Warehousing and OLAP Analysis of Bibliographic Data

In this paper, the system bgMath/OLAP for warehousing and online analytical processing bibliographic data is proposed. The implemented system can be useful for the users maintaining their electronic libraries with publications in order to monitoring, evaluating and comparing the scientific development of particular researchers, entire research groups, certain scientific fields and problems.

Data Warehousing and SAP BW

Enterprises in today＇s fast-paced business environment are always puzzled with billions of bytes of data flowing into their computers. In this paper, the new technology to solve this problem called ＂data warehousing＂ is introduced. Benefits which can be achieved from this technology for enterprises are also discussed. In addition, this paper describes ＂SAP Business Information Warehouse＂ （SAP BW）, especially its characteristics, which is the data warehousing solution from SAP. Finally, advantages and shortcomings of SAP BW are given.

Organizational Data Management： Proposing a Metadata-Driven Data Warehouse （DW） Model

Discussing the matter of organizational data management implies, almost automatically, the concept of data warehousing as one of the most important parts of decision support system （DSS）, as it supports the integration of information management by aggregating all data formats and provisioning external systems with consistent data content and flows, together with the metadata concept, as one of the easiest ways of integration for software and database systems. Since organizational data management uses the metadata channel for creating a bi-directional flow, when correctly managed, metadata can save both time and resources for organizations. This paperI will focus on providing theoretical aspects of the two concepts, together with a short brief over a proposed model of design for an organizational management tool.

Development of Geological Data Warehouse

Data warehouse (DW), a new technology invented in 1990s, is more useful for integrating and analyzing massive data than traditional database. Its application in geology field can be divided into 3 phrases: 1992-1996, commercial data warehouse (CDW) appeared; 1996-1999, geological data warehouse (GDW) appeared and the geologists or geographers realized the importance of DW and began the studies on it, but the practical DW still followed the framework of DB; 2000 to present, geological data warehouse grows, and the theory of geo-spatial data warehouse (GSDW) has been developed but the research in geological area is still deficient except that in geography. Although some developments of GDW have been made, its core still follows the CDW-organizing data by time and brings about 3 problems: difficult to integrate the geological data, for the data feature more space than time; hard to store the massive data in different levels due to the same reason; hardly support the spatial analysis if the data are organized by time as CDW does. So the GDW should be redesigned by organizing data by scale in order to store mass data in different levels and synthesize the data in different granularities, and choosing space control points to replace the former time control points so as to integrate different types of data by the method of storing one type data as one layer and then to superpose the layers. In addition, data cube, a wide used technology in CDW, will be no use in GDW, for the causality among the geological data is not so obvious as commercial data, as the data are the mixed result of many complex rules, and their analysis always needs the special geological methods and software; on the other hand, data cube for mass and complex geo-data will devour too much store space to be practical. On this point, the main purpose of GDW may be fit for data integration unlike CDW for data analysis.

Visual Composition of Complex Queries on an Integrative Genomic and Proteomic Data Warehouse

Biomedical questions are usually complex and regard several different life science aspects. Numerous valuable and he- terogeneous data are increasingly available to answer such questions. Yet, they are dispersedly stored and difficult to be queried comprehensively. We created a Genomic and Proteomic Data Warehouse (GPDW) that integrates data provided by some of the main bioinformatics databases. It adopts a modular integrated data schema and several metadata to describe the integrated data, their sources and their location in the GPDW. Here, we present the Web application that we developed to enable any user to easily compose queries, although complex, on all data integrated in the GPDW. It is publicly available at http://www.bioinformatics.dei.polimi.it/GPKB/. Through a visual interface, the user is only required to select the types of data to be included in the query and the conditions on their values to be retrieved. Then, the Web application leverages the metadata and modular schema of the GPDW to automatically compose an efficient SQL query, run it on the GPDW and show the extracted requested data, enriched with links to external data sources. Performed tests demonstrated efficiency and usability of the developed Web application, and showed its and GPDW relevance in supporting answering biomedical questions, also difficult.

基于KW、MW及DW的决策支持系统架构研究

SDSS是较为先进的决策支持系统,但由于其模型库中的模型固定不变,因此在实际应用中具有一定的局限性。提出了集成数据仓库DW、知识仓库KW和模型仓库MW作为底部架构的体系结构,能有效解决这一问题。该架构简化了模型获得和编码任务,增强了决策的有效性和智能性,提高了决策效率。

一种基于Dwarf的快速有效增量更新算法

数据立方计算是代价非常大的操作,并且被广泛研究。受空间的限制,存储一个完全实例化的数据立方是不可行的。最近提出的一种语义压缩数据立方—Dwarf,通过消除前缀冗余和后缀冗余把一个完全实例化的数据立方压缩存储到一个很小的空间。然而,当数据源发生变化时,它的更新过程是很复杂的。本文通过研究Dwarf在更新过程中汇总结点的变化特性,提出了一种基于Dwarf的新的增量更新算法,既能完全实例化数据立方又不需要重新计算,大大提高了数据立方的更新效率。实验进一步证明了该算法的效率和有效性,尤其适合数据仓库中的高维数据集。

抢先赢得商机的Data Mining──基于数据仓库的数据挖掘技术

首先介绍了数据仓库以及在此技术上产生的数据挖掘技术,其次阐述了实现数据挖掘应用的几种工具以及选用工具时应遵循的原则,最后说明了数据挖掘技术现存的问题及他现在重要的商业地位。

基于DW和OLAP技术的数字图书馆资源访问分析

针对数字图书馆资源服务系统积累中的大量数字资源访问数据,研究并实现基于数据仓库及OLAP技术的数字资源服务分析系统。首先建立了与资源服务系统分离的数据仓库,并对数据仓库进行多维建模;然后对多维数据模型进行切片、切块、旋转、上钻和下钻等多维操作,从多角度对数字资源访问数据分析;最后采用前端开发工具开发了可视化的多维分析和数据展示平台。实践表明,基于数据仓库的数字资源服务分析可以图书馆管理层提供有效的决策支持。

在CRM中应用DW、DM技术进行商业分析和决策

本文简要介绍了CRM的概念及CRM的实现模型 。

基于DW的空军通信装备技术保障DSS的框架研究

针对空军通信装备技术保障存在能力不足、决策支持手段落后等现状,提出了基于数据仓库（data warehouse,DW）的空军通信装备技术保障决策支持系统（decision support system,DSS）并构建了其整体架构,完成了系统DW设计,建构了系统元数据和数据抽取、转换、加载（extract,transform,load,ETL）的ETL模型,最后简述了系统的开发过程。该系统能有效地将通信装备技术保障数据转化为科学的决策信息,提高空军通信装备技术保障的效能。

Knowledge Discovery in Data: A Case Study

It is common in industrial construction projects for data to be collected and discarded without being analyzed to extract useful knowledge. A proposed integrated methodology based on a five-step Knowledge Discovery in Data (KDD) model was developed to address this issue. The framework transfers existing multidimensional historical data from completed projects into useful knowledge for future projects. The model starts by understanding the problem domain, industrial construction projects. The second step is analyzing the problem data and its multiple dimensions. The target dataset is the labour resources data generated while managing industrial construction projects. The next step is developing the data collection model and prototype data ware-house. The data warehouse stores collected data in a ready-for-mining format and produces dynamic On Line Analytical Processing (OLAP) reports and graphs. Data was collected from a large western-Canadian structural steel fabricator to prove the applicability of the developed methodology. The proposed framework was applied to three different case studies to validate the applicability of the developed framework to real projects data.

Web Data Cube Construction in Multidimensional On-line Analytical Processing Environment

This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube construction is proposed, which includes Web data modeling based on MIX （ Metadam based Integration model for data X-change ）, generic and specific mapping rules design, and a transformation algorithm for mapping Web data to a multidimensional array. Besides, the structure and implementation of the prototype of a Web data base cube are discussed.

基于C++的三维闪电回击数据再处理系统设计

针对三维闪电数据处理算法改进之后需重新定位回击数据,以及省级三维闪电探测系统的回击数据通常更加完整,应用时要将多个省份闪电回击数据合并后重新处理出准确的云内闪电高度值等问题,本研究使用C/S架构和C++builder编程开发了三维闪电回击数据再处理系统。系统设计了回击数据查询处理界面,提供了监视控制功能。通过设定回击数据文件和配置文件,再运行软件系统对符合条件的回击数据进行排序,在完成排序的数据中提取同一闪电相关信息,经计算处理得到重新定位的三维闪电探测结果并存储。将系统部署于国家级平台查询处理全国组网的三维闪电历史回击数据,测试结果表明,再处理系统操作便捷、功能齐全,满足三维闪电回击数据再处理系统的任务要求。

工业大数据在皮革产业智能化仓储物流体系中的多元应用研究

随着皮革产业转型升级工作的不断进行,智能化仓储物流体系在产业中的应用程度也越来越高。本文针对当前皮革产业智能化仓储物流的发展情况,对一种常见的智能化仓储物流体系模型进行分析,详细阐述了工业大数据在这些智能化仓储物流模型中的应用思路,包括库存布局、拣货路径优化、单量预测等。

基于区块链技术的物流仓储数据安全通信方法研究

由于传统物流仓储数据通信过程中存在诸多安全隐患,如数据篡改、信息泄露等,研究基于区块链技术的物流仓储数据安全通信方法。部署区块链网络存储物流仓储数据,对数据通信双方进行身份认证,通过后授予区块链访问权限,结合加密算法、消息路由算法及消息接收算法,实现区块链上的物流仓储数据安全通信传输。实验结果表明,在物流仓储数据通信存在伪造攻击的情况下,数据传输成功率高达98.69%,设计的方法保障通信数据安全性。

基于ArcPy的控规CAD数据向MDB数据转换方法研究

控制性详细规划是城市规划实施管理的法定依据,其成果数据是国土空间规划数据库的重要基础数据。目前,CAD数据是控规成果的主要源数据,准确高效地将CAD规划数据的图属信息向GIS数据转换与入库是“一张图”建设的前提保障。研究提出了一种基于Pywin32和ArcPy库二次开发的数据转换方法,构建了东莞市控规CAD数据向MDB数据的映射关系和无损转换模型,有效地实现了CAD数据图形和属性信息的无损转换。实践结果表明,该方法能确保数据在格式转换前后图形-属性信息的一致性和完整性,具有良好的实用性和平台通用性,为大数据背景下跨平台数据处理与共享打下了坚实基础。

雄安新区岩土地质时空信息服务平台建设与应用

岩土地质信息是城市规划设计和工程建设的重要基础资源,精准的地质数据对雄安规划建设、城市运行管理和安全保障具有重要支撑。但雄安岩土地质信息面临数据源质量难以保证、数据汇交不畅、共享应用困难、实时性程度低、标准体系不完善等问题,严重制约着数字孪生城市的同步建设,也无法为城市规划建设和运维提供精准的地质数据支撑。针对上述问题,开展了雄安新区岩土地质时空信息服务平台建设,构建了涵盖岩土地质数据源头监管、建库汇交、实时监测、共享应用全链条的智慧服务管理平台体系、标准体系和管理制度,系统性解决了岩土地质信息外业质量监管难、数据入库难和共享应用难等难题,建立了岩土地质信息服务城市规划、设计、建设、运营和管理的新模式。

基于数据仓库与数据服务中台的医疗大数据中心构建

目的:设计基于数据仓库(DW)与数据服务中台的医疗大数据中心,融合不同信息系统与组织架构之间的信息资源,搭建数据共享安全渠道,满足临床应用数据需求。方法:以数据流向为基础,以医院临床服务、运营管理、科研发展为依据,采用自上而下的数据应用层、数据服务层、DW层和操作型数据存储(ODS)层设计架构,设计基于DW与数据服务中台的医疗大数据中心,以医院数据和业务为导向,依据“对象-事件-报告”数据拆分逻辑,对各主题域包含角色对应的活动进行拆解和梳理,方便临床应用中快捷调用。结果:医疗大数据中心设置患者主索引管理和主数据管理基础模块,共设置可以覆盖医院的临床服务、医院管理、患者标识等16大业务主题域和52个业务子域,医疗大数据中心应用包含临床数据中心、运营数据中心和科研数据中心,并对各大类信息间的关联逻辑进行明确定义,对服务应用程序接口全生命周期进行集中管理,结合主数据信息,全面治理医疗数据,实现了医院数据归一化,并借助大数据技术建立高质量的数据资产和有弹性的DW模型。结论:基于DW与数据服务中台的医疗大数据中心能够对医院不同信息系统与医院内的其他数据进行整合,实现接口服务便捷调用和医院数据的规范化、持久化管理,保障临床应用、运营决策及科研分析等数据应用需求。

基于多元回归模型在ZJ70D电控房中通风量的预测

针对ZJ70D钻机电控系统房体内部温度过高导致设备寿命减少、人为实时关注通风量等问题,提出一种基于多元回归模型在ZJ70D电控房中通风量的预测(Predictive Calculation of Ventilation Volume Based on Multiple-regression Model in ZJ70D,MRM)方法,通过采集房体内部温度、湿度及外部环境数据,建立多元线性回归模型,并求解各个模型参数,利用DW模型拟合数据的准确性,预测当前时刻后的所需通风量,实现通风量的实时调节。实验表明,本文提出的计算方法能够提高电控房内通风量控制的精确性,并通过误差分析验证了模型的可行性和适应性。