Treffer: New implementation of OGC Web Processing Service in Python programming language. PyWPS-4 and issues we are facing with processing of large raster data using OGC WPS

Title:
New implementation of OGC Web Processing Service in Python programming language. PyWPS-4 and issues we are facing with processing of large raster data using OGC WPS
Source:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B7, Pp 927-930 (2016)
Publisher Information:
Copernicus Publications, 2016.
Publication Year:
2016
Collection:
LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Applied optics. Photonics
Document Type:
Fachzeitschrift article
File Description:
electronic resource
Language:
English
ISSN:
1682-1750
2194-9034
DOI:
10.5194/isprs-archives-XLI-B7-927-2016
Accession Number:
edsdoj.0f18b32f1604fa099b47bbfc67279f8
Database:
Directory of Open Access Journals

Weitere Informationen

The OGC® Web Processing Service (WPS) Interface Standard provides rules for standardizing inputs and outputs (requests and responses) for geospatial processing services, such as polygon overlay. The standard also defines how a client can request the execution of a process, and how the output from the process is handled. It defines an interface that facilitates publishing of geospatial processes and client discovery of processes and and binding to those processes into workflows. Data required by a WPS can be delivered across a network or they can be available at a server. PyWPS was one of the first implementations of OGC WPS on the server side. It is written in the Python programming language and it tries to connect to all existing tools for geospatial data analysis, available on the Python platform. During the last two years, the PyWPS development team has written a new version (called PyWPS-4) completely from scratch. The analysis of large raster datasets poses several technical issues in implementing the WPS standard. The data format has to be defined and validated on the server side and binary data have to be encoded using some numeric representation. Pulling raster data from remote servers introduces security risks, in addition, running several processes in parallel has to be possible, so that system resources are used efficiently while preserving security. Here we discuss these topics and illustrate some of the solutions adopted within the PyWPS implementation.