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==Get involved==
==Get involved==
*You can contribute to this project in various ways: matching data, data quality checks and data editing/upload.
*You can contribute to this project in various ways: matching data, data quality checks and data editing/upload.
*You can give your feedback at [https://github.com/UB-Mannheim/Aktienfuehrer-KG/issues GitHub AKF-KG Issues].
*You can get an account here via email request to the [https://fdz.bib.uni-mannheim.de Research Data Center at UB Mannheim]. Please write "Request an account at the AKF KG" as a subject.
*You can get an account here via email request to the [https://fdz.bib.uni-mannheim.de Research Data Center at UB Mannheim]. Please write "Request an account at the AKF KG" as a subject.
*If you are new to knowledge graphs, check out materials at [https://github.com/shigapov/wikibase-knowledge-graphs Wikibase Knowledge Graphs].
*If you are new to knowledge graphs, check out materials at [https://github.com/shigapov/wikibase-knowledge-graphs Wikibase Knowledge Graphs].

Revision as of 06:48, 11 April 2023

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Overview

The Aktienführer (AKF) Knowledge Graph is free and open. It contains structured (meta)data for the German listed stock companies from the Hoppenstedt-Aktienführer from 1956 to 2018. The metadata includes official company names with time ranges, company identifiers (ISIN and WKN) and Aktienführer IDs.

We enriched metadata via entity linking with other databases: Creditreform, Bureau van Dijk Orbis, GND and Wikidata. The knowledge graph contains 342 external identifiers representing various databases, including the valuable company databases: Crefo number, BvD ID, Orbis ID, Handelsregisternummer, PM20 folder ID, European VAT number, D&B Hoovers company profile, Bloomberg company ID, ROR ID, Legal Entity Identifier (LEI), Google Knowledge Graph ID, PermID, OpenSanctions ID, LinkedIn organization ID, German Lobbyregister ID, North Data ID and OpenCorporates ID.

Access to (meta)data

Use Cases

  • Searching identifiers of German companies for the period 1956-2018
  • Matching your (meta)data to AKF companies
  • Clean your tabular data and match it to the AKF knowledge graph with OpenRefine
  • Semantic annotation of tabular data using the AKF knowledge graph with bbw
  • Federated queries over AKF, Wikidata and other SPARQL endpoints

Get involved

External Resources

Acknowledgments

This work was funded by the Ministry of Science, Research and Arts of Baden-Württemberg through the project “BERD@BW" and by the German Research Foundation (DFG) through the project "BERD@NFDI".