Data creator

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 workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

The article summarises and critiques various training provisions around best practices in Research Data Management. The article, which is openly available on DARIAH-Campus, deals with issues such as what is data in the humanities, what are the benefits of research data management, what are your options when it comes to sharing your data, leading to a recipe for Data Management Planning of your research project.

The code for the JOSS submission tool

The repository of online research papers published in the Journal of Open Source Education.

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.