DARIAH is a pan-European infrastructure for arts and humanities scholars working with computational methods. It supports digital research as well as the teaching of digital research methods.
This course provides a comprehensive overview of cultural heritage data modelling, focusing on structuring and documenting information within the context of cultural heritage institutions. Participants will learn to represent information using entities and relationships, applying relevant metadata standards. The course emphasises the importance of understanding data models for reusing both data and metadata, with a specific focus on the Europeana Data Model (EDM) and its application in academic and research settings.
This course provides a comprehensive understanding of Europeana as a digital platform through a walkthrough of the Application Programming Interfaces (APIs) it offers. It provides the knowledge and skills to understand the purpose they serve and the functionality they have, to exploit them by formulating efficient queries for cultural heritage information retrieval. Building on use cases, it delves into the APIs required to achieve research goals, exploring their features and providing familiarisation with supported data formats.
This resource aims to introduce the main aspects of data ethics in the cultural heritage domain. It also examines how data management can be supported to become more ethical, while also addressing topical discourse about data ethics in the sector. The resource also aims to support in critically reflecting on some case studies with evident digital data ethics considerations.
This resource provides guidance on digital practices to curate interactive experiences through a set of practical exercises. The resource aims to support GLAM’s researchers and practitioners to engage with their audiences through the design of multimedia applications, while making use of appropriate frameworks and tools.
This course provides the essential knowledge and skills to understand and efficiently use Cultural Heritage data. Guided by Prof. Lorena, a persona created for the course, participants explore the significance of CH data, its types, and formats. They learn to identify sources for data acquisition and apply techniques to enhance data quality. The course also covers methods for organizing CH data, introduces key metadata standards, and examines current trends and technologies in the field.
The goal of this course is to introduce the Collections as Data principles in the cultural heritage sector to make available a digital collection suitable for computational use. Students will have a fundamental understanding of the complexities of Collections as Data as well as an appreciation of the diversity of the content provided by cultural heritage institutions. This course will be useful for small and medium-sized institutions willing to make available their digital collections suitable for computational use.
This resource is an introduction to Digitisation Methods for Material Culture. The resource explores basic topics with regards to the study of material culture, while also looking at types of media as means to communicate and share information about it, as well as digitisation methods to capture material culture data.
This resource provides guidance on how to use digital storytelling, deploying 3D data, annotations and combining media to enable users to access and explore information about digital heritage assets over the web.
This tutorial explores where and how to find, create, and collect images of textual material, a crucial initial step in any process using Automatic Text Recognition (ATR).
This talk gives an overview over developments in digital cultural heritage in recent decades and explores challenges, and opportunities, in the field. It addresses the importance of open, fair and democratic sharing of cultural data, challenges with sustainability of digital projects and how gaming can be a tool for public engagement.
This presentation outlines the aim and scope of the Historical Farm and People Registry project, explains the development process and problems encountered on the way, and demonstrates a use case for the ‘final’ product.
Kick off your journey into Automatic Text Recognition (ATR) with our introductory tutorial video. This is the first video of a tutorial series dedicated to extracting full text from scanned images.
