MBI-KG: A knowledge graph of structured and linked economic research data extrated from the 1937 book "Die Maschinen-Industrie im Deutschen Reich"

Shigapov, Renat ; Schmidt, Thomas ; Kamlah, Jan ; Schumm, Irene ; Streb, Jochen ; Lehmann-Hasemeyer, Sibylle

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DOI:	https://doi.org/10.1016/j.dib.2024.111238
URL:	https://www.sciencedirect.com/science/article/pii/...
URN:	urn:nbn:de:bsz:180-madoc-684852
Dokumenttyp:	Zeitschriftenartikel
Erscheinungsjahr Online:	2024
Datum:	17 Dezember 2024
Titel einer Zeitschrift oder einer Reihe:	Data in Brief
Band/Volume:	Article 111238
Heft/Issue:	2024
Seitenbereich:	1-12
Ort der Veröffentlichung:	Amsterdam [u.a.]
Verlag:	Elsevier
ISSN:	2352-3409
Sprache der Veröffentlichung:	Englisch
Einrichtung:	Zentrale Einrichtungen > UB Universitätsbibliothek Fakultät für Rechtswissenschaft und Volkswirtschaftslehre > Wirtschaftsgeschichte (Streb 2011-)
Bereits vorhandene Lizenz:	Creative Commons Namensnennung 4.0 International (CC BY 4.0)
Fachgebiet:	330 Wirtschaft 900 Geschichte
Freie Schlagwörter (Englisch):	German company data , mechanical engineering industry
Abstract:	The MaschinenBauIndustrie Knowledge Graph (MBI-KG) is a structured and semantically enriched dataset extracted from the 1937 publication “Die Maschinen-Industrie im Deutschen Reich” (The Machinery Industry in the German Reich), published by the “Wirtschaftsgruppe Maschinenbau” and edited by Herbert Patschan. This historical source offers data on German companies within the mechanical engineering industry during the pre-World War II era. The book was digitized, and Optical Character Recognition (OCR) was applied to extract text. The unstructured extracted data was then structured and semantically enriched to enable data integration and reuse. The semantically enriched data was uploaded into an open-source knowledge-graph software. The resulting knowledge graph includes detailed information about companies, individuals, and administrative entities relevant to the German mechanical engineering industry. The data is accessible through various means, including a SPARQL endpoint, an API, advanced search functionalities, a reconciliation API, and bulk files. Each entity in the knowledge graph can be exported in multiple formats, such as CSV, RDF (ttl), JSON, and NDJSON, ensuring compatibility with diverse research tools and platforms. This dataset can be reused in various research domains, including economic history, data science, and digital humanities. By providing machine-readable, structured data from a crucial historical period, the MBI-KG facilitates novel analyses and insights into the economic and industrial landscape of early 20th-century Germany. The dataset's interoperability with other data sources and its alignment with FAIR principles further enhance its value for interdisciplinary research and long-term preservation

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