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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Documenting 2 Items

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.

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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.

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Planning 12 Items

Guideline for the sustainable development and use of research software

NFDI4Culture Guideline
Author(s): Daniel Jettka, Ulrike Henny-Krahmer
Version: 1.0.1

How can software be developed, offered and used in such a way that it itself and the research results produced with it remain sustainably available in the sense of the FAIR criteria and can be re-used as far as possible?

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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.

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How to be FAIR with your data (2021)

Link Recommendation
Language(s): English

The teaching and training manual is intended to support higher education institutions in integrating FAIR-specific content into curricula. It offers a comprehensive presentation of all FDM and FAIR topics, arranged by competence profiles, and includes practical material.

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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.

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Formal Ontologies: A Complete Novice's Guide (2018)

Link Recommendation
Language(s): English

The multi-part learning module of the PARTHENOS project (2016–19, G. Bruseker et al.) explains the purpose, basic principles and application contexts of ontologies in semantic information processing even for users without an information science background.

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FAIR-Aware: Assess Your Knowledge of FAIR (2021)

Link Recommendation
Language(s): English

FAIR-Aware is an online tool that helps researchers and data managers assess how much they know about the requirements for the findability, accessibility, interoperability and reusability (FAIR) of datasets.

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Rights & Ethics 2 Items

The CARE Principles for Indigenous Data Governance

Link Recommendation
Language(s): English

The CARE Principles were formulated to complement the FAIR Principles with an important research ethics aspect. The topic is explained in an introductory way and via the page one can obtain both a summary and a detailed presentation (each as a PDF).

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CARE – Traditional Knowledge Labels

Link Recommendation
Language(s): English

Traditional Knowledge Labels help to implement the CARE principles. Via the page one gets a detailed explanation and further explanations of the TK labels.

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