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.
Introduction: Standards are best explained in real life use cases. The Parthenos Standardization Survival Kit is a collection of research use case scenarios illustrating best practices in Digital Humanities and Heritage research. It is designed to support researchers in selecting and using the appropriate standards for their particular disciplines and workflows. The latest addition to the SSK is a scenario for creating a born-digital dictionary in TEI.
Introduction: The explore! project tests computer stimulation and text mining on autobiographic texts as well as the reusability of the approach in literary studies. To facilitate the application of the proposed method in broader context and to new research questions, the text analysis is performed by means of scientific workflows that allow for the documentation, automation, and modularization of the processing steps. By enabling the reuse of proven workflows, the goal of the project is to enhance the efficiency of data analysis in similar projects and further advance collaboration between computer scientists and digital humanists.
Introduction: This is a comprehensive account of a workshop on research data in the study of the past. It introduces a broad spectrum of aspects and questions related to the growing relevance of digital research data and methods for this discipline and which methodological and conceptual consequences are involved and needed, especially a shared understanding of standards.
Introduction: This blog post describes how the National Library of Wales makes us of Wikidata for enriching their collections. It especially showcases new features for visualizing items on a map, including a clustering service, the support of polygons and multipolygons. It also shows how polygons like the shapes of buildings can be imported from OpenStreetMap into Wikidata, which is a great example for re-using already existing information.
Introduction: This article proposes establishing a good collaboration between FactMiners and the Transkribus project that will help the Transkribus team to evolve the “sustainable virtuous” ecosystem they described as a Transcription & Recognition Platform — a Social Machine for Job Creation & Skill Development in the 21st Century!
Introduction: Apart from its buoyant conclusion that authorship attribution methods are rather robust to noise (transcription errors) introduced by optical character recognition and handwritten text recognition, this article also offers a comprehensive read on the application of sophisticated computational techniques for testing and validation in a data curation process.
Introduction: This is a well-structured account of a seminar session on data management held in Munich. It introduces many topics which humanists have to deal with during a research process.
Introduction: This very complete tutorial by Patrick Smyth will help digital humanists or any interested person on digital technologies applied to projects how to make data more accessible to users through APIs (Application Programming Interfaces). After explaining the basics about APIs and databases, an API is built and put into practice. Python 3 and the Flask are the web frameworks used for developing this API.
Introduction: This article explains the concept, the uses and the procedural steps of text mining. It further provides information regarding available teaching courses and encourages readers to use the OpenMinTeD platform for the purpose.