Introduction: In this article, José Calvo Tello offers a methodological guide on data curation for creating literary corpus for quantitative analysis. This brief tutorial covers all stages of the curation and creation process and guides the reader towards practical cases from Hispanic literature. The author deals with every single step in the creation of a literary corpus for quantitative analysis: from digitization, metadata, automatic processes for cleaning and mining the texts, to licenses, publishing and achiving/long term preservation.
Introduction: The FAIR Data Principles (Findable, Accesible, Interoperable, Reusable) aim to make clear the need to improve the infrastructure for reuse of scholarly data. The FAIR Data Principles emphasize the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals, key activities for Digital Humanities research. The post below summarizes how Europeana’s principles (Usable, Mutual, Reliable) align with the FAIR Data ones, enhancing the findability, accessibility, interoperability, and reuse of digitised cultural heritage.