ADMIRAL Data Management Plan Template

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ADMIRAL: Data management plan

Derived from DCC data management plan template; some sections have been split.

The plan is derived from this DCC data life cycle:

DCC data life-cycle

Contents

Introduction and context

Basic information

  • title
  • summary
  • funding
  • duration
  • partners
  • etc.

What are the aims and purpose of research?

List of related policies

E.g.:

  • funding body requirements re. creation of a data management plan
  • institutional or research group guidelines, other dependencies
  • full version should demonstrate how these policies will be adhered to

What are the aims and purpose of data management plan?

  • Who is the target audience?
  • Full version to include statement on plan revision schedule)'

Glossary of terms

Legal, rights and ethical issues

Who owns the Intellectual Property and copyright?

How will the data be licensed?

  • e.g. Creative Commons, attribution

What are the ethical and privacy issues?

  • How will these be resolved? (e.g. anonymisation of data, consent agreements)

What is the dispute resolution process and/or mechanism for mediation?

Access, data sharing and reuse

How data will be made available?

  • What is the process for gaining access?
  • Are any permissions & restrictions placed on data?

How can / will the data be shared and re-use?

  • Which bodies/groups are likely to be interested?
  • What are the foreseeable uses?

Are there embargo periods?

  • How is the release timeframe justified?
  • Include note on right-of-first-use for original data collector/ creator/ investigator

Data collection/ development methods

What does 'data' comprise for the research?

  • Data description
  • volume
  • type
  • content to be created
  • etc.

Have you surveyed existing data?

(inc. 3rd party data)

  • What can be used/extended?
  • Are there any access issues?
  • What is the ‘added value’ to reuse?
  • Why does new data need to be created?
  • What is the relationship between new dataset(s) and existing data?
  • How will you manage interoperability; i.e. what methods will be used to integrate the data being gathered in the project with pre-existing data sources?

How will you capture/ create the data?

  • content selection
  • instrumentation
  • technologies and approaches chosen
  • methods for naming, versioning etc

How will metadata and documentation be captured?

  • What form will it take?
  • What standards will be used?
  • What contextual details are needed to make data meaningful?

Why have you chosen particular standards and approaches?

E.g.:

  • recourse to staff expertise
  • Open Source
  • accepted domain
  • local standards
  • widespread usage

What criteria will be used for Quality Assurance/Management

E.g.:

  • documentation
  • calibration
  • validation
  • monitoring
  • transcription metadata

Data standards

Data types

E.g.:

  • experimental measures
  • qualitative
  • raw
  • processed"

Which file formats and platforms will be used and why?

E.g.:

  • recourse to staff expertise
  • Open Source
  • accepted standards
  • widespread usage

Some of this seems to overlap the previous section "Why have you chosen particular standards and approaches".

How do data creation decisions take account of end user needs?

Short-term storage and data management

Anticipated data volumes?

Where will the data be stored?

  • On what media?
  • Who will be responsible?

How will data be transmitted?

  • encryption if appropriate

How will access arrangements and data security be managed?

  • How permissions, restrictions and embargoes are enforced?
  • Note on sensitive data, storage on off-network mobile devices etc

How regularly, by whom, and how will data be backed up?

Appraisal and retention timeframes

  • ideally with definite figures
  • N.B. this may simply point to relevant institutional or funding body requirements/ policies: political, temporal, commercial, legal

Deposit and long-term preservation

What is the long-term strategy for maintaining, curating and archiving the data?

On what basis will data be selected for preservation?

  • how long will data be kept? Ideally with definite figures
  • this may simply point to relevant institutional or funding body requirements/ policies: political, temporal, commercial, legal

How will you dispose/transfer sensitive data?

  • Justification of decisions.

How will data be prepared for preservation / sharing?

  • inc. anonymisation if appropriate

Where and how data will be archived

  • e.g. deposit in public repository or existing community database?
  • Transmission of data (encryption if appropriate)

What related information will be deposited?

  • references, reports, research papers, fonts, original bid proposal, etc

What metadata/ documentation will be created at each stage of ingest/ transformation?

  • descriptive
  • structural
  • administrative
  • preservation
  • etc.
  • How will this be created and by whom?

What procedures are in place for preservation and backup?

  • How regular
  • by whom
  • methods used? e.g.:
    • format normalisation
    • migration

Resourcing

Staff/organisational roles and responsibilities for implementing this plan

  • time allocations
  • project management of technical aspects
  • contributions of non-project staff etc

Financial issues

E.g.:

  • payments to service providers within institutions
  • payments to external data centres for hosting data
  • income derived from licensing data
  • etc.

Compliance and review

How adherence to this data management plan will be checked or demonstrated?

How and when this data management plan will be reviewed?

Agreement/ratification by stakeholders

  • (if useful)

Statement of agreement

  • (with signatures if required)

Annexes

Contact details and expertise of nominated data managers

Other annexes as required

Personal tools
Oxford DMP online
MIIDI
Claros