中国西部环境与生态科学数据中心：面向西部环境与生态科学的数据集成与共享

国家自然科学基金委员会“中国西部环境与生态科学研究计划”自2001年启动以来,有力地推动了西部区域环境演化、陆地生态过程和人类活动对环境的影响等方面的研究,积累了丰富的基础数据。国家自然科学基金委员会“中国西部环境与生态科学数据中心”承担“西部计划”项目数据产出的收集、管理、集成,并面向西部环境与生态科学的各个领域提供科学数据服务。“西部数据中心”的总体框架是以“西部计划”和地球系统科学发展的科学需求为导向,建成以数据共享、知识积累、合作交流和数据科学为主要内容的集成平台,为“西部计划”多学科的交叉研究和成果的综合集成及地球科学发展的长远目标服务。以共建共享的指导思想集成针对西部环境与生态现状与变化的基础背景数据、环境与生态观测数据、模型数据集、数据工具及数据文档;并以完全与开放的数据共享原则为用户提供推送式数据服务。目前,“西部数据中心”已完成了数据共享平台、知识积累平台与合作交流平台的开发和集成,初步形成了科学数据平台,整理并发布了大量的西部环境生态科学所需的关键数据集。     

多维GIS矿产评价数据管理系统设计和实现

矿产资源评价需通过各种物探、化探、航空磁法、遥感、地质和实地调查资料综合分析以确定钻井孔位.针对多源、多时相、多尺度矿产资源勘探资料一体化管理和可视化分析,提出了一种基于分布式多维GIS模型的矿产资源评价数据管理方法.首先,分析了矿产资源预测评价数据资料特征,提出基于多维GIS模型的矿产资源评价数据管理模型;其次,提出了多源矿产资源评价数据处理策略,设计了一种全球瓦片金字塔模型的栅格和地形数据处理方法;再次,设计了分布式多维GIS矿产资源评价数据管理系统体系结构和功能模块,提出了双缓存性能优化方案;最后,开发实现了一个典型的矿产资源评价数据管理系统,实现了多达40种二维、三维数据、文档、多媒体等矿产资源评价数据一体化管理和可视化分析,可用于分布式矿产资源勘探评价的全球协同办公.     

防震减灾空间信息资源改造方案设计

本文简要介绍“数字福建”项目中防震减灾空间信息资源改造的设计方案     

Designing submission and workflow services for preserving interdisciplinary scientific data

Developments in information and communication technologies offer new opportunities to use and integrate scientific data that have been collected by researchers and scholars from diverse fields of inquiry. Data archives and digital repository systems are being developed to preserve current and legacy scientific data and technical information for use by others. However, capabilities are needed for data producers of various disciplines to easily and efficiently submit their data into archival systems for preservation. Analysis of digital preservation requirements has identified the requirements for services to support the submission and review of scientific data for preservation. Data submission and review processes are segmented into services, which are defined to support efficient preparation of scientific data for ingest into an archive or digital repository system. A model is proposed to inform the design of submission and workflow services for preserving interdisciplinary scientific data. Recommendations are offered for improving the design and evaluation of systems and services to prepare and preserve scientific data for new uses by interdisciplinary communities of users in the future. Improving the infrastructure that enables members of the scientific community to submit their data for archiving contributes to the scientific data stewardship and data curation capabilities needed to preserve scientific data for future generations of users.     

DOI for geoscience data - how early practices shape present perceptions

The first minting of Digital Object Identifiers (DOI) for research data happened in 2004 in the context of the project “Publication and citation of primary scientific data” (STD-DOI). Some of the concepts and perceptions about DOI for data today have their roots in the way this project implemented DOI for research data and the decisions made in those early days still shape the discussion about the use of persistent identifiers for research data today. This project also laid the foundation for a tighter integration of journal publications and data. Promoted by early adopters, such as PANGAEA, DOI registration for data has reached a high level of maturity and has become an integral part of scientific publishing. This paper discusses the fundamental concepts applied in the identification of DOI for research data and how these can be interpreted for alternative and future applications of persistent identifiers for research data.     

地震、测井和地质数据融合与实现

厚覆盖区地下地质模型所依靠的数据主要是地震和测井资料,但地震数据反映范围广而分辨率低,测井数据则分辨率高而反映范围小,如何有效地将两者组合利用,克服各自不足是论证的重点,说明了用数据树的形式组织所有井与地震地质等数据,并能同时生成和编辑多口井的合成地震记录,来确定不同井的深时关系,为把不同域的地震数据和测井数据融合显示建立基础,提供了实时修改子波的频率和相位来做合成记录的功能,也有反射系数与子波的分布褶积等最新的方法,以慢镜头的形式说明合成记录的形成过程。这些功能的应用,给用户确定正确的地下速度场提供了先进的手段,为地质模型建立提供了先进的方法。     

Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study

A critical prerequisite of risk prevention measures for natural hazards is from the results of forensic disaster investigations (FDIs). The current studies of the FDIs are limited by data issues including data availability and data reliability. The applications of crowdsourcing method in natural disasters indicate the potential to provide data support for the FDIs. However, there is very limited existing research on the use of crowdsourcing data for the FDIs. Following the requirements published by the Integrated Research on Disaster Risk program for FDIs, this paper establishes the process map for conducting the FDIs by scenario analysis approach with the crowdsourcing and crowdsensor data. Hurricane Harvey is used as the case study to implement the process map. The results show that the use of crowdsourcing data for the FDIs is feasible. Though this paper takes practical measures for improving the reliability of crowdsourcing data (i.e., little data size) in the case study, future research can focus on the development of advanced algorithm for the crowdsourcing data quality validation.     

地学数据产品的开发、发布与共享

数据是科学研究的基础,数据共享可以最大程度地发挥数据的使用价值,数据是实现数据共享最基本的要素。地学数据具有空间性、综合性、时间性、海量性、多源性等特点。属性数据、遥感数据、矢量数据是加工生产地学数据产品的重要数据源,属性数据空间化是加工、生产地学数据产品的重要技术手段。地学数据共享发布平台应当具备用户管理、数据目录查询、元数据管理、数据查询与浏览、数据下载等基本功能。推进科学数据共享,必须要有相应的政策措施保证,必须建立公正、合理的数据工作评价体系。     

面向知识服务的地质资料管理转型研究

针对传统地质资料服务方式单一、数据共享困难等问题,提出了地质资料管理的转型方案.对面向知识服务的地质资料知识组织方式、知识检索以及知识管理理念如何指导地质资料服务等方面进行了探讨.以地质数据本体构建、基于关联数据技术的地质资料语义化组织以及基于地质大数据的知识检索模型搭建为转型手段,介绍了促进地质资料转型升级的语义化描...     

地质大数据体系建设的总体框架研究

基于大数据、云计算等现代信息技术与理念,结合地质调查工作实际,系统论述了建设地质大数据体系的总体框架和实现的技术途径。提出了地质大数据体系建设的5项任务组成: 建设地质数据采集体系,推进地质数据快速规范采集; 建设地质大数据汇聚体系,实现地质数据快速有效汇聚; 建设地质数据与信息服务产品体系,丰富地质数据与信息社会化服务产品; 建设地质数据与信息服务体系,推进地质数据与信息协同服务; 建设地质大数据支撑平台(“地质云”),提升地质数据与信息服务的能力和水平。论述了5项任务的主要内容及其面临的关键技术问题,并简要提出了建设地质大数据体系对其他相关工作的影响和要求。     

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 fifferent 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 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.     

资料数据集成与服务研究——以整装勘查区地质工作为例

找矿突破战略行动是保障国家经济社会可持续发展、提高矿产资源保障能力的重大举措,而整装勘查工作则是实现找矿突破的重要途径。本文从地质资料管理的角度,结合整装勘查区找矿所需地质信息,提出了地质资料数据集成与服务整装勘查的技术与方法,即汇集整装勘查区的资料数据及分布图,对数据进行集成整合后制作成公开版数据,研发相应的资料管理与服务系统进行数据发布,便于地质工作者查询以往工作形成的资料。以整装勘查区地质工作为例的资料数据集成与服务研究工作是对地质资料产品开发的一次新尝试,这为今后地质资料产品开发提供了很好的参考和借鉴。     

数据预处理技术在地学大数据中应用

大数据时代随着数据的爆发式增长,在带来可供研究的海量数据的同时,也带来巨量的噪声和冗余数据。在地学领域,由于研究方向和技术方法手段的多样化,产生了数据量巨大和类型众多的地学数据集合。在地学信息的研究过程中,经常碰到地学信息孤岛,分图幅地学数据边界系统误差和地学文档的非结构化问题。在对地学数据进行信息的提取和挖掘之前,必须根据研究目的对地学大数据进行预处理,使冗余、复杂的大数据转为结构化、准确、可用的数据。本文以地学大数据的预处理技术为切入点,从地学数据交互标准与语义、数据调平、地质图接边和文本结构化等四个研究方面,分析阐述目前地学大数据挖掘方面存在的问题及主要的解决手段,同时也对多元数据融合在大数据中的应用进行了阐述。希望通过本文对地学大数据预处理技术的探讨,能对地学大数据的挖掘有所帮助。     

矿产资源潜力评价成果数据信息管理系统设计与实现

全国矿产资源潜力评价（2006-2013）工作历时8年,是建国以来规模最大的矿情调查工作之一,形成了海量（TB级）的成果数据。如何高效的管理该数据集,实现数据的广泛应用,成为数据共享服务的关键和难点。文章以全国矿产潜力评价成果数据为基础,运用GIS技术,分析了地质大数据存储管理、基于元数据的查询检索、空间数据可视化等关键技术,提出了一种针对海量、多源、异构的地质数据的统一管理思路。通过对成果数据的分析整理,构建元数据库作为存储不同类型数据的索引,完成数据的统一集成管理,同时实现数据的快速查询访问;借助强大成熟的Mapgis k9功能模块和开源的NASA World Wind三维数字地球引擎,进行二次开发,搭建适合于矿产资源潜力评价成果数据信息管理系统平台,为矿产资源潜力评价成果数据推广应用提供信息技术支撑,提高潜力评价数据的信息化服务能力。     

初论全国重要成矿区带基础数据库服务体系

全国重要成矿区带基础数据库服务体系分为技术服务和数据服务两大部分.在技术服务层面上,根据全国重要成矿区带基础数据的特点,划分了数据裁剪类型;利用2个长二进制字段分别存储图元信息和拓扑信息,解决了空间数据装入数据库中易造成数据丢失和格式转换信息缺失的难题;利用关系数据库和空间数据引擎解决了属性数据和空间数据一体化存储和联合查询难题.在数据服务层面上,指出采用WebGIS在线服务、目录服务和解说服务以及光盘邮寄服务相互结合、互相补充的方式,既可以很好地满足用户需求,又能保证数据的安全;并划分了数据类型和用户级别;提出了保护数据安全的策略.     

An architecture for consolidating multidimensional time-series data onto a common coordinate grid

Consolidating measurement data for use by data models or in inter-comparison studies frequently requires transforming the data onto a common grid. Standard methods for interpolating multidimensional data are often not appropriate for data with non-homogenous dimensionality, and are hard to implement in a consistent manner for different datastreams. These challenges are increased when dealing with the automated procedures necessary for use with continuous, operational datastreams. In this paper we introduce a method of applying a series of one-dimensional transformations to merge data onto a common grid, examine the challenges of ensuring consistent application of data consolidation methods, present a framework for addressing those challenges, and describe the implementation of such a framework for the Atmospheric Radiation Measurement (ARM) program.     

多源异构地质数据集成方法应用研究

大数据技术的高速发展为地质数据挖掘与分析带来了新的机遇。借鉴大数据技术的思想,提出了一种多源异构的地质数据集成方法,为数据挖掘、地质数据信息化服务提供了技术基础。针对北京周口店研究区,建立了其野外地质三维综合信息平台,将各类地表、地质体、地质信息等结构、半结构、非结构数据集成到统一的平台系统中,实现了研究区域相关地质数据的集成管理、可视化浏览、查询与分析,为大数据方法在地质领域的应用提供了新的思路。     

澳大利亚南极科学数据管理综述

系统概述了澳大利亚国家南极数据政策、组织机构、管理模式、实施策略与未来发展所面临的问题。在此基础上分析澳大利亚南极数据工作的发展与实效,并回顾了中国的极地数据管理工作,初步表明建立一个有效的组织框架是顺利开展数据管理与共享工作的基础,完全基于Web的数据管理与服务对科学项目的管理与研究成果的产出具有较大的促进作用。同时可以看出,国家层面的数据管理工作首先必须有明确的国家数据政策作引导;需要建立各种相应的数据标准与规范以及基于Web的数据管理、共享与服务平台;当然更离不开一支进行数据管理、服务与技术支持的专业队伍,并通过工作绩效评价系统对各个环节进行评价和考核。其中,为数据（集）编写完整、准确的元数据始终是数据管理中最重要的基础工作。     

岩溶水文地质环境地质信息管理系统构建与实现

为服务地质调查数据管理需求,基于GIS平台,构建了岩溶地区水文地质环境地质信息管理系统,按标准对调查数据、空间数据进行集成整合,实现了岩溶数据资料信息的数字化、可视化、动态化管理。其系统主要功能模块包括调查数据管理模块、空间数据管理模块、数据核查管理模块、钻孔柱状图管理模块、基础数据管理模块、系统数据管理模块。      

The Tau Model for Data Redundancy and Information Combination in Earth Sciences: Theory and Application

Many decision-making processes in the Earth sciences require the combination of multiple data originating from diverse sources. These data are often indirect and uncertain, and their combination would call for a probabilistic approach. These data are also partially redundant with each other or with all others taken jointly. This overlap in information arises due to a variety of reasons—because the data arises from the same geology, because they originate from the same location or the same measurement device, etc. The proposed tau model combines partially redundant data, each taking the form of a prior probability for the event being assessed to occur given that single datum. The parameters of that tau model measure the additional contribution brought by any single datum over that of all previously considered data; they are data sequence-dependent and also data value-dependent. Data redundancy depends on the sequence in which the data is considered and also on the data values themselves. However, for a given sequence, averaging the tau model parameters over all possible data values leads to exact analytical expressions and corresponding approximations and inference avenues. Information on multiple-point connectivity of permeability arrives from core data, well-test data and seismic data which are defined over varying supports with complex redundancy between these information sources. In order to compute these tau weights for determining connectivity, one needs a model of data redundancy, here expressed as a vectorial training image (Ti) constructed using a prior conceptual knowledge of geology and the physics of data measurement. From such a vectorial Ti, the tau weights can be computed exactly. Neglecting data redundancy leads to an over-compounding of individual data information and the possible risk of making extreme decisions.