Abstract
Until now, geometry information for the detector description of the ATLAS experiment was only defined in C++ code, stored in online relational databases integrated into the experiment’s frameworks or described in files with text-based markup languages. In all cases, to build and use the complete detector geometry, a full software stack was needed. In this paper, we present a new and scalable mechanism to store the geometry data and to query and serve the detector description data through a web interface and a REST API. This new approach decouples the geometry information from the experiment’s framework. Moreover, it provides new functionalities to users, who can now search for specific volumes and get partial detector description, or filter geometry data based on custom criteria. We present two approaches to build a REST API to serve geometry data, based on two different technologies used in other fields and communities: The graph database Neo4j and the search engine ElasticSearch. We describe their characteristics, and we compare them in a HEP context.
Highlights
Every modern particle physics experiment is based on a sophisticated particle detector, usually composed of many different sub-detectors, each of them targeting a specific measurement
Geometry information for the detector description of the ATLAS experiment was only defined in C++ code, stored in online relational databases integrated into the experiment’s frameworks or described in files with text-based markup languages
We present two approaches to build a REST API to serve geometry data, based on two different technologies used in other fields and communities: The graph database Neo4j and the search engine ElasticSearch
Summary
Every modern particle physics experiment is based on a sophisticated particle detector, usually composed of many different sub-detectors, each of them targeting a specific measurement. Geometry information for the detector description of the ATLAS experiment was only defined in C++ code, stored in online relational databases integrated into the experiment’s frameworks or described in files with text-based markup languages.
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