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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Overarching topics 3 Items

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.

Read (de)

DFG-Code of Conduct "Guidelines for Safeguarding Good Research Practice" (2019)

Link Recommendation
Language(s): German

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.

Read (de)

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 7 Items

What are Authority Data?

NFDI4Culture Video Guideline
Author(s): Melanie Gruß, Desiree Mayer
Contributor(s): Eva Bodenschatz
Version: 1.0.0

The tutorial basically explains what authority data are and how they can be used in relation to research data. In addition, the video describes the role of authority data for different entities and from different providers and explains their potential for the Semantic Web.

Play

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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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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Data Sharing and Management Snafu in 3 Short Acts (2012)

Link Recommendation
Language(s): English

This little data management horror story illustrates fundamental problems in the subsequent use of data that arise due to poor standardisation, documentation and archiving, suitable for initial sensitisation to the topic of research data management.

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Data sharing & publishing 2 Items

From project proposal to data publication

Link Recommendation
Language(s):

This task sheet for beginners contains eight key tasks on research data management, from data capture to publication: Data Management Plan, Data Structuring and Naming, Data Selection, File Formats, Metadata/README File, Legal Aspects, License Selection, Repository Selection.

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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.

Read (en)