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DataCite Best Practice Guide
DataCite Best Practice Guide
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This document is a guideline for the use of the official DataCite Metadata Schema documentation (https://schema.datacite.org/), version 4.4 (https://doi.org/10.14454/3w3z-sa82). A support documentation for more convenience and better navigation can be found here as a HTML version DataCite Metadata Schema Documentation (https://datacite-metadata-schema.readthedocs.io/, different versions available). It is meant for researchers, IT and library support staff. Further information on the schema can be found on the DataCite support site (https://support.datacite.org/docs/datacite-metadata-schema-44). The document was created with participation from the following institutions/projects: *IT-Gruppe Geisteswissenschaften (LMU), *Leibniz Supercomputing Centre, *Max Weber Stiftung - Deutsche Geisteswissenschaftliche Institute im Ausland, *Universitätsbibliothek der FAU, *Universitätsbibliothek der LMU München, *VerbaAlpina. This guide is designed to be reused by other institutions as well. To create a DataCite XML file for the project you want to describe, we recommend to you to use the DataCite Metadata Generator [external link]. This tool is kept in sync with this guideline, safe for transmission times inbetween versions. If you want to create metadata for research data on a scale that is too large for manual procedures, please contact one of the institutions named above.
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URL: https://doi.org/10.5281/zenodo.7040047Communities:
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Disciplines:Target Groups:
  • Data Steward
  • Researcher
Proficiency Levels:
  • Competent

FAIR research data with NOMAD – FAIRmat's distributed, schema-based research-data infrastructure to harmonize RDM in materials science
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FAIR research data with NOMAD – FAIRmat's distributed, schema-based research-data infrastructure to harmonize RDM in materials scienceScientific research is becoming increasingly data centric, which requiresmore effort to manage, share, and publish data. NOMAD is a web-based platform thatprovides research data management (RDM) for materials-science data. In addition tocore RDM functionalities like uploading and sharing files, NOMAD automatically ex-tracts structured data from supported file formats, normalizes, and converts data fromthese formats. NOMAD provides an extendable framework for managing not just files,but structured machine-actionable harmonized and inter-operable data. This is the ba-sis for a faceted search with domain-specific filters, a comprehensive API, structureddata entry via customizable ELNs, integrated data-analysis and machine-learning tools.NOMAD is run as a free public service and can additionally be operated by researchinstitutes. Connecting NOMAD installations through the public services will allow afederated data infrastructure to share data between research institutes and further har-monize RDM within a large research domain such as materials science.
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PDF
Languages
English
Media Type
Presentation
Publication Date
2023-09-13
License
CCBY
Size
3.8 MB
Authors
Keywords
#metadata#research data management#FAIR data#electronic lab notebook#materials science
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DATA AFFAIRS – Data Management for ethnographic research
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DATA AFFAIRS – Data Management for ethnographic researchThe e-learning portal "DATA AFFAIRS" (developed by the DFG-funded Collaborative Research Center 1171 "Affective Societies" (FU Berlin)) offers scientists working with empirical and qualitative research data in ethnographic research a wide range of learning and training opportunities based on the current challenges of data management. The open-access platform provides all interested parties with insights into a total of 18 topics, ranging from data protection and data security, artificial intelligence and sustainability to the best methods for anonymizing and pseudonymizing personal data. The content can be explored via different areas: "Inform", "Learn", "Guide" and "Glossary", and contains text, image, audio and video material as well as interactive learning units. Practical examples and application-oriented exercises encourage interactive self-study.
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Unknown
Languages
German
Publication Date
2023-11-22
License
CCBYSA
Authors
Keywords
#metadata#research data management#archiving#copyright#data life cycle#data management plan#license#artificial intelligence#care principles#fair#audiovisual#data format#data protection#documentation#sharing
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Chemotion. An Introduction to an Open-Source ELN for FAIR Data
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Chemotion. An Introduction to an Open-Source ELN for FAIR DataElectronic Lab Notebooks (ELNs) are a key prerequisite to a comprehensive documentation of research processes, the digital storage of research data, and their reuse. ELNs can be used to plan, record, store and - in combination with repositories - disclose experiments or research data. In the long run, the benefit of ELNs is the option to store and manage data in a standardized way and to enrich the data with (automatically generated) information such as metadata, identifiers and descriptors. For scientists, ELNs offer advantages such as faster research processes and a faster access to information. Selected benefits of the ELN Chemotion - an ELN that was designed for the discipline Chemistry - will be presented to show exemplarily the use of research data management tools. The ELN offers special features for chemical work and includes diverse functions that allow the use of the ELN also in other disciplines. Both, the chemistry specific as well as the generic and adaptable modules will be presented in brief.  Chemotion ELN can be used in combination with the open access repository Chemotion. The disclosure of research data to the public is possible by a direct transfer of information from the ELN to the repository. The interoperable systems ELN and repository guarantee on the one hand an easy process for the disclosure of information and on the other hand the availability of comprehensive data including primary data and descriptions.  The systems Chemotion ELN and Chemotion Repository are part of the strategy of the National Research Data Infrastructure for Chemistry (NFDI4Chem) in Germany. Dr. John Jolliffe from NFDI4Chem will present the strategy and measures of NFDI4Chem in brief.
File Format
PDF
Languages
English
Media Type
Presentation
Publication Date
2023-06-16
License
CCBY
Size
5.6 MB
Authors
Keywords
#metadata#research data management#FAIR data#electronic lab notebook#RDM#Metadaten#Forschungsdatenmanagement#repository#FAIR-Prinzipien#ELN#FDM#FAIR principles#FAIRe Daten#Infrastruktur#Chemie#ELB#Elektronisches Laborbuch#Forschungsdateninfrastruktur#Repositorium#chemistry#infrastructure#research data infrastructure
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DFG Practical Guidelines on Digitisation. Updated version 2022.
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DFG Practical Guidelines on Digitisation. Updated version 2022.The DFG Practical Guidelines on Digitisation provide a fundamental basis for DFG-funded digitisation projects in its “Digitisation and Indexing” programme: They formulate standards and contain information on organisational, methodological and technical issues in the context of digitising and indexing objects relevant for research. They thus make an important contribution towards the sustainability, accessibility and compatibility of funded projects and to the resulting infrastructure. This document is an updated version of the Practical Guidelines last published in 2016 by the DFG. It was developed in consultation with the DFG Head Office by a group of authors initiated by the NFDI consortium NFDI4Culture, the majority of whose members have long played a part in shaping the Practical Guidelines and are actively involved in the NFDI consortia NFDI4Culture, NFDI4Memory, NFDI4Objects and Text+. The now revised Practical Guidelines on Digitisation serve as starting point for a material- and community-related differentiation of the Practical Guidelines by the communities. All communities and institutions concerned with the digitisation of research-relevant objects are encouraged to contribute their expertise to the further process.
Learning Resource Type
Report
File Format
PDF
Languages
English
Media Type
Text
Publication Date
2023
License
CCBY
Size
820 KB
Authors
Keywords
#metadata#NFDI#National Research Data Infrastructure#cataloging#digitization#information infrastructure#standardization
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MANTRA Research Data Management Training
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MANTRA Research Data Management TrainingThe MANTRA Research Data Management Training self-study course of the University of Edinburgh offers a good, English-language introduction to the topic of research data and research data management, with minor restrictions. The content of the course is rather generic and is aimed at all those who deal with the topic of research data in the context of a research project. The course is divided into eight content modules, each of which is concluded with exercises, as well as a further module containing tutorials with existing data sets for various software solutions. It should be noted that the statements on funding policy, funding institutions and DMP requirements focus predominantly on the UK.
File Format
Unknown
Languages
English
Publication Date
2017-10-23
License
CCBY
Authors
Keywords
#research data management#archiving#data management plan#sharing#research data#organizing#storing#machine learning
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How to be FAIR with your data
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How to be FAIR with your dataThe 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.
File Format
Unknown
Languages
English
Publication Date
2021-12-21
License
CCBY
Authors
Keywords
#research data management#data management plan#fair#research data#teaching#publishing#training
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