An Introduction to Oracle's Location Technologies
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Concepts and Methods of Embedding Statistical Data Into Maps
International Journal of Scientific and Research Publications, Volume 8, Issue 5, May 2018 21 ISSN 2250-3153 Concepts and Methods of Embedding Statistical Data into Maps Mohammad Liton Hossain*, Dr.-Ing. Holger Meyer** * Computational Science and Engineering, University of Rostock, Germany **Faculty of Computer Science and Electrical Engineering, University of Rostock, Germany DOI: 10.29322/IJSRP.8.5.2018.p7706 http://dx.doi.org/10.29322/IJSRP.8.5.2018.p7706 Abstract- The main focus of this study is to find appropriate and geometries stored in Oracle Spatial and Graph, as well as stable solutions for representing the statistical data into map with GeoRaster data and data in the Oracle Spatial and Graph some special features. This research also includes the comparison topology and network data models. Oracle MapViewer is also an between different solutions for specific features. In this research I Open Geospatial Consortium (OGC)-compliant web map service have found three solutions using three different technologies (WMS) and web map tile service (WMTS) server [1]. namely Oracle MapViewer, QGIS and AnyMap which are different solutions with different specialties. Each solution has its own specialty so we can choose any solution for representing the statistical data into maps depending on our criteria’s. Index Terms- API, GIS, JDBC, NSDP, Oracle MapViewer, I. INTRODUCTION A map is a very powerful way to present data. It is much more intuitive than presenting the same data in the form of coordinates or text. Using the functionalities of spatial databases, along with other Middleware tools, such spatial applications can Figure 1: Basic flow of action in MapViewer [2] be developed that is capable to represent the statistical data into maps in various ways. -
A Survey of Geospatial Semantic Web for Cultural Heritage
heritage Review A Survey of Geospatial Semantic Web for Cultural Heritage Ikrom Nishanbaev 1,* , Erik Champion 1 and David A. McMeekin 2 1 School of Media, Creative Arts, and Social Inquiry, Curtin University, Perth, WA 6845, Australia; [email protected] 2 School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, Australia; [email protected] * Correspondence: [email protected] Received: 23 April 2019; Accepted: 16 May 2019; Published: 20 May 2019 Abstract: The amount of digital cultural heritage data produced by cultural heritage institutions is growing rapidly. Digital cultural heritage repositories have therefore become an efficient and effective way to disseminate and exploit digital cultural heritage data. However, many digital cultural heritage repositories worldwide share technical challenges such as data integration and interoperability among national and regional digital cultural heritage repositories. The result is dispersed and poorly-linked cultured heritage data, backed by non-standardized search interfaces, which thwart users’ attempts to contextualize information from distributed repositories. A recently introduced geospatial semantic web is being adopted by a great many new and existing digital cultural heritage repositories to overcome these challenges. However, no one has yet conducted a conceptual survey of the geospatial semantic web concepts for a cultural heritage audience. A conceptual survey of these concepts pertinent to the cultural heritage field is, therefore, needed. Such a survey equips cultural heritage professionals and practitioners with an overview of all the necessary tools, and free and open source semantic web and geospatial semantic web platforms that can be used to implement geospatial semantic web-based cultural heritage repositories. -
Oracle Spatial and Graph Data Sheet
ORACLE DATA SHEET ORACLE SPATIAL AND GRAPH ADVANCED SPATIAL AND GRAPH Oracle provides the industry’s leading spatial database management platform. DATA MANAGEMENT FOR THE Oracle Spatial and Graph option includes advanced features for spatial data ENTERPRISE and analysis as well as for physical, network and social graph applications. The KEY FEATURES geospatial data features support complex Geographic Information Systems Option to Oracle Database Enterprise Edition (GIS) applications, enterprise applications and location-based services 3-D data model, providing native support applications. The graph features include a network data model (NDM) graph to for 3-D geometries, surfaces and point model and analyze link-node graphs to represent physical and logical networks clouds. used in industries such as transportation and utilities. In addition, Oracle Support for OGC and ISO geospatial standards- Web Feature Service, Web Spatial and Graph includes support for RDF semantic graphs used in social Map Service, Web Catalog Service, networks and social interactions. Location Services GeoRaster support for imagery and Easily Location-Enable All Your Enterprise Applications and Processes raster data, including Java API Most business information has a location component, such as customer addresses, sales Geocoding and routing engines territories and physical assets. Businesses can take advantage of their geographic information Network Data Model Graph– a storage by incorporating location analysis and intelligence into their information systems. This allows model to represent graphs and networks in link and node tables organizations to make better decisions and respond to customers more effectively and reduce operational costs – increasing ROI and creating competitive advantage. RDF Semantic Graph Features – to represent graphs as triples in Oracle Database 11g includes native location capabilities and is a foundation for deploying compressed, partitioned tables enterprise-wide spatial information systems and location enabled e-business applications. -
Oracle® Spatial and Graph Map Visualization Developer's Guide
Oracle® Spatial and Graph Map Visualization Developer's Guide 19c E94797-03 February 2021 Oracle Spatial and Graph Map Visualization Developer's Guide, 19c E94797-03 Copyright © 2001, 2021, Oracle and/or its affiliates. Primary Author: Lavanya Jayapalan Contributors: Chuck Murray, L.J. Qian, Jayant Sharma, Honglei Zhu This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs) and Oracle computer documentation or other Oracle data delivered to or accessed by U.S. Government end users are "commercial computer software" -
Oracle Big Data Spatial and Graph Data Sheet Oracle Data Sheet
ORACLE DATA SHEET Oracle Big Data Spatial and Graph Oracle Big Data Spatial and Graph offers a set of analytic services and data models that support Big Data workloads on Apache Hadoop, Oracle NoSQL Database, and Spark technologies. For over a decade, Oracle has offered leading spatial and graph analytic technology for the Oracle Database. Oracle is now applying this expertise to work with social network data and to exploit Big Data architectures. Oracle Big Data Spatial and Graph has three components: a distributed property graph with 40 high-performance, parallel, in-memory analytic functions; a wide range of spatial analysis functions and services to evaluate data based on how near or far something is to one another, whether something falls within a boundary or region, or to process and visualize geospatial map data and imagery; and, a multimedia framework for processing video and image data in Apache Hadoop, such as facial recognition. Using the graph features, analysts can discover relationships and connections among customers, organizations, and assets. With the spatial capabilities, users can achieve insight into location-based patterns and trends across big data volumes, harnessing inherent location relationships in disparate data sources through harmonization and enrichment. KEY BUSINESS BENEFITS Graph Data Management and Analysis • Reduces the complexities of Hadoop Much of the Big Data generated these days contains inherent relationships development and time to implementation between the collected data objects. For example, important relationships and patterns are found in social network data from Facebook, a listener’s music • Commercial-grade spatial and graph algorithms enable deeper insights into preferences from an online music service like Spotify, online shopper behavior Big Data workloads on eBay, and bloggers and their relationship to followers and other bloggers. -
What's New with Oracle Spatial and Graph
What’s New with Oracle Spatial and Graph Matthew Perry, Ph.D. Consultant Member of Technical Staff Oracle Spatial and Graph September 2018 Copyright © 20182016,, Oracle and/or its affiliates. All rights reserved. | Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 3 Agenda 1 Introduction to Oracle Spatial and Graph 2 Core Database Features 3 Mid-tier Components and Tools 4 Summary and Thoughts on Standardization Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 4 Agenda 1 Introduction to Oracle Spatial and Graph 2 Core Database Features 3 Mid-tier Components and Tools 4 Summary and Thoughts on Standardization Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 5 A Little About our Team • First release of RDF Knowledge Graph was Oracle 10g R2 (2005) • Active in standards development – team members have been … • Member of W3C SPARQL 1.1 WG • Member of W3C RDF 1.1 WG • Co-editor of W3C OWL 2 Web Ontology Language Profiles spec. • Co-editor of W3C R2RML: RDB to RDF Mapping Language spec. • Co-editor of OGC GeoSPARQL spec. • Several research papers in this area • VLDB, ICDE, EDBT, ISWC, etc. -
Oracle Spatial and Graph Overview
1 Copyright © 2015, Oracle and/or its affiliates. All rights reserved. Oracle Spatial and Graph Graph Overview Bill Beauregard Senior Principal Product Manager Matt Perry Principal Member of Technical Staff 2 2 Agenda • Oracle’s Graph Database Strategy • Introduction to RDF Graph • Use Cases • Feature Overview & Performance • Summary 3 Copyright © 2015, Oracle and/or its affiliates. All rights reserved. 3 Oracle’s Graph Database Strategy Support Graph Data Types… …On all enterprise platforms § Oracle Database § Add graph analytics to applications, tools, § Cloudera with Apache Hadoop and information technology platforms § Oracle NoSQL Database § Deliver a scalable, secure, and high performing product § Oracle Big Data Appliance § Simplify development with integrated graph § Oracle Exadata Database analysis, APIs and services Machine § Oracle Cloud 4 Copyright © 2015, Oracle and/or its affiliates. All rights reserved. 4 3 Graph Models / 3 Domain Use Cases Use Case Graph Model Industry Domain Spatial Network Data Model § Logistics § Transportation Network • Network path analysis Analysis § Utilities • Multi-model modeling § Telcoms RDF Data Model Linked Data / § Life Sciences Semantic • Data federation § Finance Mediation • Knowledge representation § Publishing • Master Metadata Mgmt § Public Sector Property Graph Model § National Intelligence Social Network • Graph Search & Analysis § Public Safety Analysis • Big Data analytics § Social Media search • Entity analytics § Marketing - Sentiment 5 Copyright © 2015, Oracle and/or its affiliates. All rights reserved. 5 RDF Graph Use Cases • Unified content metadata Semantic for federated resources Metadata Layer • Validate semantic and structural consistency § Find related content & Text Mining & relations by navigating Entity Analytics connected entities § “Reason” across entities § Analyze social relations Social Media using curated metadata Analysis - Blogs, wikis, tweets, video - Calendars, IM, voice 6 Copyright © 2015, Oracle and/or its affiliates. -
RDF Semantic Graph Developer's Guide
Oracle® Spatial and Graph RDF Semantic Graph Developer's Guide 18c E84309-04 March 2019 Oracle Spatial and Graph RDF Semantic Graph Developer's Guide, 18c E84309-04 Copyright © 2005, 2019, Oracle and/or its affiliates. All rights reserved. Primary Author: Chuck Murray Contributors: Eugene Inseok Chong, Souri Das, Joao Paiva, Matt Perry, Jags Srinivasan, Seema Sundara, Zhe (Alan) Wu, Aravind Yalamanchi This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency- specific supplemental regulations. As such, use, duplication, disclosure, modification, and adaptation of the programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, shall be subject to license terms and license restrictions applicable to the programs. -
Spatial Analytics with Oracle Database 19C
Spatial Analytics with Oracle Database 19c Technical Feature Overview WHITE PAPER / NOVEMBER 26, 2019 TABLE OF CONTENTS Introduction .................................................................................................. 4 Spatial Features Overview ........................................................................... 6 Vector Performance Acceleration .................................................................... 6 Vector Geometry Functions ............................................................................. 6 Whole Earth Geometry Model for Geodetic Coordinate Support ...................... 7 Projections and Coordinate Systems ............................................................... 7 Spatial Aggregates .......................................................................................... 7 Linear Referencing Support ............................................................................. 7 3D Data Type Support ..................................................................................... 8 Parametric Curve Support ............................................................................... 8 Topology Data Model ...................................................................................... 8 GeoRaster Support ......................................................................................... 9 Spatial Analytic Functions ............................................................................. 12 Geocoding .................................................................................................... -
A Survey on Spatio-Temporal Data Analytics Systems
A Survey on Spatio-temporal Data Analytics Systems MD MAHBUB ALAM and LUIS TORGO, Dalhousie University, Canada ALBERT BIFET, The University of Waikato, New Zealand Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of research and development work has been done in the area of spatial and spatio- temporal data analytics in the past decade. The main goal of existing works was to develop algorithms and technologies to capture, store, manage, analyze, and visualize spatial or spatio-temporal data. The researchers have contributed either by adding spatio-temporal support with existing systems, by developing a new system from scratch for processing spatio-temporal data, or by implementing algorithms for mining spatio-temporal data. The existing ecosystem of spatial and spatio-temporal data analytics can be categorized into three groups, (1) spatial databases (SQL and NoSQL), (2) big spatio-temporal data processing infrastructures, and (3) programming languages and software tools for processing spatio-temporal data. Since existing surveys mostly investigated big data infrastructures for processing spatial data, this survey has explored the whole ecosystem of spatial and spatio-temporal analytics along with an up-to-date review of big spatial data processing systems. This survey also portrays the importance and future of spatial and spatio-temporal data analytics. CCS Concepts: • General and reference ! Surveys and overviews; • Information systems ! Spatial- temporal systems; Parallel and distributed DBMSs. Additional Key Words and Phrases: spatial databases, spatial NoSQL, big spatial data, spatio-temporal data, trajectory data, spatial data stream, GIS software, spatial libraries ACM Reference Format: Md Mahbub Alam, Luis Torgo, and Albert Bifet. -
Oracle Spatial and Graph Georaster
Oracle Spatial and Graph GeoRaster ORACLE WHITE PAPER | NOVEMBER 2016 Disclaimer The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle. ORACLE SPATIAL AND GRAPH GEORASTER Table of Contents Disclaimer 1 Introduction 1 Architecture 3 Data Model 5 GeoRaster Object 6 Features of GeoRaster 8 Database Creation 8 Database Administration 9 Basic Data Manipulation 9 Raster Algebra and Analytics 10 Image Processing and Serving 11 GeoRaster Features in Oracle Database 12c Release 1 (12.1) 12 New Features in Oracle Database 12c Release 2 (12.2) on Oracle Cloud 13 Benefits of Managing Raster Data in Oracle Database 14 Conclusion 15 ORACLE SPATIAL AND GRAPH GEORASTER Introduction GeoRaster is a feature of Oracle Spatial and Graph that lets you store, index, query, process, analyze, and serve georeferenced raster image and gridded data and its associated metadata. It provides native data types and an object-relational schema to store and manage multidimensional array, grid layers and digital images that can be referenced to positions on the Earth's surface or in a local coordinate system. What differentiates GeoRaster is the ability to perform raster analysis on extremely large images and data sets, provide in-place image processing and analysis with no development required, and provide parallelized image processing with simple invocation of PL/SQL procedures. -
Oracle Spatial and Graph Agenda
Oracle Spatial and Graph Agenda . Introducing Oracle Spatial and Graph . Goals for Spatial Features in 12c . New Spatial and NDM Graph Features in 12c . Goals for RDF Graph Features in 12c . New RDF Graph Features in 12c . Unique advantages using Exadata 2 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Oracle Spatial and Graph option “Lines” “Points” “Polygons” Web Services Geocoding (OGC) Routing SPARQL End Point Inferencing e1 f1 e3 e2 n2 Rasters n1 f2 3D e4 Network Graphs Topologies RDF Semantic Graphs 3 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Oracle’s Spatial Technologies – Oracle Locator: Feature of Oracle Database XE, SE, EE – Oracle Spatial: Priced option to Oracle HTTP Database EE Oracle Fusion Middleware – MapViewer: Java application and map rendering feature of Oracle Fusion Middleware MapViewer – Workspace Manager: Long transactions feature of Oracle Database SE, EE JDBC – Bundled Map Content: Major roads, administrative boundaries (city, county, state, Oracle Database country) - worldwide coverage from Navteq Locator Spatial and Graph Bundled Map Content 4 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. INTRODUCING 5 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Why rename this Oracle Database option From “Oracle Spatial” to “Oracle Spatial and Graph” • Highlights existing graph capabilities in Oracle Spatial – W3C RDF graph since Oracle 10gR2 – Network Data Model graph since Oracle 10gR1 • Addresses increasing market demand for graph database capabilities – Social Network Graph database popularity – Multimodal and integrated transportation, utility and communications networks 6 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Spatial Features 7 Copyright © 2013, Oracle and/or its affiliates.