Broad, long-term financial, and economic datasets are scarce resources, particularly in the European context. In this paper, we present an approach for an extensible data model that is adaptable to future changes in technologies and sources. This model may constitute a basis for digitized and structured long-term historical datasets for different jurisdictions and periods. The data model covers the specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence, achieving extensibility. Furthermore, we outline a relational implementation of this approach based on historical German firm and stock market data from 1920 to 1932.

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Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and structured longterm, historical datasets. The data model covers specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence achieving extensibility. Furthermore, based on historical German company and stock market data, we discuss a relational implementation of this approach. Classification codes: C81, C82Acknowledgments: We are thankful to Wolfgang König and Johan Poukens who provided valuable comments on an earlier version of this paper. We are grateful for financial support to the Eurhisfirm consortium which is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 777489. The paper reflects only the author's view. The EU Commission is not responsible for any use that may be made of the information it contains.

Broad, long-term financial, and economic datasets are a scarce resource, particularly in the European context. In this paper, we present an approach for an extensible data model that is adaptable to future changes in technologies and sources. This model may constitute a basis for digitised and structured long-term historical datasets. The data model covers the specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence, achieving extensibility. Furthermore, based on historical German firm and stock market data, we discuss a relational implementation of this approach.