Mercury: reusable metadata management, data discovery and access system

Mercury is a federated metadata harvesting, search and retrieval tool based on both open source packages and custom software developed at Oak Ridge National Laboratory (ORNL). It was originally developed for the National Aeronautics and Space Administration (NASA), and the consortium now includes funding from NASA, U.S. Geological Survey (USGS), and U.S. Department of Energy (DOE). Mercury is itself a reusable software application which uses a service-oriented architecture (SOA) approach to capturing and managing metadata in support of twelve Earth science projects. Mercury also supports the reuse of metadata by enabling searches across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces allows the users to perform simple, fielded, spatial, temporal and other hierarchical searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results (Table 1) to the user, while allowing data providers to advertise the availability of their data and yet maintain complete control and ownership of that data.     

LusTRE: a framework of linked environmental thesauri for metadata management

The paper illustrates a Linked Thesaurus Framework for the Environment, named LusTRE, to facilitate data sharing across different environmental disciplines. It provides a knowledge infrastructure of multilingual thesauri and code lists, interlinking them so that they can be used as one integrated linked data source. This multilingual thesaurus is published according to the Linked Data Best Practices and supports metadata compilation and data discovery for describing and finding Environmental geodata. A human readable web interface is provided for the exploitation of LusTRE as well as a set of web services for programmatic access to the knowledge infrastructure. LusTRE has been exploited within the European directive INSPIRE and SEIS piloting testbeds implemented within the EU project eENVplus in order to support cross-border and cross-domain data sharing. It is aimed at supporting multilingual data search and query refinement. In order to show how interlinked content can help users to more easily express metadata within Spatial Data Infrastructures (SDI), LusTRE web services have been integrated within existing metadata editors and geoportals.     

Rainwater harvesting: an option for sustainable rural water supply in Ghana

Potable water is a critical for improved health and for the pursuit of various socio-economic activities. Despite its immense usefulness, rural communities in developing countries such as Ghana lack adequate access to potable water. Rainwater harvesting, which has the potential of providing potable water for rural communities in Ghana and can be undertaken largely with local resources is rarely utilized. The purpose of this paper is to present rainwater harvesting as a sustainable water supply strategy for domestic use and is based on research undertaken in two rural communities in Ghana. The paper identifies opportunities such as affordability and user ownership as well as constraining bottlenecks that include poor roofing materials, lack of appropriate harvesting facilities and housing occupancy status as factors influencing rainwater harvesting practices by rural communities. It then proposes measures to resolve these and other difficulties associated with rainwater harvesting and thereby enhance its potential for sustainable rural water supply.     

A brave new (virtual) world: distributed searches, relevance scoring and facets

Our ability to deal with complex systems has improved through information system research which includes improved modeling (both data and system), the use of semantics and advances in distributed computing. The past decade has seen an explosion in the amount and variety of geosciences data and the emergence of true open data repositories through which scientists can freely access this data. Those data are found in thousands of repositories located around the world. Virtual observatories have been created to address the challenge of helping scientists search those repositories to find and access the required data. This challenge is been addressed by using technologies such as the Internet (with ample connectivity and bandwidth), the Web, cheap computing power, cheap storage and standards for critical components. Many scientific disciplines are developing virtual observatories. Yet some of the most compelling science questions cross multiple domains. While semantics can provide cross domain reasoning, often the first step in answering a question is determining what resources are available which may be relevant to a topic. The topic can be expressed as simple phrases or word sequences. Using a common relevance scoring method at all locations can enable a federated search across loosely coupled providers. The results of which can be organized into facets to aid the user in selecting the most promising resources with which to pursue the scientific investigation. We describe an approach to developing and deploying relevance scoring methods and faceted results in this brave new (virtual) world. We have found that a scoring method which considers both the presence of terms and the proximity of these terms relative to the order of the terms in the query improves the assessment of relevance. We call this Term Presence-Proximity (TPP) scoring and describe a method for calculating a normalized score. TPP scoring compares favorably with other scoring approaches.     

非标准化地质数据存储模式研究

地质数据中存在大量非标准化的数据,此类数据主要以MapGIS的数据格式存储.针对此类数据管理难、复用水平较低的现状,建立了以元数据服务器(MDS)为核心的数据存储模式,提出了弹性的迁移机制完成数据的重构,使用了动态数据驱动生成索引元数据框架,同时实现数据访问安全机制,用户授权等功能.此模式利用MDS (Metadata Server)实现对数据的管理、检索和调阅,这使散落在单机上的地质数据能够自主迁入空间数据仓库,实现统一管理,增强了数据的可复用性,     

Getting across information communities

Amazon’s deforestation affects citizens from varying information communities. Experts like scientists or journalists acquire relevant data on-site and publish valuable information on the Web. But different and sometimes conflicting views on reality impede sharing of information across communities, relevant content remains far too often undiscovered. We introduce rule-based semantic annotations as solution to facilitate the discovery and evaluation of geographical information. With the distinction between shared domain and local information source ontologies, the proposed architecture of a semantically supported SDI for the Amazon also takes the plethora of GI formats into account. Creating semantic annotations is challenging, a recommender system for semantic annotations enables even the non-IT experts to participate. The benefits of the proposed techniques are further illustrated by a scenario which spans across information communities of economics, ecology, and ethnology.     

Google Earth and Google Fusion Tables in support of time-critical collaboration: Mapping the deepwater horizon oil spill with the AVIRIS airborne spectrometer

Web interfaces have made remote sensing image resources more accessible and interactive. However, many web-based and Digital Earth opportunities for remote sensing have not yet been fully explored and could greatly facilitate scientific collaboration. In many cases, these resources can augment traditional proprietary software packages, which can have limited flexibility, spatiotemporal controls, and data synthesis abilities. In this paper, we discuss how web services and Google Earth were used for time-critical geovisualizations of the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Deepwater Horizon oil spill imaging campaign. In particular, we describe how (1) AVIRIS Google Earth products were used to visualize the spatial and temporal characteristics of the campaign’s image acquisitions, critically needed for flight planning, (2) the Google Fusion Table cloud-based service was applied to create a highly-interactive image archive and mapping display, and (3) the Google Fusion Table API was utilized to create a flexible PHP-based interface for metadata creation and as the basis for an interactive data catalog. Although there are other possible software and programming approaches to these activities, we highlight freely-accessible and flexible solutions and bring attention to the newly introduced Google Fusion Tables as a collaborative scientific platform.     

A framework for reading and unifying heliophysics time series data

We describe a framework designed to simplify the acquisition and integration of data from multiple, diversely formatted, geographically distributed science data sets. Our domain is Heliophysics where measurements of magnetic fields, plasmas, and charged particles are often made in-situ, with the data made available in relatively low volume data sets consisting of time series tables. Data format diversity has proven to be a significant barrier to the type of integrated, multi-mission analysis that is now very important in Heliophysics. Therefore we have developed a Java framework capable of reading, interpreting, and providing uniform access to the science content of any distributed time series data set. The framework exposes data only through fully abstract interfaces that represent data content while hiding all access details such as file format, data file granularity and access protocols. Furthermore, specialized interfaces for representing measurement-specific details are also employed, so that our framework enables data sets to be recast into scientifically interoperable representations. The context of our efforts is an increasingly distributed Heliophysics data environment that employs a collection of discipline-specific Virtual Observatories (VOs), each providing data search and retrieval services for one Heliophysics sub-discipline. Our framework is bundled in a library that ultimately will serve as a universal reader for Heliophysics data, solving the formats problem and serving as key infrastructure for advanced, science-sensitive data manipulation services.     

元数据标准及其在古生物数据库中的应用

元数据(Metadata)是关于数据的数据,元数据标准在数据共享中有重要的作用。目前,元数据已越来越为人们所重视,许多国家已经发布实施元数据内容标准,并开发了许多元数据操作工具。通过对国内外一些元数据标准的研究分析,阐述元数据的定义、作用、意义和标准化问题,并介绍各相关领域的元数据标准的主要内容,从而为制定古生物学元数据标准提供参考。     

基于XML的岩芯信息元数据标准研究与实践

目前岩芯信息表述尚没有统一的格式,严重阻碍了岩芯信息资源的利用,造成了资源浪费。为提高岩芯信息利用率,方便用户和其他软件共享岩芯信息,必须规范其组织、存储和交换数据格式,并提供相应的技术实现手段通过软件自动保存、解析岩芯信息。文章参照国内外相关资料及技术标准,创建了岩芯信息元数据标准,应用XML技术生成与元数据标准对应的XSD文件,并在应用程序中成功使用,当用户交互岩芯信息时,生成符合XSD格式要求的XML数据文件传送信息,不同用户可以正确解析岩芯信息。通过应用岩芯信息元数据标准,规范了数字化岩芯信息组织、存储和交换,采用XML技术由软件自动实现,大大提高了用户工作效率,方便了岩芯信息的共享,充分发挥了岩芯信息的价值。     

基于元数据的信息共享机制研究

元数据作为关于数据的数据,是目前信息共享的关键技术,也是当前研究的热点。在对比国际、国内元数据标准的基础上,采用元数据管理的三个层次:元数据子集、元数据实体和元数据元素,建立了“数字成都”元数据标准模板。它主要包括:标识信息、数据质量信息、空间参考信息、数据集的内容信息、分发信息、元数据参考信息。讨论了“数字成都”中基于元数据信息共享系统的结构、模块和特点,实现了分布式数据组织与管理、分布式数据共享、分布式数据快速索引机制以及跨平台数据访问。     

The multiple chronological techniques applied to the Lake Suigetsu SG06 sediment core,central Japan

The varved sediment of Lake Suigetsu (central Japan) provides a valuable opportunity to obtain high‐resolution, multi‐proxy palaeoenvironmental data across the last glacial/interglacial cycle. In order to maximize the potential of this archive, a well‐constrained chronology is required. This paper outlines the multiple geochronological techniques being applied – namely varve counting, radiocarbon dating, tephrochronology (including argon–argon dating) and optically stimulated luminescence (OSL) – and the approaches by which these techniques are being integrated to form a single, coherent, robust chronology. Importantly, we also describe here the linkage of the floating Lake Suigetsu (SG06) varve chronology and the absolute (IntCal09 tree‐ring) time scale, as derived using radiocarbon data from the uppermost (non‐varved) portion of the core. This tie‐point, defined as a distinct (flood) marker horizon in SG06 (event layer B‐07–08 at 1397.4 cm composite depth), is thus derived to be 11 255 to 11 222 IntCal09 cal. years BP (68.2% probability range).     

地学G4 I 系统中空间元数据的设计技术

地学G4 I 系统是以四学科( 地质学、地理学、地球化学及地球物理学) 地学数据集成为基础,以中大比例尺矿产资源评价为服务目标的计算机系统。由于跨学科地学空间数据集成涉及到众多技术,其中空间元数据的内容与应用构成本系统的重要组成部分。笔者就元数据的概念及元数据在本系统中的具体内容、作用、标准及研究现状等进行探讨,并针对本系统提出元数据管理子系统的设计框架。     

A case of man-induced ground subsidence and building settlement related to karstified gypsum (Oviedo,NW Spain)

Within the TERENO initiative, four terrestrial observatories, collecting huge amounts of environmental data, are being set up since 2008. To manage, describe, exchange and publish these data, the distributed Spatial Data Infrastructure TEODOOR (http://www.tereno.net) was created. Each institution responsible for an individual observatory sets up its own local data infrastructure, which may communicate with each other to exchange data and metadata internally or to the public by OGC compliant Web services. The TEODOOR data portal serves as a database node to provide scientists and decision makers with reliable and well-accessible data and data products. Various tools like hierarchical search or Web-GIS functions allow a deeper insight into the different observatories, test sites and sensor networks. Sensor data can be queried and selected for measured parameters, stations and/or time periods, and can be visualized and downloaded according to a shared TERENO data policy. Currently, TEODOOR provides free access to data from more than 500 monitoring stations.     

Integrated GIS and remote sensing analysis for landfill sitting in Western Crete,Greece

The assessment of the optimum landfill sitting requires multiple environmental data organized in a proper and efficient way to be effectively processed. Geographical information systems define an ideal tool for handling vast amounts of such kind of information combining multiple heterogeneous spatiotemporal data. Additionally, archive satellite remote sensing images set an ancillary approach to effective environmental monitoring of land surface within the areas of already established landfills and their surroundings (e.g. for calculation of crucial parameters such as vegetation indices). In this study, 17 environmental and anthropogenic factors were used to identify the most suitable sites for optimum landfill sitting in the western part of the island of Crete-Greece. The method used for the evaluation of all different factors is the analytical hierarchy process enhanced with fuzzy logic techniques. The results were compared with the already established landfills (legal/controlled and illegal/non-controlled) in the area of Chania prefecture and the results demonstrated that 75 % of the already (legal or illegal) established landfills of the prefecture are situated in extremely inappropriate areas from environmental point of view.     

VxOware: software for managing virtual observatory metadata

The recent Heliophysics Virtual Observatory (VxO) effort involves the development of separate observatories with a low overlap in physical domain or area of scientific specialization and a high degree of overlap in metadata management needs. VxOware is a content and metadata management system. While it is intended for use by a VxO specifically, it can also be used by any entity that manages structured metadata. VxOware has many features of a content management system and extensively uses the W3C recommendations for XML (Extensible Markup Language), XQuery (XML Query), and XSLT (Extensible Style Sheet Language Transformations). VxOware has features such as system and user administration, search, user-editable content, version tracking, and a wiki. Besides virtual observatories, the intended user-base of VxOware includes a group or an instrument team that has developed a directory structure of data files and would like to make this data, and its associated metadata, available in the virtual observatory network. One of the most powerful features of VxOware is the ability to link any type of object in the observatory to other objects and the ability for every object to be tagged.