Plan

What is it?

Everything starts with a research question. Already think about data management, data sharing and re-use as early as possible, preferably already at the research proposal stage, and create a data management plan! This will save you a lot of time later on. Consider for instance, which data you are going to collect, which methods you are going to use and how you are going to backup, preserve and share your data. Discovering other authors’ data can foster new ideas and hypotheses.

Moreover, you may be able to strengthen or validate your research by reusing data collected by others. Portals like GFBio facilitate such data driven research.

Check if your institution or department has data management recommendations, guidelines or even has its own data management policy. In this case, you’re a lucky guy and can draw on these valuable information!

Note that you can apply for funding to manage your data (e.g. at DFG), by formulating a data management plan as part of your proposal.

DLC_Plan

How to do it?

  1. Browse data portals to generate data-driven hypothesis or to find data that may complement your own.
  2. Check for existing data management recommendations, guidelines or policies of your institution, department or funder.
  3. Formulate a data management plan, including:
    • Basic information: project title, contact information, motivation for data collection
    • Information on data: type, format, volume, collection standards, methodologies, quality assurance
    • Documentation and metadata: readability and interpretability of data, metadata standards
    • Ethical and legal compliance: agreement on preservation/sharing conditions, sensitive data, intellectual property
    • Storage and backup plan: responsibility, data recovery, access for collaborators, security
    • Preservation: selection of data, foreseeable future use, time and location for preservation, costs
    • Data sharing and publication: modalities, conditions, persistent identifiers
    • Responsibilities: implementation, roles and responsibilities for each activity, ownership agreement
    • Resources: need for additional hardware/software or expertise for training, efforts and costs for data management and data archiving
  1. Consider the data management plan and costs for data management in your research proposal.
  2. Do not underestimate the benefit of a data management plan for your project work, take it as a living document and update it regularly during project time.

Who does it?

Every data producer and data re-user, integrating secondary data or creating own data within his/her research project or as a partner in a research program.

Key Elements

  • Propose a hypothesis of current interest (consider the possibilities of data-driven research).
  • Take data management into account of your research questions and formulate a data management plan as part of your Research Proposal.
  • Apply for data curation and preservation costs.
  • Keep your data management plan up to date.

GFBio Services

Data Search

Data Visualization and Analysis

GFBio Data Management Plan Tool and DMP Support

Useful Links

http://www.dfg.de/formulare/54_01 (Proposal Preparation Instructions)
http://www.dfg.de/en/research_funding/announcements_proposals/2015/info_wissenschaft_15_36/index.html (Guidelines on the handling of research data)

Publish ← → Collect

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Recommended citation:
German Federation for Biological Data (2022). GFBio Training Materials: Data Life Cycle Fact-Sheet: Data Life Cycle: Plan. Retrieved 27 Jun 2022 from https://www.gfbio.org/training/materials/data-lifecycle/plan.