- 1 Data Management for Reproducibility
- 1.1 Content overview
- 1.2 Learning objectives
- 1.3 Completion criteria
- 1.4 Audience
- 1.5 Level
- 1.6 Prerequisite skills, expertise and experience
- 1.7 Overall likely time commitment
- 1.8 Event date and time
- 1.9 Registration deadline
- 1.10 Training partner
- 1.11 Location
- 1.12 Cost to institution per participant
- 1.13 Number of attendees
- 1.14 Application
Data Management for Reproducibility
Approaches to ensuring reproducible research are many and varied. This workshop presents a forensic approach to identifying data, processes, equipment and environmental factors which influence the variability and outcome of research and therefore impact its reproducibility. Using this approach we will analyse the elements of traditional Data Management Plans.
Participants will identify the content required to demonstrate that research methods are robustly documented, and that data and metadata, which shows the extent to which variability has been controlled, are available for external scrutiny.
This workshop is designed for researchers using primarily quantitative methods and is ideal for those in life and biomedical sciences. Familiarity with FAIR principles is advised.
- Describe data integrity in relation to research data, understand the concept of critical data as it relates to research data integrity.
- Learn the basics of process mapping.
- Articulate the benefits of process mapping in defining robust research protocols and identifying data which is critical to reproducibility.
- Conduct data integrity assessments on process maps to identify critical research data.
- Analyse the research process to identify risks to critical data e.g. sources of variability.
- Categorise the critical research data and associated data which can demonstrate the extent to which different types of variability have been controlled.
- Identify metadata for critical data and data associated with variables.
- Understand the elements of the data management plan which are key to documenting how critical research data has been robustly generated, recorded, checked and stored.
- Describe the key elements of metadata and be able to articulate methods for documenting these within a DMP.
- Take a generic DMP template and describe the modifications, annotations etc required to ensure that it captures critical research data, associated data on control of variability and metadata within your discipline.
- Attend both of the online workshops (2 hours each) and complete a process mapping exercise (1 hour) between the two online sessions.
- Following the second online session, create a customised DMP for your discipline, either alone or with colleagues. The plan needs to be accompanied with a process map which identifies critical research data and associated variability data (data which demonstrates control of variability).The plan needs to be presented to the workshop facilitators via an online appointment.
- We request that any new or adapted materials developed by participants be shared with an appropriate license on OSF.
The course would suit researchers who use mainly quantitative methods and is ideal for life and biomedical sciences.
Prerequisite skills, expertise and experience
General familiarity with research processes
Overall likely time commitment
- 2×2 training hours
- 1 office hour
- 6 to 8 hours creating and presenting deliverables
Event date and time
18th and 24th April 2024, both 1300-1500 UK time
8th March 2024
Cost to institution per participant
Number of attendees