Data Management and Data Management Plans

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

Modern research requires special tooling, software and processes that allow researchers to link, transform, visualise and interpret the data. Lack of proper data management practices can lead in extreme cases to irreversible loss of data. As a consequence, reproducibility of scientific experiments can be questioned. This in turn reduces trust in scientific findings and undermines reputation of researchers and their institutions. For this reason, excellent data management skills are nowadays an essential asset to successful researchers. This talk will introduce participants to Data Management Plans that help to plan how data is handled during experiments so that no data is lost, can easily be found, correctly interpreted using provided metadata, and properly licensed. Participants will learn about practical aspects of data management. They will also get familiar with research funder requirements for Data Management Plans that are becoming an obligatory project deliverable around the world.
Topics covered:
• Why good data management is important?
• What are the Data Management Plans?
• How to create a Data Management Plan?
• What are the best data management practices?
• How to make research data FAIR?
• What are the funder requirements for Data Management Plans?
• What does the future look like concerning data management?

Authoring Person(s) Name: 
Tomasz Miksa
Authoring Organization(s) Name: 
SBA Research
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution 4.0 International - CC BY 4.0
Access Cost: 
No fee
Citation - format of the preferred citation for the learning resource: 
Tomasz Miksa. (2017, December). Data Management and Data Management Plans. Zenodo.
Primary language(s) in which the learning resource was originally published or made available: 
More info about
Keywords - short phrases describing what the learning resource is about: 
Data management
Data management planning
Data management planning tools
Machine-actionable data management plans (DMPs)
Published / Broadcast: 
Monday, December 4, 2017
ID - identifier that provides the means to locate the learning resource or its citation: 
Type - namespace prefix for the citable locator, if any: 
Publisher - organization credited with publishing or broadcasting the learning resource: 
SBA Research
Version - revision or edition number or date associated with a learning resource: 
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.
Contact Person(s): 
Tomasz Miksa
Contact Organization(s): 
SBA Research
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.
Target Audience - intended audience for which the learning resource was created: 
Data manager
Data policymaker
Data professional
Data supporter
Repository manager
Research scientist
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
Up to 1 hour