
doi: 10.5281/zenodo.12653484 , 10.5281/zenodo.14755407 , 10.5281/zenodo.14998397 , 10.5281/zenodo.17569607 , 10.5281/zenodo.12653483 , 10.5281/zenodo.15827235 , 10.5281/zenodo.15113302 , 10.5281/zenodo.13239266 , 10.5281/zenodo.15827317 , 10.5281/zenodo.17035768 , 10.5281/zenodo.15079654 , 10.5281/zenodo.15260518 , 10.5281/zenodo.15260505
doi: 10.5281/zenodo.12653484 , 10.5281/zenodo.14755407 , 10.5281/zenodo.14998397 , 10.5281/zenodo.17569607 , 10.5281/zenodo.12653483 , 10.5281/zenodo.15827235 , 10.5281/zenodo.15113302 , 10.5281/zenodo.13239266 , 10.5281/zenodo.15827317 , 10.5281/zenodo.17035768 , 10.5281/zenodo.15079654 , 10.5281/zenodo.15260518 , 10.5281/zenodo.15260505
AUDITOR is short for AccoUnting Data handlIng Toolbox for Opportunistic Resources. It allows one to flexibly build accounting pipelines for various use cases and environments. AUDITOR sits at the core of the pipeline as the provider of the storage for the accounting records. Via a REST interface, records can be pushed into or pulled from AUDITOR. Collectors are used to collect accounting data form a source and push it to AUDITOR, while plugins pull data from AUDITOR for further processing. Plugins and collectors are problem- and environment-specific and can be combined as needed. A Python library handles the interaction with AUDITOR and as such enables quick and easy development of collectors and plugins.
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
