Management of your data

文章目錄

• Management of your data
• • Intro
  • Session data
  • Data lifecycle
  • Why
  • Areas of data management
  • Creating and reusing data
  • Issues to consider
  • • Creating your own data
    • Both
    • Using other's data
  • FAIR data principles
  • • Findable
    • Accessible
    • Interoperable
    • Reusable
  • Organising data: metadata
  • Data storage and backup
  • University storage options
  • Other storage options
  • Sharing your data
  • Why share research?
  • University position
  • Open data
  • Confidentiality and anonymity
  • Data management planning
  • Why a DMP
  • Resources for my pro

Intro

• What do you want to learn today?
• Write some ideas in the chat

Session data

• Why we need to manage your data
• How to management data and fair
• data management plans
• online data
• https://libguides.cam.ac.uk/engineering/managing-data

Data lifecycle

• creating data

• processing data

• analyzing data

• preserving data

• giving access to your data

• re-use data

Why

• increased efficiency
• preservation
  • Data need to be in the domain
• funder mandates
  • Have the follow the mandates from the founder’s perspectives
• good academic practice
  • It is the things that making the evidence based level for your academic reputations

Areas of data management

• four key areas of data management
  • creation and reuse
  • organization
  • Storage and backup
  • sharing

Creating and reusing data

• not all data needed to be created
  • datasets can be reused
• think about your own research
  • are you creating your own data or
  • reusing existing data
• what do you need to think about?
  • data privacy
  • ethics
  • liscening
  • quality

Issues to consider

Creating your own data

• set standards scale
• hardware and software
• think about to capture about the data
• decide where to store your data
• choose how to license and share

Both

• critical appraisal and reflection
• transpoarency and reproductibility
• visualization
• version control
• ethics

Using other’s data

• understanding metadata
• deal with interoperability and consistency
• familiarise yourself with context
• access issues
• Understand licenses and permissions for using it

FAIR data principles

Findable

• first step
• Metadata and data should be easy to find
  • human
  • computer
• machine readable metadata
  • automatic discovery
    • datasets
    • services

Accessible

• finds the required data
• know how they can be accessed
• possibly including authentication and authorization

Interoperable

• integrated with other data
• interoperate with applications or workflows
• anaysis storage and processing

Reusable

• ultimate goal of FAIR
• optimize the reuse of data
• to achieve this
• metadata and data in well-described
• replicated
• combined in different settings

Organising data: metadata

• metadata
  • any other descriptive document
  • help secondary users
  • to understand and use your data
• what information is needed
  • for the data to be read and interpreted in the future
• how will you capture
  • create this document and metadata
  • ceating a procedure
  • listing what software you used
  • writing a readme file to accompany the data

Data storage and backup

• Where do you think you would store your research data
  • Any issues
• Data security levels
  • Level 0
    • unclassified or public information
  • level 1
    • cambridge only (most the data)
  • level 2
    • confidential information
      • meeting minutes
  • level 3
    • personal and strictly confidential
    • names
    • Records
• Never store level 3 data on a cloud service
  • even the university levels
  • Storage
  • what kind of level are you working at

University storage options

• Help uis
• Engineering department
• storage options: OneDrive
  • Integration with MS365
  • online slide show
  • drag and drop file operations

Other storage options

• external hard drives
• other domains
• GitHub repositories
• university data stores and data repository
• filing cabinets for paper notes, samples, equipment
• backup frequently in at least two separate locations

Sharing your data

• how will you share data?
• wILL YOU HAVE ANY RESTRICTIONS ON DATA sharing?
• Consider when you will share your data
  • Funders often require a timely release of data
• Have you made plans for sharing your data?
  • Discuss in the chat or turn on your microphone to share your thoughts

Why share research?

• improved reproducbility
• use in education
• applied by practioners
• better value for money
• new research possible around the world
• comply with grant rules
• increased visability
• higher citations
• Improved efficiency
• more collaborations

University position

• Open research culture
• increasing access to
• ensure publication open access
• underlying data
• share propotals

Open data

• Open data is increasing

Confidentiality and anonymity

• confidentiality
  • private
  • Reveal this information to third parties
• anonymity
  • assurance to participate

Data management planning

• data management plans (DMPs)
  • documents you create before collecting and working with data
• what types of research data are you working with?
• what is your strategy for organising your data?
• what is your data backup storage

Why a DMP

• Data management plans (DMP)
  • ROADMAP TO A GOOD DATa management
  • mandated by funders
  • ensure essential

Resources for my pro

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