Culture Knowledge Base

This 2020 European Commission report identifies ten basic questions and principles that researchers should ask themselves before deciding to go 3D digitizing.

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.

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.

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.

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 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.

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.

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.

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.

EOSC Pillar: Legal Compliance Guidelines for Researchers is a checklist for researchers to design research projects in compliance with data protection law. In addition to data protection law, the checklist also takes into account other legal issues of intellectual property law.