Data creator | SSH Training Discovery Toolkit

Source
Title	Body
FD Mentor	Roadmaps, recommendations for action and good practice examples for the strategic development and improvement of research data management at German-speaking universities are developed for subsequent use. The focus is on the development of tools for strategy development for research data management, models for institutional research data policies, and a consulting and training concept
DelftX - Free online courses from Delft University of Technology	Free online courses from Delft University of Technology on edX Delft University of Technology is the largest and oldest technological university in the Netherlands. Our research is inspired by the desire to increase fundamental understanding, as well as by societal challenges. We encourage our students to be independent thinkers so they will become engineers capable of solving complex problems. Our students have chosen Delft University of Technology because of our reputation for quality education and research.
Coursera	MOOC, offering diverse online teaching including single courses, specializations, professional certificates, mastertrack certificates and online degrees. It offers an array of syllabuses on "Data Science".
Training catalogue ENVRI	Training catalogue of the ENVRI community. This catalogue is designed to facilitate findability, sharing and reuse of educational resources on FAIR data management. To do so, it hosts metadata of educational resources collected by ENVRI so that these can be searched, discovered and accessed.

Item
Title	Body
Archive and Publish	High-quality data have the potential to be reused in many ways. This chapter explores options for archiving and publishing data as a strategy for FAIR data, considering repository solutions, access, use and citation of data. Focus on: the difference between data archiving and data publishing the benefits of data publishing different data publication services, such as data journal, self-archiving, a data repository selecting a data repository which fits your research data's needs ways to promote published research data relevant DMP questions on these topics
Protect	Key legal and ethical considerations in creating shareable data. This chapter clarifies the different legal requirements of the European Union Member States, and the impact of the General Data Protection Regulation (GDPR) on research data management. It shows how sharing personal data can often be accomplished by using a combination of obtaining informed consent, data anonymisation and regulating data access. The supporting role of ethical review in managing legal and ethical obligations is also highlighted in this chapter. Focus on: legal and ethical obligations towards research participants and the different legal requirements of EU Member States how protecting data properly protects against violating laws and promises made to participants the General Data Protection Regulation and its relevance in research informed consent, anonymisation and access controls to facilitate creating shareable data relevant elements in a consent form anonymisation techniques for quantitative and qualitative data relevant DMP questions on these topics
Store	Chapter on storage, backup, recovery and security strategies for research data, to protect them against accidental loss and against unauthorised manipulation. Particularly when collecting (sensitive) personal data it is necessary to ensure that these data can only be accessed by those authorized to do so. Focus on: different storage solutions and their advantages and disadvantages storage strategy for research data backup and disaster recovery strategy to ensure that avoid data loss, e.g. through human error or hardware failure protect data against unauthorised access with strong passwords and encryption relevant DMP questions on these topics
Process	Chapter on the data operations needed to prepare data files for analysis and data sharing, starting with data entry and coding of data files. Throughout the different phases of research data files will be edited numerous times. During this process, it is crucial to maintain the authenticity of research information contained in the data and prevent it from loss or deterioration, as well as a comprehensive approach to data quality. Focus on: strategies to minimise errors during the processes of data entry and data coding the choice of file formats managing the integrity and authenticity of data during the research process a systematic approach to data quality DMP questions on these topics.
Organise and Document	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.
Plan	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