Service provider

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.

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

Library Carpentry workshops teach people working in library- and information-related roles how to:

• Cut through the jargon terms and phrases of software development and data science and apply concepts from these fields in library tasks;
• Identify and use best practices in data structures;
• Learn how to programmatically transform and map data from one form to another;
• Work effectively with researchers, IT, and systems colleagues;
• Automate repetitive, error prone tasks.

Chapter on the process of data discovery and reuse, including evaluating data quality. For discovering high-quality data, curated lists of different types of social science data sources in Europe and around the world are presented.

Focus on:

• set up - and adjust - a search strategy to find suitable data for your research purposes
• social science data repositories as sources for discovering social science data
• data sources which CESSDA-experts recommend for selected research topics
• evaluating the quality and usefulness of data for secondary analysis
• different types and modes of access to data
• relevant DMP questions on this topic

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. 

The lessons introduce terms, phrases, and concepts in software development and data science, how to best work with data structures, and use regular expressions in finding and matching data. We introduce the Unix-style command line interface, and teach basic shell navigation, as well as the use of loops and pipes for linking shell commands. We also introduce grep for searching and subsetting data across files. Exercises cover the counting and mining of data. In addition, we cover working with OpenRefine to transform and clean data, and the benefits of working collaboratively via Git/GitHub and using version control to track your work.

This workshop is co-developed with the National Ecological Observatory Network (NEON). It focuses on working with geospatial data - managing and understanding spatial data formats, understanding coordinate reference systems, and working with raster and vector data in R for analysis and visualization.

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.