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  4. Generic schema descriptions for comma-separated values files of environmental data
 
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2018
Conference Paper
Title

Generic schema descriptions for comma-separated values files of environmental data

Abstract
Comma-Separated Values (CSV) files are commonly used to publish data about environmental phenomena and environmental sensor measurements. Due to its simplicity, this format has many advantages. However, at the same time there is no official standard for CSV and no possibility to specify schematic constraints or other metadata. As a result, CSV files come in many variations and often with no metadata that would support interpretation or further processing, analysis and visualization. In this paper, we propose a framework for the specification of schema descriptions for CSV files as they are used in the environmental sciences. It allows to constrain the structure and content of a CSV file and also to specify relations between files, for example when they are published in one data package. The framework is extensible, also to other spatial data formats such as GeoTiff. The schema descriptions are encoded in JSON or XML to be published in the Web as a supplement to the data. It comes as a lightweight solution that provides metadata required to publish OGC compliant services from CSV files. It helps to overcome the heterogeneities of different data providers when exchanging environmental measurement data on the Web.
Author(s)
Mäs, Stephan
TU Dresden
Henzen, Daniel
TU Dresden
Bernard, Lars
TU Dresden
Müller, Matthias
TU Dresden
Jirka, Simon
52°North GmbH
Senner, Ivo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
21th AGILE International Conference on Geographic Information Science 2018. Proceedings. Online resource  
Conference
International Conference on Geographic Information Science 2018  
Link
Link
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Lead Topic: Visual Computing as a Service

  • Research Line: Modeling (MOD)

  • geographic information systems (GIS)

  • environmental data

  • metadata

  • data integration

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