<?xml version="1.0" encoding="UTF-8"?><feed xmlns="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
<title>Umweltinformationssysteme 2015</title>
<link href="http://dl.gi.de/handle/20.500.12116/27685" rel="alternate"/>
<subtitle/>
<id>http://dl.gi.de/handle/20.500.12116/27685</id>
<updated>2026-07-23T21:38:54Z</updated>
<dc:date>2026-07-23T21:38:54Z</dc:date>
<entry>
<title>Suchmaschinen-getriebene Umweltportale – Nutzung einer ElasticSearch-Suchmaschine</title>
<link href="http://dl.gi.de/handle/20.500.12116/27706" rel="alternate"/>
<author>
<name>Schlachter, Thorsten</name>
</author>
<author>
<name>Düpmeier, Clemens</name>
</author>
<author>
<name>Schmitt, Christian</name>
</author>
<author>
<name>Schillinger, Wolfgang</name>
</author>
<id>http://dl.gi.de/handle/20.500.12116/27706</id>
<updated>2019-09-20T12:04:38Z</updated>
<published>2015-01-01T00:00:00Z</published>
<summary type="text">Suchmaschinen-getriebene Umweltportale – Nutzung einer ElasticSearch-Suchmaschine
Schlachter, Thorsten; Düpmeier, Clemens; Schmitt, Christian; Schillinger, Wolfgang
Hosenfeld, Friedhelm; Knetsch, Gerlinde; Zacharias, Uta
In order to merge data from different information systems in web portals, querying of this data has to be simple and with good performance. If no direct, high-performance query services are available, data access can be provided (and often accelerated) using external search indexes, which is well-proven for unstructured data by means of classical full text search engines. This article describes how structured data can be provided through search engines, too, and how this data then can be re-used by other applications, e.g., mobile apps or business applications, incidentally reducing their complexity and the number of required interfaces. Users of environmental portals and applications can benefit from an integrated view on unstructured as well as on structured data.
</summary>
<dc:date>2015-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Aus Groß mach Klein: Verarbeitung orchestrierter OGC Web Services mit RichWPS Server- und Client-Komponenten</title>
<link href="http://dl.gi.de/handle/20.500.12116/27704" rel="alternate"/>
<author>
<name>Wössner, Roman</name>
</author>
<author>
<name>Abecker, Andreas</name>
</author>
<author>
<name>Bensmann, Felix</name>
</author>
<author>
<name>Alcacer-Labrador, Dorian</name>
</author>
<author>
<name>Roosmann, Rainer</name>
</author>
<id>http://dl.gi.de/handle/20.500.12116/27704</id>
<updated>2019-09-20T12:04:37Z</updated>
<published>2015-01-01T00:00:00Z</published>
<summary type="text">Aus Groß mach Klein: Verarbeitung orchestrierter OGC Web Services mit RichWPS Server- und Client-Komponenten
Wössner, Roman; Abecker, Andreas; Bensmann, Felix; Alcacer-Labrador, Dorian; Roosmann, Rainer
Hosenfeld, Friedhelm; Knetsch, Gerlinde; Zacharias, Uta
RichWPS is a project aiming at more powerful and more user-friendly support for using the OGC Web Processing Services standard (WPS) for distributed geodata processing in the Web. While we have already discussed in other publications the RichWPS ModelBuilder for geoprocessing-workflow composition as well as the RichWPS approach to geoprocessing-workflow orchestration, this paper sketches the RichWPS Server software as well as some client-side developments facilitating the effective usage of WPS processes.
</summary>
<dc:date>2015-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Aus Klein mach Groß: Komposition von OGC Web Services mit dem RichWPS ModelBuilder</title>
<link href="http://dl.gi.de/handle/20.500.12116/27703" rel="alternate"/>
<author>
<name>Bensmann, Felix</name>
</author>
<author>
<name>Roosmann, Rainer</name>
</author>
<author>
<name>Kohlus, Jörn</name>
</author>
<id>http://dl.gi.de/handle/20.500.12116/27703</id>
<updated>2019-09-20T12:04:37Z</updated>
<published>2015-01-01T00:00:00Z</published>
<summary type="text">Aus Klein mach Groß: Komposition von OGC Web Services mit dem RichWPS ModelBuilder
Bensmann, Felix; Roosmann, Rainer; Kohlus, Jörn
Hosenfeld, Friedhelm; Knetsch, Gerlinde; Zacharias, Uta
Distributed geospatial data and services can be used to form Spatial Data Infra-structures (SDI). Current technological developments enable SDI to process large amounts of geospatial data. In this context, Web Processing Services (WPS) can be used as an open interface standard for accessing and executing geospatial processes. Since many SDI are based on Service-Oriented Architectures (SOA), the orchestration of services is enabled by composing existing services. The results are higher services, e.g. complex geospatial applications. The RichWPS research project focuses on analysing and providing practical approaches of web service orchestration. For this, software components are developed to build a modular orchestration environment. The main client-side application is the ModelBuilder.
</summary>
<dc:date>2015-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Erfahrungen mit MongoDB bei der Verwaltung meteorologischer Massendaten</title>
<link href="http://dl.gi.de/handle/20.500.12116/27702" rel="alternate"/>
<author>
<name>Lutz, Richard</name>
</author>
<id>http://dl.gi.de/handle/20.500.12116/27702</id>
<updated>2019-09-20T12:04:37Z</updated>
<published>2015-01-01T00:00:00Z</published>
<summary type="text">Erfahrungen mit MongoDB bei der Verwaltung meteorologischer Massendaten
Lutz, Richard
Hosenfeld, Friedhelm; Knetsch, Gerlinde; Zacharias, Uta
The remote sensing of atmospheric trace gases investigates dynamic, microphysical and chemical processes in the Earth?s atmosphere, with the goal to understand, quantify and predict its natural variability and long-term changes. Accurate measurements of atmospheric trace gases from various observational platforms (ground-based stations, air craft, balloons, satellites) provide the data that are required for the modelling of atmospheric processes. The instrument GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere), developed by KIT/IMK and FZ Jülich, an Infrared Spectrometer, which measures atmospheric emissions, was engaged in several measurement campaigns on board of HALO (High Altitude and Long Range Research Aircraft) and provided a large amount of data, which has to be managed efficiently for processing and visualisation. This paper describes the system background and the use of MongoDB for the provision of measured and processed mass data.
</summary>
<dc:date>2015-01-01T00:00:00Z</dc:date>
</entry>
</feed>
