The task of downloading comprehensive datasets of event-based seismic waveforms has been made easier through the development of standardised web services, but is still highly non-trivial, as the likelihood of temporary network failures or even worse subtle data errors naturally increase when the amount of requested data is in the order of millions of relatively short segments. This is even more challenging as the typical workflow is not restricted to a single massive download but consists of fetching all possible available input data (e.g., with several repeated download executions) for a processing stage producing any desired user-defined output. Here, we present stream2segment, a highly customisable Python 2+3 package helping the user through the whole workflow of downloading, inspecting and processing event-based seismic data by means of a relational database management system as archiving storage, which has clear performance and usability advantages. Stream2segment provides an integrated processing implementation able to produce any kind of user-defined output based on a configuration file and a user-defined Python function. Stream2segment can also produce diagnostic maps or user-defined plots which, unlike existing tools, do not require external software dependencies and are not static images but interactive browser-based applications ideally suited for data inspection or annotation tasks.
Physical samples (or specimen or artefacts) represent the origin of research results in many scientific disciplines. Assigning persistent identifier (PID) to samples is a fundamental step to make them discoverable and traceable in unambiguous way over the Web. The International Generic Sample Number (IGSN) is a PID for physical samples and connecting these with their online description following a dedicated metadata schema.
Sample descriptions of samples are available in various formats and detail. In order to publish them in a standardized manner and to automate and standardize the preparation and processing, the software product SAMIRA (Sample IGSN Registration Automation) was created as part of the Project FAIR WISH, funded by the Helmholtz Metadata Collaboration (HMC).
SAMIRA aims to automate the generation of Metadata XML-Files for the Registration of PIDs from different input sources (e.g. the FAIR Samples Template, Wiezcorek et al., 2023). This first version of SAMIRA implements the creation of IGSN metadata and Datacite metadata and the respective registration.