{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/4"}],"enrichment":{"capability":"Provides a pragmatic data model and validation toolkit for entities in investigative reporting and financial crime research\u2014people, companies, assets, payments, ownership relations, court cases\u2014with CLI tools for data transformation and mapping.","skillfed_tags":["financial-crime","investigative-data","entity-modeling"],"use_cases":["Build a database of corporate ownership networks and beneficial ownership chains for anti-corruption investigations.","Normalize and validate entity records (names, addresses, identifiers) from multiple sources before merging into a single dataset.","Transform spreadsheet or CSV data into a standardized entity-relationship model for compliance reporting.","Generate RDF/OWL exports of financial crime data for semantic web tools and linked-data applications.","Map court case records, sanctions lists, and payment flows into a unified schema for cross-domain analysis."],"what_it_does":"followthemoney is a data model and toolkit designed for investigators, journalists, and compliance researchers working with financial crime and anti-corruption data. Rather than aiming for an ideal theoretical model, it prioritizes practical usability by simplifying complex legal concepts into a working structure for efficient data processing. The package defines schemas for common entities (people, companies, assets, payments, ownership relations, court cases) and provides validation and normalization code to ensure data quality.\n\nBeyond the schema itself, followthemoney includes a command-line tool for processing and transforming data, mapping from tabular formats into the model, and generating RDF/OWL representations. It integrates with established libraries like SQLAlchemy, Pydantic, RDFlib, and NetworkX to support both relational and graph-based workflows. The project maintains active documentation and an explorer for schema definitions, making it suitable for teams building investigative data pipelines.","worth_installing":"Yes. followthemoney is actively maintained, has no known vulnerabilities, and solves a specific and well-defined problem for investigative and compliance workflows. The permissive MIT license poses no restrictions. Install friction is low and dependencies are mature. It is worth installing if you are building a data pipeline for financial crime, sanctions, or investigative journalism work."},"id":"followthemoney","links":{"html":"https://skillfed.io/packages/followthemoney","md":"https://skillfed.io/packages/followthemoney.md","pypi":"https://pypi.org/project/followthemoney/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-30","license_spdx":null,"license_treatment":"permissive","name":"followthemoney","python_support":"supports_current","summary":"A data model for anti corruption data modeling and analysis."},"popularity":{"monthly_downloads":81103,"position":14249,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"4.10.1"}