DOCSLIB.ORG

OGC Standards for Raster Data Management

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
OGC Standards for Raster Data Management A Prototype Infrastructure for Sentinel Earth Observation Data Relative to Portugal Supporting OGC Standards for Raster Data Management Diogo Filipe Pimenta Andrade Thesis to obtain the Master of Science Degree in Information Systems and Computer Engineering Supervisor(s): Prof. Bruno Emanuel da Grac¸a Martins Prof. Mario´ Jorge Costa Gaspar da Silva Examinatiom Committee Chairperson: Prof. Daniel Jorge Viegas Gonc¸alves Supervisor: Prof. Prof. Bruno Emanuel da Grac¸a Martins Members of the Committe: Prof. Armanda Rodrigues May 2017 The only way to achieve the impossible is to believe it is possible. Charles Lutwidge Dodgson Acknowledgments I would like to thank those who have been present and have in a way or another contributed to this thesis. First, I would like to thank my advisors, Prof. Bruno Martins and Prof. Mario´ Gaspar, for all the guidance, patience, and support. I would also like to thank Eng. Bruno Anjos and Eng. Marco Silva from Instituto Portuguesˆ do Mar e da Atmosfera (IPMA) for the technical support. I also thank the future mother of my children, Barbara´ Agua,´ for always being kind and supportive. I can not thank her enough for all the encouragement and dedication. I thank my good friend Joao˜ Vieira, for the inspiration and motivation that brought me to pursue higher education. I would like to thank my brother, Joao˜ Andrade, for being the father that I never had. Finally, I would like to thank the taxpayers of Portugal for providing me with financial support, through a scholarship from Governo Regional da Madeira, through the SASUL scholarship, and through the researh grant from the Fundac¸ao˜ para a Cienciaˆ e Tecnologia (FCT) within project DataS- torm - EXCL/EEI-ESS/0257/2012. I also would like to express my gratitude to the Republica´ ”A Desordem dos Engenheiros”, for all the moments, for helping me to grow as a person, for being my second family, and for facilitating my life in an economic way. I will never forget and will be always grateful. iii Abstract This document describes an architecture for the IPSentinel infrastructure for managing Earth ob- servation data together with its implementation. This infrastructure was developed using the DHuS software from the European Space Agency together with the RasDaMan array database manage- ment system, to catalogue, disseminate and process Sentinel Earth observation products for the Portuguese territory. RasDaMan implements standards from the Open Geospatial Consortium, such as Web Coverage Service and Web Coverage Processing Service, which provide access and pro- cessing of the rasters encoding Earth observation data, through the Internet. The reported experiments show that the prototype system meets the functional requirements. This dissertation also provides measurements of the used computational resources, in terms of storage space and response times. Keywords Remote Sensing Products, Earth Observation Data, Raster Data, OGC Standards, Geospatial Data Infrastructures, Big Data Management v Resumo Este documento descreve a arquitectura e a implementac¸ao˜ de um prototipo´ da infraestrutura IP Sentinel para a gestao˜ de produtos de observac¸ao˜ da Terra. Esta infraestrutura foi desenvolvida usando o software DHuS da Agenciaˆ Espacial Europeia, juntamente com o sistema de gestao˜ de base de dados de arrays RasDaMan. Esta infraestrutura tem como objectivo catalogar, disseminar e processar produtos de observac¸ao˜ da Terra Sentinel relativos ao territorio´ Portugues.ˆ O RasDaMan implementa normas do Open Geospatial Consortium, tais como as normas Web Coverage Service and Web Coverage Processing Service, que disponibilizam o acesso e o processamento de rasters que codificam os dados de obvservac¸ao˜ da Terra, atraves´ da Internet. As experienciasˆ relizadas mostram que o prototipo´ cumpre os requisitos funcionais. Esta disserta- c¸ao˜ fornece tambem´ algumas medic¸oes˜ dos recursos computacionais utilizados, em termos do espac¸o de armazenamento e do tempo de resposta. Palavras Chave Detecc¸ao˜ Remota, Dados de Observac¸ao˜ da Terra, Dados Raster, Especificac¸oes˜ OGC, Infras- truturas para Dados Geoespaciais, Gestao˜ de Megadados vii Contents 1 Introduction 1 1.1 Thesis Proposal . .2 1.2 Summary of Contributions . .3 1.3 Document Organization . .3 2 Concepts and Related Work 5 2.1 Concepts . .6 2.1.1 The Sentinel Programme . .6 2.1.2 Computational Storage of EO Rasters . .7 2.1.3 Array Database Managing Services . .9 2.1.3.A Array Algebra . 10 2.1.4 Open Geospatial Consortium Standards . 11 2.1.4.A OGC Web Coverage Service . 13 2.1.4.B OGC Web Coverage Processing Service . 14 2.1.4.C OGC Web Map Service . 15 2.2 Related Work . 16 2.2.1 The ESA Data Hub Service . 17 2.2.2 The RasDaMan Array Database Management System . 21 2.2.3 The SciDB Array Database Management System . 23 2.2.4 Handing Raster data in MonetDB and the TELEIOS Infrastructure . 26 2.3 Summary and Discussion . 28 3 Prototype Infrastructure 31 3.1 Overview . 32 3.2 System Assumptions and Functional Requirements . 33 3.3 Architecture . 34 3.4 Implementation . 39 3.4.1 Integration of Petascope with the Data Hub Service (DHuS) software . 39 3.4.2 Modification of Petascope and DHuS Web Clients . 39 3.4.3 Modification of the DHuS Core to Automate the Process of Ingesting Coverages in RasDaMan . 41 3.5 Summary . 42 ix 4 Validation 45 4.1 Requirements Compliance . 46 4.2 Measurement of Required Computational Resources . 48 4.2.1 Storage Space . 48 4.2.2 Response Time . 49 4.3 Summary . 54 5 Conclusions and Future Work 57 5.1 Conclusions . 58 5.2 Future Work . 58 Bibliography 61 x List of Figures 2.1 The two GeoTIFF raster coordinate systems [Ritter and Ruth, 1997]. .7 2.2 The GeoTIFF raster, map, and world space [Ritter and Ruth, 1997]. .8 2.3 Example of GeoTIFF metadata parameter set [Ritter and Ruth, 1997]. .9 2.4 Constituents of an array. 10 2.5 Examples of 2D rectified (1 and 2) and referenceable (3 and 4) grids. 12 2.6 Dissemination of Earth Observation (EO) data from a centralised Data Hub. 17 2.7 Related view on the DHuS architecture centered around the Spring Framework [Fred´ eric´ Pi- dancier and Mbaye, 2014]. 18 2.8 The DHuS graphical user interface. 20 2.9 The DHuS service architecture [Fred´ eric´ Pidancier and Mbaye, 2014]. 21 2.10 RasDaMan infrastructure and its Petascope and SECORE components for exposing arrays through OGC web services. 23 2.11 Some SciQL array operations. 26 2.12 TELEIOS Infrascture Overview. 28 3.1 Major functionalities of the IPSentinel prototype. 32 3.2 Overview of interactions of the prototype with ESA SciHub and users. 34 3.3 Overview of the modified DHuS project. 35 3.4 Available APIs in the DHuS. 35 3.5 Component & connector allocated-to files view over the Tomcat and web applications. 36 3.6 IPSentinel context diagram. 36 3.7 Component & connector view from the DHuS core. 37 3.8 Component & connector view with pipe and filter style from the Rasdaman Feeder. 37 3.9 Petascope web client with GetMap tab open. 40 3.10 A product listed with Open Geospatial Consortium (OGC) services availability checked. 40 3.11 Product details screen displaying OGC service buttons. 41 3.12 Convention structure for the Sentinel1 products name . 42 3.13 Diagram of involved java classes in the implementation. 43 4.1 Result of executing a getCoverage of Sentinel 1 image with only VV band selected. 47 4.2 Result of executing a false colouring processing through the Web Coverage Processing Service (WCPS) query language. 47 xi 4.3 Result of executing multiples getMap requests. 47 4.4 Scenario 2: Regions selected by the 4 clients. 50 4.5 Results produced by the queries in the Table 4.8. 53 4.6 Result produced by the query in the Listing 4.7. 54 xii List of Tables 2.1 The parameters of a GetCapabilities request. 14 2.2 The parameters of a DescribeCoverage request. 15 2.3 The parameters of a GetCoverage request. 15 2.4 The parameters of a GetCapabilities request. 15 2.5 The parameters of a GetMap request. 16 2.6 Examples of operations supported by RasQL . 22 2.7 Two dimensional SciDB array. 24 2.8 The matrix stored as three BATs. 27 4.1 Space occupied by Sentinel 1 products on disk. 48 4.2 Space occupied by GRD type products in RasDaMan. 49 4.3 Storage space required for different rolling archive plans. 49 4.4 Scenario 1: Response time . 50 4.5 Scenario 2: Response time . 50 4.6 Scenario 3: Response time . 50 4.7 Resume of response times of the WCS operations. 51 4.8 Summary of response time from different queries. 52 xiii Abbreviations AFL Array Functional Language AQL Array Query Language BAT Binary Association Table DAOs Data Access Objects DBMS Database Management System DGT Direcc¸ao˜ Geral do Territorio´ DHuS Data Hub Service CRS Coordinate Reference Systems EO Earth Observation EPSG European Petroleum Survey Group ESA European Space Agency EW Extra Wide swath GIS Geographic Information Systems GML Geography Markup Language GRD Ground Range Detected GUI graphical user interface HSQLDB HyperSQL Database IPMA Instituto Portuguesˆ do Mar e da Atmosfera IW Interferometric Wide swath MDD multidimensional discrete data OData Open Data Protocol OGC Open Geospatial Consortium xv POM Project Object Model SLC Single Look Complex URL Uniform Resource Locator UTM Universal Transverse Mercator WAR Web application ARchive WCPS Web Coverage Processing Service WCS Web Coverage Service WMS Web Map Service xvi 1 Introduction Contents 1.1 Thesis Proposal . .2 1.2 Summary of Contributions . .3 1.3 Document Organization . ..
Load more

Recommended publications
  • Array Databases: Concepts, Standards, Implementations
    Baumann et al. J Big Data (2021) 8:28 https://doi.org/10.1186/s40537-020-00399-2 SURVEY PAPER Open Access Array databases: concepts, standards, implementations Peter Baumann , Dimitar Misev, Vlad Merticariu and Bang Pham Huu* *Correspondence: b. Abstract phamhuu@jacobs-university. Multi-dimensional arrays (also known as raster data or gridded data) play a key role in de Large-Scale Scientifc many, if not all science and engineering domains where they typically represent spatio- Information Systems temporal sensor, image, simulation output, or statistics “datacubes”. As classic database Research Group, Jacobs technology does not support arrays adequately, such data today are maintained University, Bremen, Germany mostly in silo solutions, with architectures that tend to erode and not keep up with the increasing requirements on performance and service quality. Array Database systems attempt to close this gap by providing declarative query support for fexible ad-hoc analytics on large n-D arrays, similar to what SQL ofers on set-oriented data, XQuery on hierarchical data, and SPARQL and CIPHER on graph data. Today, Petascale Array Database installations exist, employing massive parallelism and distributed processing. Hence, questions arise about technology and standards available, usability, and overall maturity. Several papers have compared models and formalisms, and benchmarks have been undertaken as well, typically comparing two systems against each other. While each of these represent valuable research to the best of our knowledge there is no comprehensive survey combining model, query language, architecture, and practical usability, and performance aspects. The size of this comparison diferentiates our study as well with 19 systems compared, four benchmarked to an extent and depth clearly exceeding previous papers in the feld; for example, subsetting tests were designed in a way that systems cannot be tuned to specifcally these queries.
    [Show full text]
  • Spatio-Temporal Retrieval with Rasdaman
    Spatio-Temporal Retrieval with RasDaMan Peter Baumann, Andreas Dehmel, Paula Furtado, Roland Ritsch, Norbert Widmann FORWISS (Bavarian Research Center for Knowledge-Based Systems) Orleansstr.34, D-81667 Munich, Germany Dial-up: voice +49-89-48095-207, fax - 203 E-Mail {baumann,dehmel,furtado,ritsch,widmann}@forwiss.de Abstract important research has been accomplished in several subfields. In practice, BLOBs still prevail in multimedia, while statistics and OLAP have developed their own Database support for multidimensional arrays is methods of MDD management. an area of growing importance; a variety of high- The RasDaMan array DBMS has been developed by volume applications such as spatio-temporal data FORWISS in the course of an international project partly management and statistics/OLAP become focus sponsored by the European Commission [Bau97]. The of academic and market interest. overall goal of RasDaMan is to provide classic database RasDaMan is a domain-independent array services in a domain-independent way on MDD database management system with server-based structures. Based on a formal algebraic framework query optimization and evaluation. The system is [Bau99], RasDaMan offers a query language [Bau98a], fully operational and being used in international which extends SQL-92 [ISO92] with declarative MDD projects. We will demonstrate spatio-temporal operators, and an ODMG 2.0 conformant programming retrieval using the rView visual query client. interface [Cat96]. Server-based query evaluation provides Examples will encompass 1-D time series, 2-D several optimization techniques and a specialized storage images, 3-D and 4-D voxel data. The real-life manager. The latter combines MDD tiling with spatial data sets used stem from life sciences, geo indexing and compression whereby an administration sciences, numerical simulation, and climate interface allows to change default strategies for research.
    [Show full text]
  • Web Coverage Service (WCS) V1.0.0
    Open Geospatial Consortium Inc. Date: 2005-10-14 Reference number of this OGC® Project Document: OGC 05-076 Version: 1.0.0 (Corrigendum) Category: OGC® Implementation Specification Editor: John D. Evans Web Coverage Service (WCS), Version 1.0.0 (Corrigendum) Copyright © 2005 Open Geospatial Consortium. All Rights Reserved To obtain additional rights of use, visit http://www.opengeospatial.org/legal/ Document type: OpenGIS® Implementation Specification Document subtype: Corrigendum Document stage: Approved Document language: English OGC 05-076 Contents Page 1 Scope........................................................................................................................1 2 Conformance............................................................................................................1 3 Normative references...............................................................................................1 4 Terms and definitions ..............................................................................................2 5 Conventions .............................................................................................................4 5.1 Symbols (and abbreviated terms) ............................................................................4 5.2 UML notation ..........................................................................................................4 5.3 XML schema notation..............................................................................................6 6 Basic service elements.............................................................................................6
    [Show full text]
  • An Array Database Approach for Earth Observation Data Management and Processing
    International Journal of Geo-Information Article An Array Database Approach for Earth Observation Data Management and Processing Zhenyu Tan 1, Peng Yue 2,3,* and Jianya Gong 2 1 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China; [email protected] 2 School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China; [email protected] 3 Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China * Correspondence: [email protected] Received: 2 June 2017; Accepted: 17 July 2017; Published: 19 July 2017 Abstract: Over the past few years, Earth Observation (EO) has been continuously generating much spatiotemporal data that serves for societies in resource surveillance, environment protection, and disaster prediction. The proliferation of EO data poses great challenges in current approaches for data management and processing. Nowadays, the Array Database technologies show great promise in managing and processing EO Big Data. This paper suggests storing and processing EO data as multidimensional arrays based on state-of-the-art array database technologies. A multidimensional spatiotemporal array model is proposed for EO data with specific strategies for mapping spatial coordinates to dimensional coordinates in the model transformation. It allows consistent query semantics in databases and improves the in-database computing by adopting unified array models in databases for EO data. Our approach is implemented as an extension to SciDB, an open-source array database. The test shows that it gains much better performance in the computation compared with traditional databases. A forest fire simulation study case is presented to demonstrate how the approach facilitates the EO data management and in-database computation.
    [Show full text]
  • Wcs-Core-2.0.1
    Open Geospatial Consortium Approval Date: 2012-07-10 Publication Date: 2012-07-12 External identifier of this OGC® document: http://www.opengis.net/doc/IS/wcs-core-2.0.1 Reference number of this Document: OGC 09-110r4 Version: 2.0.1 Category: OGC® Interface Standard Editor: Peter Baumann OGC® WCS 2.0 Interface Standard- Core: Corrigendum Copyright © 2012 Open Geospatial Consortium. To obtain additional rights of use, visit http://www.opengeospatial.org/legal/. Warning This document is an OGC Member approved corrigendum to existing OGC standard. This document is available on a royalty free, non-discriminatory basis. Recipients of this document are invited to submit, with their comments, notification of any relevant patent rights of which they are aware and to provide supporting documentation. Document type: OGC® Interface Standard Document subtype: Corrigendum Document stage: Approved for public release Document language: English OGC 09-110r4 License Agreement Permission is hereby granted by the Open Geospatial Consortium, ("Licensor"), free of charge and subject to the terms set forth below, to any person obtaining a copy of this Intellectual Property and any associated documentation, to deal in the Intellectual Property without restriction (except as set forth below), including without limitation the rights to implement, use, copy, modify, merge, publish, distribute, and/or sublicense copies of the Intellectual Property, and to permit persons to whom the Intellectual Property is furnished to do so, provided that all copyright notices on the intellectual property are retained intact and that each person to whom the Intellectual Property is furnished agrees to the terms of this Agreement.
    [Show full text]
  • IAC-18-F1.2.3 Page 1 of 9 IAC-18.B1.4.4X44924 Bigdatacube: Making Big Data a Commodity Dimitar Miševa*, Peter Baumanna
    69th International Astronautical Congress (IAC), Bremen, Germany, 1-5 October 2018. Copyright ©2018 by the International Astronautical Federation (IAF). All rights reserved. IAC-18.B1.4.4x44924 BigDataCube: Making Big Data a Commodity Dimitar Miševa*, Peter Baumanna, Vlad Merticariua, Dimitris Bellosb, Stefan Wiehlec a Department of Computer Science & Electrical Engineering, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany, {first name initial}.{last name}@jacobs-university.de b cloudeo AG, Ludwigstrasse 8, 80539 Munich, Germany, {first name initial}{last name}@cloudeo.group c Remote Sensing Technology Institute / SAR Signal Processing, German Aerospace Center (DLR), Henrich-Focke- Straße 4, 28199 Bremen, Germany, {first name}.{last name}@dlr.de * Corresponding Author Abstract The BigDataCube project aims at advancing the innovative datacube paradigm – i.e., analysis-ready spatio- temporal raster data – from the level of a scientific prototype to pre-commercial Earth Observation (EO) services. To this end, the European Datacube Engine (in database lingo: ‖Array Database System‖), rasdaman, will be installed on the public German Copernicus hub, CODE-DE, as well as in a commercial cloud environment to exemplarily offer analytics services and to federate both, thereby demonstrating an integrated public/private service. Started in January 2018 with a runtime of 18 months, BigDataCube will complement the batch-oriented Hadoop service already available on CODE-DE with rasdaman thereby offering important additional functionality, in particular a paradigm of ―any query, any time, on any size‖, strictly based on open geo standards and federated with other data centers. On this platform novel, specialized services can be established by third parties in a fast, flexible, and scalable manner.
    [Show full text]
  • GIS Glossary (PDF)
    GIS Glossary A AAT Arc attribute table. A table containing attributes for arc coverage features. In addition to user-defined attributes, the AAT contains the from and to nodes, the left and right polygons, the length, an internal sequence number and a feature identifier. See also feature attribute table. ACCESS directory The system directory that LIBRARIAN uses to store the files that manage access to the library. Each library has an ACCESS directory located in the library's DATABASE directory. accessibility An aggregate measure of how reachable locations are from a given location. The ACCESSIBILITY command computes values for accessibility as a function of the distance between locations and an empirically derived distance decay parameter. access rights The privileges accorded a user for reading, writing, deleting, updating and executing files on a disk. Access rights are stated as `no access', `read only' and `read/write'. ACODE file An INFO data file storing arc attributes for coverages created from TIGER, DIME, IGDS and Etak files. ACODE stands for `Arc CODE'. The ACODE file is related by Cover-ID to the Arc Attribute Table (AAT) of the coverage. address matching A mechanism for relating two files using address as the relate item. Geographic coordinates and attributes can be transferred from one address to the other. For example, a data file containing student addresses can be matched to a street coverage that contains addresses creating a point coverage of where the students live. ADS 1. Arc Digitizing System. A simple digitizing and editing system used to add arcs and label points to a coverage.
    [Show full text]
  • Web Coverage Service (WCS) V0.8.4
    Open Geospatial Consortium Inc. Date: 2003-08-27 Reference number of this OGC™ Project Document: OGC 03-065r6 Version: 1.0.0 Category: OpenGIS® Implementation Specification Editor: John D. Evans Web Coverage Service (WCS), Version 1.0.0 © OGC 2003 – All rights reserved i OGC 03-065r6 Copyright notice Copyright 2002, 2003, BAE SYSTEMS Mission Solutions Copyright 2002, 2003, CubeWerx Inc. Copyright 2002, 2003, George Mason University Copyright 2002, 2003, German Aerospace Center – DLR Copyright 2002, 2003, Intergraph Mapping and Geospatial Solutions Copyright 2002, 2003, IONIC SOFTWARE s.a. Copyright 2002, 2003, National Aeronautics and Space Administration (U.S.) Copyright 2002, 2003, Natural Resources Canada Copyright 2002, 2003, PCI Geomatics Copyright 2002, 2003, Polexis, Inc. The companies listed above have granted the Open Geospatial Consortium, Inc. (OGC) a nonexclusive, royalty-free, paid up, world- wide license to copy and distribute this document and to modify this document and distribute copies of the modified version. This document does not represent a commitment to implement any portion of this specification in any company’s products. OGC’s Legal, IPR and Copyright Statements are found at http://www.opengeospatial.org/about/?page=ipr&view=ipr_policy NOTICE Permission to use, copy, and distribute this document in any medium for any purpose and without fee or royalty is hereby granted, provided that you include the above list of copyright holders and the entire text of this NOTICE. We request that authorship attribution be provided in any software, documents, or other items or products that you create pursuant to the implementation of the contents of this document, or any portion thereof.
    [Show full text]
  • Glossary of Common Gis and Gps Terms
    United States Department of Agriculture NATURAL RESOURCES CONSERVATION SERVICE Cartographic and GIS Technical Note MT-1 (Rev. 1) August 2006 CARTOGRAPHIC AND GIS TECHNICAL NOTE GLOSSARY OF COMMON GIS AND GPS TERMS A almanac Information describing the orbit of each GPS satellite including clock corrections and atmospheric delay parameters. An almanac is used by a GPS receiver to facilitate rapid satellite acquisition. altitude Altitude is specified relative to either mean sea level (MSL) or an ellipsoid (HAE). Altitude above an ellipsoid is the distance from a precise mathematical model, whereas altitude above Mean Sea Level is a distance from a surface of gravitational equipotential that approximates the statistical average level of the sea. AML ARC Macro Language. A high-level algorithmic language for generating end-user applications. Features include the ability to create on-screen menus, use and assign variables, control statement execution, and get and use map or page unit coordinates. AML includes an extensive set of commands that can be used interactively or in AML programs (macros) as well as commands that report on the status of ARC/INFO environment settings. analysis The process of identifying a question or issue to be addressed, modeling the issue, investigating model results, interpreting the results, and possibly making a recommendation. annotation 1. Descriptive text used to label coverage features. It is used for display, not for analysis. 2. One of the feature classes in a coverage used to label other features. lnformation stored for annotation includes a text string, the location at which it is displayed, and a text symbol (color, font, size, etc.) for display.
    [Show full text]
  • Unidata Outreach Activities Focusing on Evolving Standards for Delivering Atmospheric Data Into the GIS Realm (Mainly OGC GALEON)
    Unidata Outreach Activities focusing on Evolving Standards for Delivering Atmospheric Data into the GIS Realm (mainly OGC GALEON) Ben Domenico, Unidata Stefano Nativi, CNR/IMAA Jeff Weber, Unidata With Input from the GALEON Team September 2009 Outreach Activities (Winding Down) • KNMI ADAGUC – Royal Dutch Meteorological Institute – Atmospheric Data Access for the GIS User Community • NSF NSDL: THREDDS 2G – Finished up last CU CIRES evaluation – THREDDS now part of Unidata core • NASA: Gateway to Oceans Land Air Collaboration with George Mason – OGC Standard CS-W search of TDS – Final report in press • NSF GEO: AccessData (formerly DLESE Data Services) – Final workshop was last June – Possible follow on evaluation activity Ongoing Outreach Activities (not the focus of this presentation) • NCAR GIS Program (official program of NCAR as of a couple months ago) • Marine Metadata Interoperability Project • IOOS DMAC Steering Team • CUAHSI Standing Committee • Oceans Interoperability Experiment sponsor • UCAR wide representative to OGC Technical Committee • AGU (and EGU) ESSI Focus Group • ESIN Journal Editorial Board • Liaison to OOI Cyberinfrastructure Project Working Together on A Mosaic for Atmospheric Data ThisThis presentationpresentation describesdescribes andand drawsdraws onon thethe work*work* ofof manymany collaboratingcollaborating individualsindividuals andand institutionsinstitutions * Unidata’s contribution supported by the U.S. National Science Foundation OstiaOstia AnticaAntica circacirca 77 BCBC Acronym Glossary • GALEON (Geo-interface
    [Show full text]
  • On the Integration of Array and Relational Models in Databases
    On the Integration of Array and Relational Models in Databases by Dimitar Miˇsev A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy in Computer Science Prof. Dr. Peter Baumann Jacobs University Bremen Prof. Dr. Michael Sedlmair Jacobs University Bremen Prof. Dr. Tore Risch Uppsala University Dr. Heinrich Stamerjohanns Jacobs University Bremen Date of defense: May 15th, 2018 Computer Science & Electrical Engineering Statutory Declaration Family Name, Given/First Name Miˇsev,Dimitar Matriculation number 20327580 Type of thesis PhD English: Declaration of Authorship I hereby declare that the thesis submitted was created and written solely by myself without any external support. Any sources, direct or indirect, are marked as such. I am aware of the fact that the contents of the thesis in digital form may be revised with regard to usage of unauthorized aid as well as whether the whole or parts of it may be identified as plagiarism. I do agree my work to be entered into a database for it to be compared with existing sources, where it will remain in order to enable further comparisons with future theses. This does not grant any rights of reproduction and usage, however. This document was neither presented to any other examination board nor has it been published. German: Erkl¨arung der Autorenschaft (Urheberschaft) Ich erkl¨arehiermit, dass die vorliegende Arbeit ohne fremde Hilfe ausschließlich von mir erstellt und geschrieben worden ist. Jedwede verwendeten Quellen, direkter oder indirekter Art, sind als solche kenntlich gemacht worden. Mir ist die Tatsache bewusst, dass der Inhalt der Thesis in digitaler Form gepr¨uftwerden kann im Hinblick darauf, ob es sich ganz oder in Teilen um ein Plagiat handelt.
    [Show full text]
  • Rasdaman Documentation Release 10.0.0
    rasdaman documentation Release 10.0.0 rasdaman team Oct 01, 2021 CONTENTS 1 Introduction3 1.1 Features......................................4 1.2 Rasdaman Application Domains.........................6 1.3 OGC geo standards support...........................7 1.4 How to Contribute................................7 2 Installation and Administration Guide9 2.1 Preface......................................9 2.2 Getting Started..................................9 2.3 Directories and Configuration Files....................... 38 2.4 rasdaman Architecture.............................. 42 2.5 Access Interfaces................................. 47 2.6 Server Administration.............................. 49 2.7 Security...................................... 65 2.8 Backup...................................... 65 2.9 Example Database and Programs........................ 66 2.10 Uninstall rasdaman................................ 68 2.11 Troubleshooting................................. 68 3 Contributing to Rasdaman 71 3.1 Development Contributions........................... 72 3.2 Documentation.................................. 72 3.3 Git resources................................... 77 3.4 C++ Guidelines.................................. 80 3.5 Adding Tests................................... 83 3.6 rasdaman Code Guide.............................. 100 3.7 Geo services................................... 120 4 Query Language Guide 129 4.1 Preface...................................... 129 4.2 Introduction................................... 129 4.3 Terminology..................................
    [Show full text]