An Application of a Multi-Tier Data Warehouse in Oil and Gas Drilling Information Management

Expenditure on wells constitute a significant part of the operational costs for a petroleum enterprise, where most of the cost results from drilling. This has prompted drilling departments to continuously look for ways to reduce their drilling costs and be as efficient as possible. A system called the Drilling Comprehensive Information Management and Application System (DCIMAS) is developed and presented here, with an aim at collecting, storing and making full use of the valuable well data and information relating to all drilling activities and operations. The DCIMAS comprises three main parts, including a data collection and transmission system, a data warehouse (DW) management system, and an integrated platform of core applications. With the support of the application platform, the DW management system is introduced, whereby the operation data are captured at well sites and transmitted electronically to a data warehouse via transmission equipment and ETL (extract, transformation and load) tools. With the high quality of the data guaranteed, our central task is to make the best use of the operation data and information for drilling analysis and to provide further information to guide later production stages. Applications have been developed and integrated on a uniform platform to interface directly with different layers of the multi-tier DW. Now, engineers in every department spend less time on data handling and more time on applying technology in their real work with the system.

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.

Study on Material ManagementSystem of Coal Enterprise Basedon Data Warehouse

On the bas is of the reality of material supply management of the coal enterprise, this paper expounds plans of material management systems based on specific IT, and indicates the deficiencies, the problems of them and the necessity of improving them. The structure, models and data organizing schema of the material management decision support system are investigated based on a new data management technology (data warehousing technology).

Web-based: A data warehouse on osteoporosis data warehouse in the osteoporosis community health information management system

Objective: To establish an interactive management model for community-oriented high-risk osteoporosis in conjunction with a rural community health service center. Materials and Methods: Toward multidimensional analysis of data, the system we developed combines basic principles of data warehouse technology oriented to the needs of community health services. This paper introduces the steps we took in constructing the data warehouse;the case presented here is that of a district community health management information system in Changshu, Jiangsu Province, China. For our data warehouse, we chose the MySQL 4.5 relational database, the Browser/Server, (B/S) model, and hypertext preprocessor as the development tools. Results: The system allowed online analysis processing and next-stage work preparation, and provided a platform for data management, data query, online analysis, etc., in community health service center, specialist outpatient for osteoporosis, and health administration sectors. Conclusion: The users of remote management system and data warehouse can include community health service centers, osteoporosis departments of hospitals, and health administration departments;provide reference for policymaking of health administrators, residents’ health information, and intervention suggestions for general practitioners in community health service centers, patients’ follow-up information for osteoporosis specialists in general hospitals.

ROLE OF META-MODEL IN ENGINEERING DATA WAREHOUSE

Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.

Construction of Meteorological Observation Quality Management System for Basic Observation Business

A set of closed-loop normative standards of PDCA(planning-implementing-checking-improvement) of the quality management system is applied to promote the standardization, normalization and institutionalization of grass-roots meteorological observations, further improve the service availability and timely rate of data, and improve the quality and efficiency of meteorological observations.

A trajectory data warehouse solution for workforce management decision-making

In modern workforce management,the demand for new ways to maximize worker satisfaction,productivity,and security levels is endless.Workforce movement data such as those source data from an access control system can support this ongoing process with subsequent analysis.In this study,a solution to attaining this goal is proposed,based on the design and implementation of a data mart as part of a dimensional trajectory data warehouse(TDW)that acts as a repository for the management of movement data.A novel methodological approach is proposed for modeling multiple spatial and temporal dimensions in a logical model.The case study presented in this paper for modeling and analyzing workforce movement data is to support human resource management decision-making and the following discussion provides a representative example of the contribution of a TDW in the process of information management and decision support systems.The entire process of exporting,cleaning,consolidating,and transforming data is implemented to achieve an appropriate format for final import.Structured query language(SQL)queries demonstrate the convenience of dimensional design for data analysis,and valuable information can be extracted from the movements of employees on company premises to manage the workforce efficiently and effectively.Visual analytics through data visualization support the analysis and facilitate decisionmaking and business intelligence.

Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.

A study on building data warehouse of hospital information system

Background Existing hospital information systems with simple statistical functions cannot meet current management needs. It is well known that hospital resources are distributed with private property rights among hospitals, such as in the case of the regional coordination of medical services. In this study, to integrate and make full use of medical data effectively, we propose a data warehouse modeling method for the hospital information system. The method can also be employed for a distributed-hospital medical service system. Methods To ensure that hospital information supports the diverse needs of health care, the framework of the hospital information system has three layers： datacenter layer, system-function layer, and user-interface layer. This paper discusses the role of a data warehouse management system in handling hospital information from the establishment of the data theme to the design of a data model to the establishment of a data warehouse. Online analytical processing tools assist user-friendly multidimensional analysis from a number of different angles to extract the required data and information. Results Use of the data warehouse improves online analytical processing and mitigates deficiencies in the decision support system. The hospital information system based on a data warehouse effectively employs statistical analysis and data mining technology to handle massive quantities of historical data, and summarizes from clinical and hospital information for decision making. Conclusions This paper proposes the use of a data warehouse for a hospital information system, specifically a data warehouse for the theme of hospital information to determine latitude, modeling and so on. The processing of patient information is given as an example that demonstrates the usefulness of this method in the case of hospital information management. Data warehouse technology is an evolving technology, and more and more decision support information extracted by data mining and with decision-making technology is required for further research.

Research on Welding Quality Traceability Model of Offshore Platform Block Construction Process

Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry.Currently,qualitymanagement remains in the era of primary information,and there is a lack of effective tracking and recording of welding quality data.When welding defects are encountered,it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data.In this paper,a composite welding quality traceability model for offshore platform block construction process is proposed,it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm.By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm,the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems.Furthermore,the model and the quality traceability algorithm are checked by cases in actual working conditions.Verification analyses suggest that the proposed early-warningmodel for welding quality and the algorithmfor optimizing backtracking requests are effective and can be applied to the actual construction process.

A Rule Management System for Knowledge Based Data Cleaning

In this paper, we propose a rule management system for data cleaning that is based on knowledge. This system combines features of both rule based systems and rule based data cleaning frameworks. The important advantages of our system are threefold. First, it aims at proposing a strong and unified rule form based on first order structure that permits the representation and management of all the types of rules and their quality via some characteristics. Second, it leads to increase the quality of rules which conditions the quality of data cleaning. Third, it uses an appropriate knowledge acquisition process, which is the weakest task in the current rule and knowledge based systems. As several research works have shown that data cleaning is rather driven by domain knowledge than by data, we have identified and analyzed the properties that distinguish knowledge and rules from data for better determining the most components of the proposed system. In order to illustrate our system, we also present a first experiment with a case study at health sector where we demonstrate how the system is useful for the improvement of data quality. The autonomy, extensibility and platform-independency of the proposed rule management system facilitate its incorporation in any system that is interested in data quality management.

A Framework for Identifying and Managing Information Quality Metrics of Corporate Performance Management System

Corporate Performance Management （CPM） system is an information system used to collect, analyze, and visualize key performance indicators （KPIs） to support both business operations and especially strategic decisions. CPM systems display KPIs in forms of scorecard and dashboard so the executives can keep track and evaluate corporate performance. The quality of the information as shown in the KPIs is very crucial for the executives to make the right decisions. Therefore, it is important that the executives must be able to retrieve not only the KPIs but also the quality of those KPIs before using such KPIs in their strategic decisions. The objectives of this study were to determine the role of the CPM system in the organizations, current data and information quality state, problems and perspectives regarding data quality, as well as data quality maturity stage of the organizations. Survey research was used in this study; a questionnaire was sent to collect data from 477 corporations listed in the Stock Exchange of Thailand （SET） on January, 2011. Forty-nine questionnaires were returned. The results show that about half of the organizations have implemented CPM systems. Most organizations are confident in the information in CPM system, but information quality issues are commonly found. Frequent problems regarding information quality are information not up to date, information not ready by time of use, inaccuracy and incomplete. The most concerned and frequently assessed quality dimensions were security, accuracy, completeness, and validity. When asked to prioritize, the most important quality dimensions are accuracy, timeliness, completeness, security, and validity respectively. In addition, most organizations concern about data govemance management and have deployed such measures. This study showed that most organizations are on level 4 on Gartner＇s data governance maturity stage in which data governance is concerned and managed, but still not effective.

企业高质量数字化转型管理:理论前沿

在相关领域理论前沿与企业实践的基础上,首先,基于数据生产要素和数实融合的中国数字经济原创思想及理论,按“基础理论—应用基础理论—应用理论”的科学研究递进逻辑,提出企业高质量数字化转型管理的研究框架;然后,归纳提炼出7个重要研究领域及关键科学问题;最后,通过与已有相关研究框架和结论的文献对话,论述该框架理论的学术价值和实践指导潜力,以期为今后的理论研究提供方向性指导。

ArcGIS Data Reviewer在林业矢量数据质量管理中的应用

介绍ArcGIS Data Reviewer基本功能和特性,对其应用于林业地理信息矢量数据质量检查,如图斑重复、重叠,图斑间有间隙、多部件、狭长面、急锐角化、漏绘等空间关系,以及属性字段之间的逻辑性检查等的方法和步骤,举例进行了详细叙述,可为该软件模块的使用提供参考。

基于大数据反馈的急诊预检全流程管理实践

目的:评价基于大数据反馈的急诊预检全流程管理的效果,为提高急诊预检分诊质量提供借鉴。方法:采用历史对照研究方法,便利选取杭州市某三级甲等医院2021年4月22689位急诊预检患者作为改进前组,接受常规急诊预检分诊管理;以2022年4月22236位急诊预检患者作为改进后组,接受大数据反馈的急诊预检分诊全流程管理,包括预检前、中、后端质量的动态评估及持续改进。比较改进前后急诊预检分诊质量和效率。结果:实施基于大数据反馈的全流程预检管理后,患者分诊信息完整率、分诊级别符合率、响应时间符合率显著高于改进前(P<0.05),分诊候诊时间、候诊不良事件发生率显著低于改进前(P<0.05)。结论:基于大数据智能化及可视化的全流程管理可有效提高急诊预检分诊质量与效率,保障急诊患者安全。

《真实世界针灸临床研究数据管理规范》的编制与解读

随着中医药标准化进程的不断加快和由于真实世界临床研究理念的影响,越来越多的研究者重视从真实世界获得数据,以解决医学问题。针灸临床试验由于实施盲法存在一定困难,使得随机对照研究并不好开展,因而越来越多地转向真实世界研究。真实世界数据主要来源于医院信息系统数据、登记研究数据、医保支付数据等多个数据源,相较于“金标准”随机对照试验(Randomized Controlled Trial,RCT),真实世界数据在大多数情况下缺乏记录、采集、存储等流程的研究质量控制,数据质量问题严重影响了临床研究结果的可靠性。数据管理是提高数据质量的重要途径,故《真实世界针灸临床研究数据管理规范》的诞生对于真实世界针灸临床研究的规范性具有重要意义。因此,通过详述该规范的编制原则、方法、过程及具体内容和在编制中的思考过程,希望帮助读者深刻理解该规范的内容,将该规范应用于数据管理实践,提高研究数据质量。

基于数据驱动的临床危急值数据直采与统筹管理实践

临床危急值管理是医疗质量安全核心制度的要求。为进一步推动住院患者危急值规范化管理,搭建基于数据驱动的市级医院医疗质量安全信息监管平台,制订临床危急值数据直采标准,加强危急值的数字化应用,建立临床危急值管理促进机制,在应用与联动中提升危急值管理标准化与精细化水平。实施后,危急值临床及时确认率、危急值临床及时处置率和危急值规范闭环率得以显著提升。统一的区域临床危急值数据直采与统筹管理体系,能够确保数据精准可靠,拓展分析广度和深度,促进医疗质量安全持续改进。

基于全生命周期管理的县域水利工程数字档案馆的研发与应用

针对县域水利工程全生命周期过程档案不全、无法实现闭环管理的难题,通过数据仓库、数据接口、一码通管理等技术的研发应用实现闭环管理,并在苍南县进行了应用。县域水利工程数字档案馆采用NoSQL和MPP NewSQL相结合的方法建设数据仓,以解决数字档案馆的多元化数据存储问题;采用API和XML Web Service接口融合方法,解决了内部局域网系统和外部其他云系统的接口对接问题;开发了基于工作流引擎技术的SPARK分布式组件库,实现了水利局各个科室的业务协同与数据共享;采用一码通三色督查技术建立了三阶段数字档案健康评价指标体系,实现了“绿、黄、红”一码督查的管理档案;采用全链透析档案串并联技术,实现了水利工程整个全生命周期过程的数据分析。

大数据驱动的税收征管与非上市公司高质量发展——基于创新行为的研究视角

作为我国经济发展的重要力量,非上市公司创新行为是社会技术进步不可或缺的推动力。利用独特的全国税收调查数据,以金税三期工程在我国各省市的逐步试点作为政策冲击,探讨大数据驱动的税收征管是否以及如何影响非上市公司的创新行为。实证研究发现,在金税三期工程试点实施后,非上市公司加大了创新投入。机制检验发现,这种影响主要是通过大数据税收征管的公司治理效应和信息质量效应获得实现。异质性检验发现,大数据税收征管对非上市公司创新投入的影响与金税三期工程实施的客观条件和主观能动性,以及企业融资约束程度密切相关。进一步分析发现,在金税三期工程试点实施后,非上市公司的创新产出有了明显提升。