cube exchange

Motivated by the globalization trend and Internet speed competition, enterprise nowadays often divides into many departments or organizations or even merges with other companies that located in different regions to bring up the competency and reaction ability. As a result, there are a number of data warehouse systems in a geographically-distributed enterprise. To meet the distributed decision-making requirements, the data in different data warehouses is addressed to enable data exchange and integration. Therefore, an open, vendor-independent, and efficient data exchange standard to transfer data between data warehouses over the Internet is an important issue. However, current solutions for cross-warehouse data exchange employ only approaches either based on records or transferring plain-text files, which are neither adequate nor efficient. In this research, issues on multidimensional data exchange are studied and an Intelligent XML-based multidimensional data exchange model is developed. In addition, a generic-construct-based approach is proposed to enable many-to-many systematic mapping between distributed data warehouses, introducing a consistent and unique standard exchange format. Based on the transformation model we develop between multidimensional data model and XML data model, and enhanced by the multidimensional metadata management mechanism proposed in this research, a general-purpose intelligent XML-based multidimensional data exchange process over web is facilitated efficiently and improved in quality. Moreover, we develop an intelligent XML-based prototype system to exchange multidimensional data, which shows that the proposed multidimensional data exchange model is feasible, and the multidimensional data exchange process is more systematic and efficient using metadata.     

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

The development of data warehouses begins with the definition of multidimensional models at the conceptual level in order to structure data, which will facilitate decision makers with an easier data analysis. Current proposals for conceptual multidimensional modelling focus on the design of static data warehouse structures, but few approaches model the queries which the data warehouse should support by means of OLAP (on-line analytical processing) tools. OLAP queries are, therefore, only defined once the rest of the data warehouse has been implemented, which prevents designers from verifying from the very beginning of the development whether the decision maker will be able to obtain the required information from the data warehouse. This article presents a solution to this drawback consisting of an extension to the object constraint language (OCL), which has been developed to include a set of predefined OLAP operators. These operators can be used to define platform-independent OLAP queries as a part of the specification of the data warehouse conceptual multidimensional model. Furthermore, OLAP tools require the implementation of queries to assure performance optimisations based on pre-aggregation. It is interesting to note that the OLAP queries defined by our approach can be automatically implemented in the rest of the data warehouse, in a coherent and integrated manner. This implementation is supported by a code-generation architecture aligned with model-driven technologies, in particular the MDA (model-driven architecture) proposal. Finally, our proposal has been validated by means of a set of sample data sets from a well-known case study.     

Data warehouse enhancement: A semantic cube model approach

Many data warehouse systems have been developed recently, yet data warehouse practice is not sufficiently sophisticated for practical usage. Most data warehouse systems have some limitations in terms of flexibility, efficiency, and scalability. In particular, the sizes of these data warehouses are forever growing and becoming overloaded with data, a scenario that leads to difficulties in data maintenance and data analysis. This research focuses on data-information integration between data cubes. This research might contribute to the resolution of two concerns: the problem of redundancy and the problem of data cubes’ independent information. This work presents a semantic cube model, which extends object-oriented technology to data warehouses and which enables users to design the generalization relationship between different cubes. In this regard, this work’s objectives are to improve the performance of query integrity and to reduce data duplication in data warehouse. To deal with the handling of increasing data volume in data warehouses, we discovered important inter-relationships that hold among data cubes, that facilitate information integration, and that prevent the loss of data semantics.     

基于数据驱动的螺旋式数据仓库开发方法的研究

文章首先分析了数据仓库与数据库技术本质的区别,讨论了软件系统开发的生命周期方法、快速原型法、螺旋法的特点,然后结合数据仓库开发特点,提出了基于数据驱动的螺旋式开发方法,并给出运用该方法开发数据仓库的步骤。     

跨境电商保税仓库拣货策略研究

针对跨境电商客户订单的多品类且数量不稳定的特点，对跨境电商保税仓库拣货流程进行分析与优化。采用订单动态时间窗分拣策略，并在仓库拣货路径优化的基础上，建立了跨境电商保税仓库拣货模型。最后应用于某公司跨境电商保税仓库管理系统中，取得了较好的预期效果。