GeOxygene: Built on Top of the Expertise of the French NMA to Host and Share Advanced GI Science Research Results

Bucher, Bénédicte; Brasebin, Mickaël; Buard, Elodie; Grosso, Eric; Mustière, Sébastien; Perret, Julien

doi:10.1007/978-3-642-10595-1_2

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…Differences in position were then computed on each pair of homologous objects. A specific application has been implemented in Java, based on the GeOxygene library (Bucher et al. 2010).…”

Section: Quality Assessment Of French Openstreetmap Datamentioning

confidence: 99%

Quality Assessment of the French OpenStreetMap Dataset

Girres¹,

Touya²

2010

Transactions in GIS

556

495

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The concept of Volunteered Geographic Information (VGI) has recently emerged from the new Web 2.0 technologies. The OpenStreetMap project is currently the most significant example of a system based on VGI. It aims at producing free vector geographic databases using contributions from Internet users. Spatial data quality becomes a key consideration in this context of freely downloadable geographic databases. This article studies the quality of French OpenStreetMap data. It extends the work of Haklay to France, provides a larger set of spatial data quality element assessments (i.e. geometric, attribute, semantic and temporal accuracy, logical consistency, completeness, lineage, and usage), and uses different methods of quality control. The outcome of the study raises questions such as the heterogeneity of processes, scales of production, and the compliance to standardized and accepted specifications. In order to improve data quality, a balance has to be struck between the contributors' freedom and their respect of specifications. The development of appropriate solutions to provide this balance is an important research issue in the domain of user-generated content.

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“…Differences in position were then computed on each pair of homologous objects. A specific application has been implemented in Java, based on the GeOxygene library (Bucher et al. 2010).…”

Section: Quality Assessment Of French Openstreetmap Datamentioning

confidence: 99%

Quality Assessment of the French OpenStreetMap Dataset

Girres¹,

Touya²

2010

Transactions in GIS

556

495

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“…The CartAGen platform is a GIS library focused on map generalization, but it was not completely built from scratch. It is built upon the GeOxygene Java library 2 (Bucher et al, 2012), which implements OGC/ISO specifications and contains advanced GIS capabilities for research, such as data matching, conflation or data quality assessment. It is also based on very common open source Java libraries, such as JTS 3 for geometry computing, or GeoTools 4 for handling GIS files and coordinate systems.…”

Section: Platform Architecturementioning

confidence: 99%

“…CartAGen can be combined with the data matching capabilities of GeOxygene, which provides implementations of several matching techniques (Bucher et al, 2012). Common requirements: a) Platform/environment independent research: not really, not really but it is possible to access to CartAGen algorithms using a QGIS plugin.…”

Section: D) Matching Features From Multi-scale Datasetsmentioning

confidence: 99%

CartAGen: an Open Source Research Platform for Map Generalization

Touya¹,

Lokhat²,

Duchêne³

2019

Proc. Int. Cartogr. Assoc.

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<p><strong>Abstract.</strong> Automatic map generalization is a complex task that is still a research problem and requires the development of research prototypes before being usable in productive map processes. In the meantime, reproducible research principles are becoming a standard. Publishing reproducible research means that researchers share their code and their data so that other researchers might be able to reproduce the published experiments, in order to check them, extend them, or compare them to their own experiments. Open source software is a key tool to share code and software, and CartAGen is the first open source research platform that tackles the overall map generalization problem: not only the building blocks that are generalization algorithms, but also methods to chain them, and spatial analysis tools necessary for data enrichment. This paper presents the CartAGen platform, its architecture and its components. The main component of the platform is the implementation of several multi-agent based models of the literature such as AGENT, CartACom, GAEL, CollaGen, or DIOGEN. The paper also explains and discusses different ways, as a researcher, to use or to contribute to CartAGen.</p>

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“…The major part of the experiments was conducted on CartAGen (Renard, Gaffuri and Duchêne 2010), that is the module dedicated to generalization in the open source GeOxygene Java platform (Bucher et al 2012). For the sake of simplicity, we distributed the processes of CartAGen using the Java Parallel Processing Framework (JPPF), which only requires minimum refactoring of the code to distribute Java software.…”

Section: Case Studymentioning

confidence: 99%

Experiments to Distribute and Parallelize Map Generalization Processes

Touya

Berli

Lokhat

et al. 2017

The Cartographic Journal

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Automatic map generalization requires the use of computationally intensive processes often unable to deal with large datasets. Distributing the generalization process is the only way to make them scalable and usable in practice. But map generalization is a highly contextual process, and the surroundings of a generalized map feature needs to be known to generalize the feature, which is a problem as distribution might partition the dataset and parallelize the processing of each part. This paper proposes experiments to evaluate the past propositions to distribute map generalization, and to identify the main remaining issues. The past propositions to distribute map generalization are first discussed, and then the experiment hypotheses and apparatus are described. The experiments confirmed that regular partitioning was the quickest strategy, but also the less effective in taking context into account. The geographical partitioning, though less effective for now, is quite promising regarding the quality of the results as it better integrates the geographical context.

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GeOxygene: Built on Top of the Expertise of the French NMA to Host and Share Advanced GI Science Research Results

Cited by 9 publications

References 5 publications

Quality Assessment of the French OpenStreetMap Dataset

Quality Assessment of the French OpenStreetMap Dataset

CartAGen: an Open Source Research Platform for Map Generalization

Experiments to Distribute and Parallelize Map Generalization Processes

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