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 Friday Frontiers presentation provides a rich insight to the design and development of the University College London's Sloane Lab knowledge base, the modelling choices, and priorities in relation to semantics and vocabularies and the range of challenges addressed in the process of aggregation in terms of data disparity, integration facility, conflicting information and inconsistency, uncertainty and data absence.
The data you generate in humanities and social science projects may well need longer term storage
beyond the scope of your own research project. Medium to long term data storage is vital for
allowing other scholars to examine and test your data and models, and ensuring open access to your
data is an increasingly prominent issue. This resource will guide you through a thoughtful discussion of Data Management and Storage.
This resource discusses various approaches and methods to evaluate digital or hybrid interactive experiences, which support the interpretation of heritage assets. The resource also aims to support researchers’ and practitioners’ practical understanding of evaluation methods and tools to capture audiences’ engagement with media and explore technology impact.
This resource offers an introduction to copyright laws within the UK context when dealing with multidimensional media from repositories, archives and collections from that country.
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.
In this resource students will learn what a database is and how it is used in humanities research, go through examples of Humanities Databases in use by researchers today, learn when a researcher would need to use a database and how to distinguish between different database technologies.
This resource is an introduction to the photogrammetry technique to capture visual data about cultural heritage assets and produce associated 3D models.
This resource offers a starting point to learn more about the different types of multidimensional media, as well as managing media in a way which promotes the FAIR principles.
The resource also introduces the concept of a Virtual Research Environment to support retrieval and curation of multidimensional data for storytelling via interoperable frameworks.
Google Vision and Tesseract are both popular and powerful OCR tools, but they each have their weaknesses. In this lesson, you will learn how to combine the two to make the most of their individual strengths and achieve even more accurate OCR results.
This resource helps students tackle key prosopography challenges, such as disambiguating individuals with the same name, handling anonymous entries, and recognizing fictional people, known as the Rusudan Problem. Additionally, this resource focuses on the theory of identity, where roles, titles, and historical presence may be disputed but still carry an assumed "correct" interpretation. Fluid identities—such as ethnicity, gender, and religion—are more complex and require careful modeling in databases. The course also covers how to scope projects effectively by defining clear research questions and boundaries.
This resource is an introduction to 360 degrees panorama photography. It explores different types of panoramic representations and examples of 360 degree panoramas in the cultural heritage domain. Practical advice and step by step guidance on how to capture data and process them is also included in order to produce and publish 360 degrees panorama images.
In this resource, learners will receive an introduction to artificial intelligence through the exploration of prompt engineering across text to text and text to image interfaces. Learners will also explore the positive varied applications of AI as well as the drawbacks.
