Weaver

  • Workflow Execution Management Service (EMS)

  • Application, Deployment and Execution Service (ADES)

Weaver (the nest-builder)

Weaver birds build exquisite and elaborate nest structures that are a rival to any human feat of engineering. Some of these nests are the largest structures to be built by birds. (Eden).

Although weavers are named for their elaborately woven nests, some are notable for their selective parasitic nesting habits instead. (Wikipedia)

Weaver is an Execution Management Service (EMS) that allows the execution of workflows chaining various applications and Web Processing Services (WPS) inputs and outputs. Remote execution is deferred by the EMS to an Application Deployment and Execution Service (ADES), as defined by Common Workflow Language (CWL) configurations.

Weaver can be launched either as an EMS or an ADES according to configuration values it is deployed with. For more details, see Configuration section.

dependencies

Requires Python 3.6+ Requirements Status Dependencies Status

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releases

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Summary

Weaver is primarily an Execution Management Service (EMS) that allows the execution of workflows chaining various applications and Web Processing Services (WPS) inputs and outputs. Remote execution of each process in a workflow chain is dispatched by the EMS to one or many registered Application Deployment and Execution Service (ADES) by ensuring the transfer of files accordingly between instances when located across multiple remote locations.

Weaver can also accomplish the ADES role in order to perform application deployment at the data source using the application definition provided by Common Workflow Language (CWL) configuration. It can then directly execute a registered process execution with received inputs from a WPS request to expose output results for a following ADES in a EMS workflow execution chain.

Weaver extends the OGC API - Processes (WPS-REST bindings) by providing additional functionalities such as more detailed job log routes, adding more process management request options than required by the standard, and supporting remote providers to name a few. Because of this, not all features offered in Weaver are guaranteed to be applicable on other similarly behaving ADES and/or EMS instances. The reference specification is tracked to preserve the minimal conformance requirements and provide feedback to Open Geospatial Consortium (OGC) in this effect.

Weaver can be launched either as an EMS or an ADES according to configuration values it is deployed with. For more details, see Configuration and Documentation sections.

Configuration

All configuration settings can be overridden using a weaver.ini file that will be picked during instantiation of the application. An example of such file is provided here: weaver.ini.example.

Setting Weaver’s operational mode (EMS/ADES) is accomplished using the weaver.configuration field of weaver.ini.

For more configuration details, please refer to Documentation.

Documentation

The REST API documentation is auto-generated and served under any running Weaver application on route {WEAVER_URL}/api/. This documentation will correspond to the version of the executed Weaver application. For the latest documentation, you can refer to the OpenAPI Specification served directly on readthedocs.

More ample details about installation, configuration and usage are also provided on readthedocs. These are generated from corresponding information provided in docs source directory.

Extra Details & Sponsors

The project was initially developed upon OGC Testbed-14 – ESA Sponsored Threads – Exploitation Platform findings and following improvements. It is also advanced with sponsorship of U.S. Department of Energy to support common API of the Earth System Grid Federation (ESGF). The findings are reported on the OGC Testbed-14 thread, and more explicitly in the ADES & EMS Results and Best Practices Engineering Report.

The project has been employed for OGC Testbed-15 - ML Thread to demonstrate the use of Machine Learning interactions with OGC web standards in the context of natural resources applications. The advancements are reported through the OGC Testbed-15: Machine Learning Engineering Report.

Developments are continued in OGC Testbed-16 to improve methodologies in order to provide better interoperable geospatial data processing in the areas of Earth Observation Application Packages.

The project is furthermore developed through the Data Analytics for Canadian Climate Services (DACCS) initiative.

Weaver is a prototype implemented in Python with the Pyramid web framework. It is part of PAVICS and Birdhouse ecosystems.

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