Culture Knowledge Base

Specifications for the digitization of two-dimensional materials such as manuscripts, books, newspapers, and magazines, but also photographs, paintings, and graphic sheets. They are technically oriented and refer exclusively to the image quality and metadata of the primary file.

This document presents professional methods for creating the most faithful digital reproductions possible of physical two-dimensional collection items such as texts, plans, maps, graphics, or photographs.Iit also focuses on documenting image-related information in metadata.

The DFG Practical Guidelines formulate standards and provide guidance on organisational, methodological and technical issues in the context of object digitisation and indexing. This document is an updated version of the Practical Guidelines published by the DFG in 2016.

In its discussion impulse on the scientific, scholarly and cultural use of collections, the Council for Information Infrastructures (RfII) addressed the (future) role of collecting institutions in the digital transformation of science with regard to the framework conditions.

The DFG Code of Conduct represents the consensus of the DFG's member organizations on the fundamental principles and standards of good practice, underscoring the importance of integrity in everyday research.

The publication identifies concrete data problems in research data on tangible cultural assets. Each problem is described by a structured profile that includes aspects such as the quality dimensions involved, examples, causes and ideas for improvement.

The position paper of the Council for Information Infrastructures (RfII) deals with quality assurance and enhancement in the documentation of research data and is a comprehensive and motivating analysis on the topic of quality assurance in the science system.

GO FAIR is a bottom-up initiative aiming to implement the FAIR data principles and make data discoverable, accessible, interoperable and reusable (FAIR). It provides an implementation network active in the areas of GO CHANGE, GO TRAIN, GO BUILD.

The page explains the FAIR principles quickly and clearly. On the one hand, it describes the tasks involved in creating FAIR research data, and on the other hand, it presents the requirements for repositories to offer FAIR data.