Hypertext Technique and its Application to Engineering Data Management

Since the late of previous decade, hypertext technique has been applied in many areas. A hypertext data model with version control which is applied to a digital delivery for engineering documents named Optical Disk based Electronic Archives Management System(ODEAMS) is presented first and it has successfully solved some problems in engineering data management. Then, this paper describes some details to implement the hypertext network in ODEAMS after introducing the requirements and characters of engineering data management.

Integrated Engineering Design and Data Management

This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.

Engineering Change Management Adaptive to PLM

Engineering Change (EC) management for a Product Lifecycle Management (PLM) system, including EC data model, EC evaluation and EC implementation is presented. A method of dynamic and parallel EC evaluation is proposed, which breaks an EC evaluation task into several subtasks. Such subtasks can be dynamically and simultaneously proceeded, disassembled and communicated by different specialists, and at the same time a set of EC objects is created. This approach provides flexible and effective evaluation of the EC. The EC implementation followed will further ensure the completeness and consistency of EC data.

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.

Blockchain-based engine data trustworthy swarm learning management method

Engine data management is of great significance for ensuring data security and sharing,as well as facilitating multi-party collaborative learning.Traditional data management approaches often involve decentralized data storage that is vulnerable to tampering,making it challenging to conduct multi-party collaborative learning under privacy protection conditions and fully leverage the value of data.Moreover,data with compromised integrity can lead to incorrect results if used for model training.Therefore,this paper aims to break down data sharing barriers and fully utilize decentralized data for multi-party collaborative learning under privacy protection conditions.We propose a trustworthy engine data management method based on blockchain technology to ensure data immutability and non-repudiation.To address the issue of limited data samples for some users resulting in poor model performance,we introduce swarm learning techniques based on centralized machine learning and design a trustworthy data management method for swarm learning,achieving trustworthy regulation of the entire process.We conduct research on engine models under swarm learning based on the NASA open dataset,effectively organizing decentralized data samples for collaborative training while ensuring data privacy and fully leveraging the value of data.

Intelligent data analytics is here to change engineering management

A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern scientific discovery and technologic advancement. The importance of good information was long recognized by prominent leaders such as Sun Tzu and Napoleon. Factual data enables managers to measure, to understand their businesses, and to directly translate that knowledge into improved decision making and performance. This position paper argues that data analytics is ready to change engineering management in the following areas: 1) by making relevant historical data available to the manager at the time when it's needed; 2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful data from multiple sources to support quantitative decision-making. Considering the unique need for engineering management, the paper proposes researchable topics in the two broad areas of data acquisition and data analytics. The purpose of the paper is to provoke discussion from peers and to encourage research activity.

Challenges to Engineering Management in the Big Data Era

This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge and the history of big data. Second, the paper reviews the academic activities about big data in China. Then, it elaborates a number of challenging big data problems, including transforming semi-structured and non-structured data into"structured format" and explores the relationship of data heterogeneity, knowledge heterogeneity and decision heterogeneity. Furthermore, the paper reports various real-life applications of big data, such as financial and petroleum engineering and internet business.

基于ArcGIS Engine的小型地籍信息管理系统的开发

在地籍信息的管理建设中,将地籍数据的属性数据与矢量数据一体化,建立小型的地籍信息管理系统,可以降低管理成本,为地籍信息管理工作提供便捷的管理手段和有效的决策。本文对地籍信息管理系统的现状进行了研究,总结了系统的总体框架,并且阐述了所涉及的关键技术,选用.NET架构搭建平台,利用C/S模式实现了小型地籍信息管理系统的开发。根据系统的需求与数据的特征,以ArcGIS Engine、VS2010、C#为开发工具,在ArcCatalog中建立文件地理数据库,实现了查询、统计、数据的编辑更新、空间分析、专题图制作、统计与输出等功能。通过实验数据验证,本系统操作简便,可满足对地籍数据管理的需要。

Special issue: Advances and prospect of engineering management

As an important part of engineering domain,construction engineering and management focuses on studying the planning,execution and maintenance of civil and infrastructure projects.This special issue is composed based on a collection of research papers contributed by a group of leading experts,dedicating to providing a state-of-the-art development in construction management research.

数智赋能信息资源管理新路径:指令工程的概念、内涵和发展

新一轮科技革命和产业变革方兴未艾,大数据、人工智能等系列数智技术对信息资源管理学科产生了深远影响。在大模型背景下,指令工程通过高质量、体系化、流程化的指令设计引导模型生成结果,是高效发挥大模型能力的重要途径,可以用于解决学科相关重要问题。本文首先介绍了指令工程的概念,然后详细梳理了指令的构成要素、设计模式以及指令工程的特点和意义,并探讨了指令工程赋能信息资源管理的建设路径。未来,指令工程的研究和发展还需要关注通用及领域指令工程建设、指令工程标准化、知识产权保护、安全性和体系化测试评估等问题,以期能够在各行业复杂的应用场景中更好地发挥指令的效能。

基于ArcGIS Engine的空间信息项目一体化管理系统的研究

测绘和地理信息空间数据作用重要,但不易管理。为此,文章从生产单位实际工作管理需求出发,分析了传统数据管理的不足和弊端,提出了基于Arc GIS Engine的空间信息项目一体化管理系统的研发思路,实现了多元空间信息数据及项目信息快速入库、便捷调用、统一管理,为市县级测绘单位的数据管理提供了一种方法。

DataGrid数据引擎助运营商业务转型

在传统移动网络中,用户数据的管理通过HLR实现。随着网络越来越复杂,提供的业务越来越多,离散在各网元中的信息,形成了"数据孤岛",用户数据不能充分利用和开发。随着运营商越来越强烈的精品网络意识,和业务转型的必然趋势,大家逐渐意识到用户数据的重要性和必要性,需要一种能够适应网络发展的新方法来进行用户数据管理、开发和应用。DataGrid正是提供了这样一个革命化的概念和产品,水平化组织数据,在整合数据的基础上,挖掘数据的内在联系,统一用户数据视图,为提供个性化业务提供数据平台的支持。

数智技术时代的中国档案学学科发展

数智技术,直接导致我国千行百业的原始数据形成,其管理正发生前所未有的变化。为适应从人人相连走向万物智联的大数据安全管理,需要对我国高等教育相关学科专业进行系统研究。梳理数字技术对我国组织的业务活动及其原始记录形成和管理的作用影响之后,提出传统的“中国档案学”学科将演进为“档案大数据工程”学科。并且指出,档案大数据工程学科高等教育包括“管理文秘”“数据资源管理”“大数据技术”等专业,尝试提出以上几个专业建设的发展方向。

基于ArcGIS Engine的雨量数据管理软件开发

针对纸质雨量数据资料存在的管理和应用现状,基于ArcGIS Engine二次开发平台,用C#语言开发出雨量数据管理软件。通过对纸质雨量数据的处理,得到数字雨量值模型数据及雨量等值线图,本软件对上述数据进行管理,并实现了图层管理、数据查询、编辑及导出等功能。本程序对雨量数据进行数字化管理及应用,极大提高了雨量数据使用的工作效率和精度。

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。

大数据环境下基于BIM与CNN的电力工程造价优化算法

针对大数据环境下电力工程造价在精准化、动态化等方面存在的不足,提出了一种基于BIM与CNN的电力工程造价优化算法。利用BIM技术的特点进行电力工程全生命周期的造价管理,实现了造价的动态化管控。并且采用Levenberg-Marquardt规则算法改进卷积神经网络,通过改进后的CNN网络对每个工程环节的造价完成预测,从而优化整个工程的施工方案。结合相关的电力工程造价数据,基于Matlab对所提算法进行实验测试。结果表明,当学习率为0.010时CNN网络的性能最佳,所提算法的预测准确率为94%,并且与造价的真实值最为接近。

全过程工程咨询的数据协同管理模式研究

为凸显全过程工程咨询模式的核心价值和优势,需要克服多参与方、多阶段、多专业数据衔接不畅问题,实现全过程、多专业之间的数据高效协同管理。本研究通过分析全过程工程咨询项目的数据分类和数据交互需求,针对典型全过程工程咨询项目数据协调方面存在问题,从“物理-事理-人理”方面提出数据协同分析框架,提出构建“一套数字基座平台、一个数据协同管理组织、一套协同管理机制”的实体集中型数据协同管理模式,旨在为业内同行的全过程工程咨询数据管理提供有益参考。

剧院舞台机械资料管理探索与实践

随着现代舞台技术不断发展和剧院规模不断扩大,舞台机械资料管理面临越来越多的挑战和机遇。随着舞台机械资料的种类和数量不断增加,目前还没有类似建筑电气、智能建筑等分部工程有完善的资料管理、组卷、归档规范,给舞台机械资料管理增加了难度。基于北京艺术中心项目对剧院舞台机械资料管理进行深入研究与分析,以期为剧院管理人员提供相关参考价值。

企业数据资产管理体系框架研究及实践

通过对数据要素产生、变现的过程进行研究,构建了数据资产管理体系框架模型。该体系框架包含数据资产运营框架、数据资产体系模型、数据资产工程实施模型3部分。其中,数据资产运营框架定义了数据要素运转原理,即业务数据化、数据资产化、资产服务化、服务业务化“四化”过程;数据体系模型是包含业务数据层、数据汇聚层、数据模型层、数据服务层、数据应用层的5层模型,实现了数据分层治理,数据从下往上流动实现数据要素价值;数据资产工程实施模型定义了实施的指导模型,包括工程管理流程、数据模型开发流程、应用开发流程和数据资产资源管理4部分。文章还介绍了该体系框架模型的实践应用,在历史系统、在建系统、新建系统环境中数据资产管理的实施中,验证了该体系框架模型在数据资产管理中的可行性,旨在为企业数据资产管理建设提供有价值的参考。

测量标志数据管理系统设计与实现

测量标志数据管理系统是实现测量标志管理信息化的基础,是测量标志数据采集、汇总、查询统计、决策分析的基础。本文详细介绍了以Visual Studio为开发平台、C#为编程语言、结合Microsoft Office Access数据库管理系统及ArcGIS Engine对测量标志数据管理系统进行设计与开发。系统实现了测量标志巡查、托管、维护维修等基本信息的录入、存储、汇总分析等功能,极大地提高了测量标志数据管理信息化能力。