Data warehouse testing: A prototype-based methodology

Context

Testing is an essential part of the development life-cycle of any software product. While most phases of data warehouse design have received considerable attention in the literature, not much has been written about data warehouse testing.

Objective

In this paper we propose a comprehensive approach to testing data warehouse systems. Its main features are earliness with respect to the life-cycle, modularity, tight coupling with design, scalability, and measurability through proper metrics.

Method

We introduce a number of specific testing activities, we classify them in terms of what is tested and how it is tested, and we show how they can be framed within a prototype-based methodology. We apply our approach to a real case study for a large retail company.

Results

The case study we faced, based on an iterative prototype-based medium-size project, confirmed the validity of our approach. In particular, the main benefits were obtained in terms of project transparency, coordination of the development team, and organization of design activities.

Conclusion

Though some general-purpose testing techniques can be applied to data warehouse projects, the effectiveness of testing can be largely improved by applying specifically-devised techniques and metrics.     

基于JXTA的语义通信模型的研究

语义Web服务与语义P2P都没有将语义引入通信过程.提出一个基于JXTA平台的语义通信模型架构,结合语义Web服务与P2P的优势,将消息建模为本体.消息的管理控制部分由消息服务本体支持,消息所传输的内容由领域本体支持.通过推理模块,挖掘出消息中隐含的语义,以指导消息的路由.从而将语义引入通信过程,使通信知晓内容和环境,达到了通信的语义化.模型运行于开放的、分布式的环境中,使通信更灵活、更智能.     

A semantic approach to interpolation

Craig interpolation is investigated for various types of formulae. By shifting the focus from syntactic to semantic interpolation, we generate, prove and classify a series of interpolation results for first-order logic. A few of these results non-trivially generalize known interpolation results; all the others are new. We also discuss some applications of our results to the theory of institutions and of algebraic specifications, and a Craig–Robinson version of these results.     

Ontology-based semantic similarity: A new feature-based approach

Estimation of the semantic likeness between words is of great importance in many applications dealing with textual data such as natural language processing, knowledge acquisition and information retrieval. Semantic similarity measures exploit knowledge sources as the base to perform the estimations. In recent years, ontologies have grown in interest thanks to global initiatives such as the Semantic Web, offering an structured knowledge representation. Thanks to the possibilities that ontologies enable regarding semantic interpretation of terms many ontology-based similarity measures have been developed. According to the principle in which those measures base the similarity assessment and the way in which ontologies are exploited or complemented with other sources several families of measures can be identified. In this paper, we survey and classify most of the ontology-based approaches developed in order to evaluate their advantages and limitations and compare their expected performance both from theoretical and practical points of view. We also present a new ontology-based measure relying on the exploitation of taxonomical features. The evaluation and comparison of our approach’s results against those reported by related works under a common framework suggest that our measure provides a high accuracy without some of the limitations observed in other works.     

Estimating semantic content: An A priori approach

We present our research into the use of the logical structure of natural language discourse to generate estimates of the quantity of semantic content contained within a passage. These estimates of the degree of meaningfulness are recovered from the logical form of the passage, without actually recovering its meaning or necessitating real understanding. We first consider analysis of statements in the propositional calculus, then consider analysis of the logical structure within propositions, as formalized by the predicate calculus. Along the way, we consider several questions related to logic and meaning and introduce several interesting results. the theory and methodology we develop has potential application to a natural language preprocessor for a priori skimming and the production of abstracts, although for now the input should be specified in logical form, rather than in a natural language.     

一种分布式多媒体数据仓库模型

多媒体数据采掘是从大型多媒体数据库中提取高层的多媒体信息及知识。介绍一种分布式多媒体数据仓库模型──ＣＭＳ模型的体系结构及存储结构,并构造了具有综合处理各种媒体数据,能够对这些媒体数据进行修改、查询的军用多媒体数据仓库原型系统。     

基于侏儒立方体的保持语义的数据立方体结构*

在侏儒立方体研究的基础上,提出了一种新的能够保持语义的立方体结构。这种结构改变了侏儒立方体对聚集数据的存储方式,在保持基本立方体上卷、下钻语义的前提下,尽量地去除前缀冗余、后缀冗余,节约存储空间,保证立方体清晰的结构,并且拥有比侏儒立方体更高的存储效率和查询响应速度,对点查询和范围查询能够快速地返回结果,对大数据量情况下的稀疏立方体具有良好的支持。     

XChange: A semantic diff approach for XML documents

XML documents are extensively used in several applications and evolve over time. Identifying the semantics of these changes becomes a fundamental process to understand their evolution. Existing approaches related to understanding changes (diff) in XML documents focus only on syntactic changes. These approaches compare XML documents based on their structure, without considering the associated semantics. However, for large XML documents, which have undergone many changes from a version to the next, a large number of syntactic changes in the document may correspond to fewer semantic changes, which are then easier to analyze and understand. For instance, increasing the annual salary and the gross pay, and changing the job title of an employee (three syntactic changes) may mean that this employee was promoted (one semantic change). In this paper, we explore this idea and present the XChange approach. XChange considers the semantics of the changes to calculate the diff of different versions of XML documents. For such, our approach analyzes the granular syntactic changes in XML attributes and elements using inference rules to combine them into semantic changes. Thus, differently from existing approaches, XChange proposes the use of syntactic changes in versions of an XML document to infer the real reason for the change and support the process of semantic diff. Results of an experimental study indicate that XChange can provide higher effectiveness and efficiency when used to understand changes between versions of XML documents when compared with the (syntactic) state-of-the-art approaches.     

IRS-III: A broker-based approach to semantic Web services

A factor limiting the take up of Web services is that all tasks associated with the creation of an application, for example, finding, composing, and resolving mismatches between Web services have to be carried out by a software developer. Semantic Web services is a combination of semantic Web and Web service technologies that promise to alleviate these problems. In this paper we describe IRS-III, a framework for creating and executing semantic Web services, which takes a semantic broker-based approach to mediating between service requesters and service providers. We describe the overall approach and the components of IRS-III from an ontological and architectural viewpoint. We then illustrate our approach through an application in the eGovernment domain.     

A semantic approach to ETL technologies

Data warehouse architectures rely on extraction, transformation and loading (ETL) processes for the creation of an updated, consistent and materialized view of a set of data sources. In this paper, we support these processes by proposing a tool that: (1) allows the semi-automatic definition of inter-attribute semantic mappings, by identifying the parts of the data source schemas which are related to the data warehouse schema, thus supporting the extraction process; and (2) groups the attribute values semantically related thus defining a transformation function for populating with homogeneous values the data warehouse.Our proposal couples and extends the functionalities of two previously developed systems: the MOMIS integration system and the RELEVANT data analysis system. The system has been experimented within a real scenario concerning the creation of a data warehouse for enterprises working in the beverage and food logistic area. The results showed that the coupled system supports effectively the extraction and transformation processes.     

数据仓库中数据粒度的划分

为了提高银行数据仓库的性能,合理地确定数据仓库中数据单元的详细程度和级别,给出了一种银行数据仓库中数据粒度划分的方法.分析了数据仓库中的粒度模型,介绍了数据粒度划分的策略,在此基础上提出了一种估计数据仓库大小的方法,进而在明确数据粒度划分原则的基础上,提出了一种银行环境中数据粒度的划分.该划分方法有效的解决了银行数据仓库开发者面临的一个最重要的设计问题,使其设计和实现中的其余方面得以非常顺畅地进行.     

数据仓库技术及其应用

数据仓库技术是决策支持系统(DSS)处理中的核心技术。本文说明了在当今信息极为丰富的时代里数据仓库技术的产生背景，讨论了几种常见数据库管理系统对于数据仓库技术的支持，以及数据库管理系统和数据仓库专用管理系统之间的关系。为了从数据仓库内大量的数据中抽取出潜在的、不为人知的有用信息、模式和趋势，产生了数据挖掘技术。本文还讨论了数据仓库技术在化学中可能的应用。     

Knowledge management in biomedical libraries: A semantic web approach

In recent years, technological advances in high-throughput techniques and efficient data gathering methods, coupled with a world-wide effort in computational biology, have resulted in an enormous amount of life science data available in repositories devoted to biomedical literature. These repositories lack the ability to attain an effective and accurate search. Using semantic technologies as the key for interoperation enables searching and processing of biomedical literature in a more efficient way. However, emerging semantic applications take for granted specific knowledge that biomedical researchers may not have. This paper presents design principles for easy-to-use biomedical semantic applications by means of ontology-based annotations and faceted search. The proposed approach is backed with a usable prototype that shows the breakthroughs of adding these principles to a biomedical digital library where identifying and searching information are critical aspects for non-semantic Web experts.     

IoT-enabled Web warehouse architecture: a secure approach

Web warehouse (WWh) has overcome the geographical dependencies of data warehouse. With the rapid development of WWh, decision makers (humans) and intelligent devices are able to remotely retrieve the information for supporting the effective decision-making process. This paper presents a secure Web service-oriented architecture of the WWh. The proposed architecture provides the better scalability, availability of WWh, and secure analytical service for human and Internet of Things for effective decision making. In addition, the service-oriented architecture of WWh integrates intelligent devices for the process of decision making. The proposed architecture uses XML-based Web services to provide authentication, authorization, and data confidentiality and integrity. Experiments show that the proposed architecture is more reliable, scalable, and secure.     

From fine-grained to abstract process models: A semantic approach

Organizations actively managing their business processes face a rapid growth of the number of process models that they maintain. Business process model abstraction has proven to be an effective means to generate readable, high-level views on business process models by showing coarse-grained activities and leaving out irrelevant details. In this way, abstraction facilitates a more efficient management of process models, as a single model can provide for many relevant views. Yet, it is an open question how to perform abstraction in the same skillful way as experienced modelers combine activities into more abstract tasks. This paper presents an approach that uses semantic information of a process model to decide on which activities belong together, which extends beyond existing approaches that merely exploit model structural characteristics. The contribution of this paper is twofold: we propose a novel activity aggregation method and suggest how to discover the activity aggregation habits of human modelers. In an experimental validation, we use an industrial process model repository to compare the developed activity aggregation method with actual modeling decisions, and observe a strong correlation between the two. The presented work is expected to contribute to the development of modeling support for the effective process model abstraction.     

ESM:一种增强语义匹配的语句评分模型

语义匹配问题是自然语言处理的核心问题之一。基于语义的匹配,即通过提取文本内在语义进行匹配度计算,是目前自然语言处理领域研究的热点。传统的语义匹配模型并没有结合语句通顺度等多种要素综合评价,因此效果较差。提出一种增强语义匹配模型,模型在文本相似度计算的基础上,增加通顺度因子,并通过大量数据来调整最优参数。通过自动阅卷系统进行测试,对比3种常用的自动阅卷评分模型验证该模型能有效降低平均误差值。