Culture Knowledge Base

The NFDI4Culture Knowledge Base contains guidelines, reports, and specifications by the task areas of the consortium covering all aspects of research data management in the domain of material and immaterial cultural heritage. Additionally, we provide you with curated link recommendations to high quality open educational resources.

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Digitizing, Inventorizing, Enriching 2 Items

FADGI – Technical Guidelines for Digitizing Cultural Heritage Materials (2022)

Link Recommendation
Language(s): English

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.

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DFG Practical Guidelines on Digitisation (2022)

Link Recommendation
Language(s): English, German

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.

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Overarching topics 1 Items

Guideline for a FAIR Cultural Studies Research Data Management

NFDI4Culture Guideline
Author(s): Angela Kailus
Version: 1.0.1

In order to be optimally re-usable, research data should be processed according to the FAIR principles. This guideline explains what these principles mean and how they can be implemented in cultural studies and heritage collections.

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Planning 2 Items

Catalog of Quality Problems in Data, Data Models and Data Transformations (2020)

Link Recommendation
Language(s): English

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.

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FAIR Data Principles for Research Data (2017)

Link Recommendation
Language(s): English, German

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.

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