Components

The main components of GrimoireLab are:

  • Perceval. Includes components for retrieving data from data sources. All components provide an uniform API for accessing their data sources, based on Python generators and data dictionaries (JSON documents).
  • Arthur. Organizes the data retrieval from large collections of repositories of different kinds, providing a uniform API to all of them, and to the different retrieval jobs running in any moment.
  • GrimoireELK. Collects data retrieved by Arthur, or directly by Perceval, and stores it in ElasticSearch indexes (raw indexes). It also organizes and transforms those raw indexes into other ElasticSearch indexes (enriched indexes), more suitable for visualization or reporting.
  • SortingHat. Manages identities for persons, including capabilities for merging the many identities corresponding to the same person, and other data related to them (such as affiliation to companies).
  • Kibiter. Visualization platform. It is a soft fork of Kibana, which allows for the construction of actionable dashboards to show the data in enriched indexes.
  • Panels. Definition of Kibiter dashboards. They encode the panels, visualizations and other details needed to produce dashboards in Kibiter or Kibana.
  • Reports. Production of PDF documents reporting on the main characteristics of a project.
  • Mordred. Manages the configuration of all the components needed to produce a dashboard, automating its production.

In the figure above, GrimoireLab components are represented in the pale green box. Bold arrows show the main data flow: from data sources to Perceval (which retrieves them), to Arthur (which schedules retrieval batches and stores results in Reddis), to GrimoireELK (which stores retrieved items as raw indexes, and then uses them to produce enriched indexes, both in ElasticSearch), to Reports (to produce specialized reports) or Kibiter (to visualize in actionable dashboards).

GrimoireELK uses SortingHat to store all the identities it founds in a MariaDB database. SortingHat uses lists of known identifiers (usually maintained in configuration files) and heuristics to merge identities corresponding to the same person, and related information (such as affiliation).

All the process is configured and orchestrated by Mordred, which uses its own configuration about, for example, which data sources to use.

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