"973"计划资源环境领域数据汇交进展与数据分析

国家科技计划项目数据汇交对于促进科学数据的整合集成,增强国家科技投入的效益,提高我国科技计划项目管理水平具有重要意义。经过充分研究,科技部基础司选择国家重点基础研究发展计划(973计划)资源环境领域作为试点,于2008年启动数据汇交工作,并专门成立数据汇交中心。2008年,按照数据汇交计划制定、数据汇交准备、数据实体汇交、数据共享服务4个阶段的工作流程,分"已结题"、"即将于2008年结题"和"在研"3种类型开展汇交工作,完成了24个结题项目的数据汇交,汇交数据总量超过620 GB。为了保证数据汇交的可操作性和规范化,数据汇交中心制定了包括核心元数据规范、数据文档格式等7项标准规范;研制了数据汇交软件工具;建立了海量数据存储环境;设计开发了数据汇交共享服务网络平台。面向数据服务进一步的需要,分析了已汇交数据情况,具体分为5种类型,即定点长期监测和野外定点调查类、区域调查和统计分析类、模型计算类、试验化验分析类、客观或主观描述类,并提出了相应的数据展示策略。     

地层信息系统中的地质实体与数据类型

结合地质实体概念厘清数据类型及其特征对地层信息系统的发展有重要意义。地层信息系统数据可以归类为属性数据、几何数据、关系数据、元数据4类,地层信息中的地质实体可分为基础地质实体和地质实体要素,进一步把地质实体要素分为关联要素和非关联要素。文中分析了矿体、风化分界面、断层、褶皱、不整合面、滑坡体的几何属性。区分观测者位置、数据采集点和数据本身空间属性,数据获取方法可分为地表调查、钻入调查、岩层透视调查、岩层非透视调查,并分析了原始数据与地质实体的对应关系。     

A review of geoanalytical databases

Geoanalytical data provide fundamental information according to which the Earth’s resources can be known and exploited to support human life and development. Large amounts of manpower and material and financial resources have been invested to acquire a wealth of geoanalytical data over the past 40 years. However, these data are usually managed by individual researchers and are preserved in an ad hoc manner without metadata that provide the necessary context for interpretation and data integration requirements. In this scenario, fewer data, except for published data, can be reutilized by geological researchers. Many geoanalytical databases have been constructed to collect existing data and to facilitate their use. These databases are useful tools for preserving, managing, and sharing data for geological research, and provide various data repositories to support geological studies. Since these databases are dispersed and diverse, it is difficult for researchers to make full use of them. This contribution provides an introduction on available geoanalytical databases. The database content can be made accessible to researchers, the ways in which this can be done, and the functionalities that can be used are illustrated in detail. Moreover, constraints that have limited the reutilization of geoanalytical data and creation of more advanced geoanalytical databases are discussed.

     

水工监测软件开发中数据库和数据结构设计问题

针对水电工程监测软件系统开发,讨论了系统总体设计、数据库和数据结构设计以及系统界面架构方面的一些共性问题,提出用7种属性对象来描述水工建筑物和观测仪器之间,以及各水工建筑物之间复杂的从属关系,介绍了实现这些关系的数据库表和相关数据结构;讨论了采取单文档和多窗口视界面的优点、可变大小的整编数据结构、软件容错、设置多个初值日期和更换传感器所带来的数据结构设计等问题。这些讨论对于开发监测系统软件是很有益的。     

Normal and lognormal data distribution in geochemistry: death of a myth. Consequences for the statistical treatment of geochemical and environmental data

All variables of several large data sets from regional geochemical and environmental surveys were tested for a normal or lognormal data distribution. As a general rule, almost all variables (up to more than 50 analysed chemical elements per data set) show neither a normal or a lognormal data distribution. Even when different transformation methods are used more than 70 % of all variables in every single data set do not approach a normal distribution. Distributions are usually skewed, have outliers and originate from more than one process. When dealing with regional geochemical or environmental data normal and/or lognormal distributions are an exception and not the rule. This observation has serious consequences for the further statistical treatment of geochemical and environmental data. The most widely used statistical methods are all based on the assumption that the studied data show a normal or lognormal distribution. Neglecting that geochemcial and environmental data show neither a normal or lognormal distribution will lead to biased or faulty results when such techniques are used. Received: 21 June 1999 · Accepted: 14 August 1999     

探地雷达数据可视化方法

采用文件映射降低大数据量探地雷达(GPR)数据显示对计算机内存的需求,同时使GPR数据可以当作一维数组进行数据处理,方便对数据的随机、实时访问;应用直接写位图、视区分割的成图方案,实现对GPR数据的实时显示;通过位图调色板实现GPR数据调色板,灵活应用该技术可使本来需要对原始数据进行大量运算的算法通过调整调色板实现,提高了GPR数据处理的速度。     

Derivation of short-duration design rainfalls using daily rainfall statistics

Design rainfall intensity–frequency–duration data are a basic input to many water-related development projects. To derive design rainfalls, one needs long period of recorded rainfall data. Although daily rainfall data are generally widely available, short-duration rainfall data are scarce. For many urban applications, design rainfalls for much shorter durations are needed, which cannot be obtained directly from daily read rainfall data. This paper presents a simple approach that can be adopted to derive design rainfalls of short durations using daily rainfall data and other physio-climatic characteristics using a novel ‘index frequency combined with parameter regression technique’. This uses L moments to reduce the impacts of sampling variability in the analysis. Furthermore, this adopts generalised least squares regression to account for the inter-station correlation of the rainfall data in the analysis. The proposed method is applied to a pilot data set consisting of 203 rainfall stations across Australia. An independent Monte Carlo cross-validation test shows that the proposed method is capable of generating consistent and accurate design rainfall estimates from 6-min to 12-h duration. The developed technique can be adapted to other countries where there is a scarcity of short-duration rainfall data, but daily rainfall data are abundant.     

Reconceptualizing the role of the user of spatial data infrastructure

Spatial data infrastructures, which are Internet-based mechanisms for the coordinated production, discovery, and use of geospatial information in the digital environment, have diffused worldwide in the last two decades. Currently, there are about one hundred spatial data infrastructures at the national level and many other at supra- and sub-national levels. These contemporary spatial data infrastructures operate with two main assumptions: formal organizations are the producers and suppliers of geospatial information; users are the passive recipients of information. The recent phenomenon of volunteered geographic information departs from these assumptions. In this paper, we argue that reconceptualizing the user of a spatial data infrastructure can accommodate this new phenomenon. Such a reconceptualization creates a middle ground between spatial data infrastructure and volunteered geographic information, which has important implications for future research.     

渗流监测数据缺失处理与渗透稳定判断

由于地下岩体条件复杂,渗流监测数据缺失现象普遍存在。为了在时间和空间上对地下渗流场进行全面分析,需要对缺失数据进行补充。提出了三类缺失数据的插补方法,对时间序列、空间断面以及区域整体的缺失数据分别用监测统计模型、物理因子修正和反演进行了有效的补充,反映了缺失数据的规律和时间、空间因素对监测数据的影响,最终可得完整、全面的渗流场,并通过反演渗流场对渗透稳定进行判断,为工程评价提供了依据。将该方法用于天荒坪电站缺失数据的插补,结果有效地插补了缺失数据,最终的反演渗流场能够判断渗透破坏可能发生的部位,对工程加固措施具有指导意义。     

探讨基于CitusDB的地质资料集群和大数据架构

地质资料是地质工作形成的重要成果资料,具有可被重复开发利用、能够长期提供服务的功能。然而,因地质资料的分散式管理,使得地质资料信息存储分散,“孤岛”式服务的现象普遍存在,缺乏资料信息共享、综合利用的机制和手段,制约着地质资料信息潜在价值的有效发挥。地质资料信息服务集群化旨在通过信息领域前沿技术,对地质资料进行集成集群和深度开发,将分散、孤立的地质资料进行分布式汇集,全方位多角度解读、展现、挖掘地质资料信息,充分发挥地质资料服务于经济社会发展的作用。长期的地质调查工作,已经形成了多专业、数据格式多样的海量地质资料,信息服务的集群化必将面临地质大数据相关的技术问题。介绍了地质资料信息服务集群化模式,分析了CitusDB软件的分布式大数据运行机理,探讨了基于CitusDB软件的地质资料集群和大数据服务架构,可为地质大数据与信息服务提供一定的参考。     

基于数据智能可视化分析的滑坡信息化施工研究

采用信息化施工技术进行大型滑坡整治,既安全又经济。笔者探讨了基于大量监测数据处理为核心的信息化施工技术。采用数据可视化技术对大型滑坡巨大数据进行分析处理,确定了滑动面位置、滑动方向和对滑坡进行危险性分区。将支持向量机方法用于预测滑坡变形。将智能和可视化分析结果用于滑坡动态优化设计中,并用一个实际工程实例论述了方法的思路。     

基于控制字典的对象式地质属性数据管理

传统地质数据管理与应用是参照数据库的外模式来设计数据结构和数据访问接口,在业务逻辑没有发生大的变动情况下,外模式发生更改后,需要修改应用程序才能适应新的数据库结构.鉴于此弊,在关系数据库视图机制的启发下,通过分析不同地质专业地质属性数据的特征,对地质数据库外模式的高度概括,形成用于地质业务分析评价所需的关键属性组成的元组集——控制字典表,基于控制字典抽象出面向地质行业的对象式数据模型、映射数据模型与地质数据的关系,并参照控制字典表的“数据结构”来设计数据访问接口,最终实现地质数据库的动态扩展,无需再修改应用程序,需要做的仅仅是修改控制字典与外模式之间的映射关系,以不变应万变.控制字典作为一个中间件,将用户对地质数据的操作和计算机对地质数据的处理分离开来,充分保证了程序和数据层的逻辑独立性.      

澳大利亚油气地质资料汇交与公开制度及其借鉴意义

油气地质资料是国家重要的资源,其作用的发挥取决于地质资料的管理水平,而资料汇交和公开是资料管理中的重要内容。澳大利亚联邦和各州在油气地质资料的汇交和公开方面都有完善的法律规定,以罚款和矿权审查作为主要的手段约束矿权所有人的汇交行为,通过属地化管理为汇交油气地质资料提供便利条件,建立完善的资料管理信息系统,提高资料的管理和使用效率。中国在油气地质资料管理方面存在诸多问题。需要完善法律法规,严格落实矿权管理制度来促进资料的汇交;推行属地化管理,打破原有的条块分割,降低资料管理成本;完善现行的委托保管制度,加大在油气地质资料管理方面的资金投入;加快建立全国油气地质资料管理服务系统,通过公益服务与商业服务相结合的方式来提高资料共享水平。     

1988 Compilation of Elemental Concentration Data for USGS Basalt BCR-1

Concentration data on up to 82 individual constituents in USGS Basalt BCR-1 have been collected from 1395 journal articles and technical reports. These data are summarized in consensus (mean) values with uncertainties expressed as ± one standard deviation. Mean values are also calculated as a function of analytical procedure and all raw data are given in the tables. Recommended values are proposed based upon data criteria used by NIST (National Institute of Standards and Technology, formerly the National Bureau of Standards or NBS).     

GLDAS月降水数据在中国区的适用性评估

全球陆面数据同化系统(GLDAS)是全球变化与水循环研究的重要数据源之一.对比分析了1979—2012年间GLDAS多套降水数据与中国地面观测逐月降水数据所反映的中国降水趋势变化空间特征,采用相关系数、平均偏差、相对绝对误差和均方根误差4个指标,从时间变化和空间分布特征两个方面,对GLDAS降水数据在中国区域的数据质量进行了系统评估.结果表明:GLDAS-1的几套数据在时间上具有明显不连续性,1996年数据质量严重异常,2000年数据质量也较差,而且,不论是GLDAS-1数据,还是GLDAS-2数据,都存在前期(1979—1995年)与实测数据吻合度高于后期(1997年以后)的现象;GLDAS数据在中国东部湿润区的质量高于在西部干旱区;从相关性与误差指标来看,GLDAS-1数据质量略优于GLDAS-2(主要体现在1995年以前时段),但是GLDAS-2在数据一致性、数据质量季节稳定性及对趋势性描述能力方面则明显优于GLDAS-1数据.     

煤矿水害的多源信息及定量化方法预测研究与应用

基于MAPGIS平台,用V isual C 对其进行专业方面的二次开发,研制了煤矿水害多源信息预测系统。通过利用各种多源数据,对地震、电法、水文地质等进行处理后,在MAPGIS系统下进行生成专题图、配准、空间定量分析,最后建立预测模型。应用该系统对煤矿实际资料进行了处理,结果表明预测结果更为准确。     

浅析GIS空间数据不确定性概念模型

对空间数据不确定性的研究，大多数都是针对数据本身进行的，很少针对地理空间数据实际应用的不确定性展开研究，由于各种不确定性之间也常常是相互联系、相互影响，各种不确定性之间也存在很大的相关性。对地理空间数据的应用范围，以及在规定的应用范围内将产生怎样的应用结果进行不确定性评定，远比只研究地理空间数据本身的不确定性更为复杂。从目前GIS的空间数据不确定性所存在的问题出发．在介绍空间数据不确定性概念、形成的原因及一般的空间数据流程的基础上，对空间数据不确定性概念模型的建立及其模型进行了阐述，可以对空间数据不确定性的研究起到一定的借鉴作用。     

锆石SHRIMP年龄测定数据处理时系统偏差的避免——标准锆石分段校正的必要性

介绍了高分辨率、高灵敏度离子微探针质谱计（SHRIMP）锆石原位微区年龄测定中标准锆石的作用、测定方式、数据处理时产生系统偏差的原因及避免系统偏差的办法。以两组实际测定数据处理阐明标准锆石分段校正的可行性和有效性。     

Analysis of the Modes of Aggregation of Scientific Data and Proposals for its Development in China

Scientific data are strategic resources, and the aggregation of scientific data is an important method to seize the upstream and competitive highlands of scientific data. Notably, it is challenging to grasp the international situation and the scientific laws concerning the mode of scientific data aggregation; exploring the modes and methods of scientific data aggregation that are suitable for China's national conditions is also difficult. This paper investigated and analyzed the modes of scientific data aggregation both at home and abroad from the viewpoints of international organizations, international scientific programs, government agencies, and professional data centers. Five modes of scientific data aggregation were summarized, including scientific research projects converging to designated data centers/repositories, scientific research projects dispersing to data centers/repositories, individual scientists submitting datasets to data centers/repositories with published papers, scientific research projects/individual scientists sharing directories/networks, big data computing/processing platform, and citizen science models of open and public convergence. This paper analyzed each mode and the corresponding cases. On this basis, the paper put forward six suggestions for the reasonable aggregation of scientific data in China, including the implementation of the “Measurement of Scientific Data Management”, certification of data aggregation centers, scientific data collection and publishing in journals, construction of data aggregation networks, aggregation of international resources, and construction of the whole data aggregation chain.     

Using of gene expression programming and climatic data for forecasting flow discharge by considering trend,normality, and stationarity analysis

In this research, the main hydrological characteristics (such as trend, stationarity, and normalization of hydrological data) of the Kasilian watershed are considered from 1970 to 2009. For forecasting of discharge, gene expression programming (GEP) method is applied. Normality and stationarity of time series are necessary for application of GEP method. For this purpose, third edition of Mann-Kendall trend test and skewness test are used for detection of trend and normalization of data, respectively. Also, five methods are applied for detection of stationarity of data. Modified Mann-Kendall trend test and Theil and Sen’s median slope method illustrate that annual and monthly precipitation data have slight decreasing trend, annual and monthly discharge data have insignificant decreasing trend, and annual and monthly temperature data have an increasing trend. Skewness test illustrates that annual, monthly, and daily discharge and precipitation data are not normal. By using logarithm function, skewness is minimized and symmetry of data is improved. After normalization of time series by logarithm function, five methods are applied for testing of stationarity of time series. These methods show that different normalized time series are stationarity and stationarity of time series is improved by elimination of periodic properties of data. For forecasting of daily discharge by GEP method, 85% of data are used for training and 15% of data are used for testing. By using data of 3 days ago, the GEP has the best efficiency. Coefficient of correlation (CC), root mean square error (RMSE), mean absolute error (MAE), and mean absolute relative error (MARE) are 0.9, 0.495 lit/s, 0.288 lit/s, and 0.053, respectively.