How to write a Data Management Plan for your project A taster of the Transferrable Skills module Gareth Knight Project Manager RDM Support Service

Research Data Digital or physical material that is collected, observed, or created for the purposes of performing original research Data is produced using many methods: Observation: Watch & record variables of interest Experiment: Apply treatment or control condition & record variables of interest Simulation: Produce model that imitates a real-world process or system Derivation: Secondary data processed to produce new research results. Data Management is the decision-making process that determines how data should be handled during a research activity. By taking steps to manage your data, you can achieve several objectives: - See more at: http://www.lshtm.ac.uk/research/researchdataman/introduction/rdm_intro.html#sthash.GYmcHqxZ.dpuf http://libraries.mit.edu/guides/subjects/data-management/what.html https://www.flickr.com/photos/flow14/3714092493/

LSHTM Expectations “Data produced during the research activity should be managed appropriately, ensuring that it is stored, organised and documented in a manner that allows it to be understood and used for the intended purpose.” LSHTM Research Degrees Handbook “A Data Management Plan describing the approach that will be taken to create, manage, and share research data should be produced by all School-led research grants that are creating, capturing, or enhancing data.” LSHTM Research Data Management Policy

Why Plan Data Management? Identify end goal & practical steps you need to perform Anticipate problems and reduce likelihood that they will occur Recognise support needs & resource implications Communicate objectives to your supervisor Demonstrate you’re taking a responsible approach to project management Meet sponsorship obligations Identify research topic & funding Perform literature review Develop research plan Upgrading seminar Perform research Write-up results Produce several drafts Finalise & submit

Session Outline The session will cover the following topics: Reasons to manage your research data The role of Data Management Plans in research Key decisions that should be made related to: Data handling practices File formats and software tools Quality control Documentation Storage and security Data archiving and sharing Concluding thoughts & recommendations