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.
Type:
Documenting 2 Items
21.08.2023
Data Curation Profile
Link Recommendation
Language(s):
German
The publication by Jake Carlson provides instructions on how to use the so-called "toolkit" for documenting research data, as well as templates and examples compiled for free use by Purdue University in the US.
21.08.2023
Data Documentation
Link Recommendation
Language(s):
German
The site provides detailed information on why, how and which research data should be documented in accordance with the FAIR criteria, with regard to formats, vocabularies, languages, protocols, repositories, persistent identifications.
Overarching topics 2 Items
14.08.2023
Shaping inventory-based research
Link Recommendation
Language(s):
German
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.
20.07.2023
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.
Planning 5 Items
15.08.2023
The challenge of data quality – recommendations for the future viability of research in the digital transformation (2019)
Link Recommendation
Language(s):
German
English
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.
14.08.2023
GO FAIR
Link Recommendation
Language(s):
English
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.
14.08.2023
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.
14.08.2023
FAIR Data Maturity Model (2020)
Link Recommendation
Language(s):
English
German
To counteract ambiguities in the interpretation of FAIR principles, the Research Data Alliance has developed core assessment criteria for FAIRness of data and formulated a set of indicators, including a checklist, as a starting point for reviewing your own data.
14.08.2023
Data Management Plan
Link Recommendation
Language(s):
German
The article offers a good first introduction to the topic of DMP and contains numerous useful, further links for the user (including the specifications of the funding institutions, DMP tools, etc.).
Data sharing & publishing 1 Items
14.08.2023
Checklist for appropriate handling of research data
Link Recommendation
Language(s):
English
This DFG questionnaire helps researchers to plan and describe the handling of research data in their project beyond the context of an application.