English

Chapter on how to properly organise and document data and metadata, discussing good practices in designing an appropriate data file structure, file naming and organising data within suitable folder structures; how organising data facilitates orientation in the data file, contributes to the understanding of the information contained and helps to prevent errors and misinterpretations. Also what counts as appropriate documentation of data, development of rich metadata to make data FAIR and standards to promote data sharing.

Focus on:

• elements which are important in setting up an appropriate structure for organising data for intended research work and data sharing
• overview of best practices in file naming and organising data files in a well-structured and unambiguous folder structure
• how comprehensive data documentation and metadata increases the chance data are correctly understood and discovered
• common metadata standards and their value
• relevant DMP questions on this topic.

Chapter introducing research data management and data management planning, explaining basic concepts on:

• research data, social science data, (sensitive) personal data and FAIR principles
• data management and data management plans (DMP)
• the content elements that make up a DMP

Practical tutorials to manage and handle research data for particular software packages: SPSS, R, ArcGIS and N-Vivo. Tutorials contain many practical exercises.

Detailed guidance for researchers, with model consent form and example consent forms, on how to consider future reuse of research data as part of consent procedures with research participants. To make sure that research data, in particular qualitative data, can be made available for future reuse, it is important that consent for future reuse of the data by other researchers is sought from participants. Participants should be informed how research data will be stored, preserved and used in the long-term, and how confidentiality can be protected when needed.

Guidance considers written and verbal consent, the timing of consent, examples consent forms and wording to use, etc. 

Set of hands-on exercises that can be used for data management and sharing training, developed from real-case datasets and scenarios. 

This OpenAIRE and EOSC-hub webinar covers Horizon 2020 rules and good practices approaches to addressing issues about Open Data, Open Science and research results exploitation in Consortium Agreements and Data Management Plans. It also specifically covers the issues of concern between Open Science and exploitation (patents, spin offs/ outs, confidentiality), business planning and licensing strategies.

Materials:

• Recording
• Slides: 
  • EOSCDIH
  • IPR and exploitation
  • DATA Ownership

The module offers a primer on managing research data.  

The primer is specifically aimed at those who are not yet familiar with Open Access. 

Online data management guidance and resources for researchers, developed by the UK Data Service. This resource provides best practice guidance and advice, including examples, exercises, tools and templates. The focus is on the social sciences and research with human participants. Particular areas covered are:

• Data management planning
• Legal and ethical aspects of managing and sharing data
• IP Rights
• Documenting data
• Formatting data
• Storing data

About 200 online courses dedicated to various disciplines including humanities and social sciences.