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2017 Guide [EN] (Copy)

Last modified by vristika@helsinki_fi on 2023/12/12 07:31

Question are from the Tuuli template April 2017.

SECTION

QUESTIONS

 GUIDELINES  (Updated10.4.2017) 

Introduction

 

 

Why should you manage your research data and plan its management?

Research data management and its planning (DMP) is an integral part of good research practices. By writing a DMP before your project starts you will help minimise unexpected problems.

The invaluable advantages of data management planning include e.g. the following:

  • reducing the risk of losing data
  • saving time and money
  • meeting funder and policy requirements
  • maintaining/ensuring data integrity.

A clearly outlined DMP will also help you to overcome complex ownership and user rights issues in advance, and to support open access in order to promote new discoveries and productive future collaborations.

In the DMP data is understood as a broad term including:

  • research material (such as any kind of physical artifacts)
  • research sources (such as various archive material)
  • data produced during the research (such as digitized copies of the aforementioned physical artifacts)
  • data collected by various methods (such as surveys, interviews, measurements, imaging techniques etc.)
  • curated collections
  • annotation and coding of the material on various levels
  • all revisions of a data set produced in/for the analysis process
  • physical and electronic lab journals
  • source code and software

Your DMP should describe how you manage data during the whole research life cycle - and also cover what happens after the active phase of the project. Too often data cannot be shared or reused in research, teaching and learning in the future because of poor data management planning at the beginning of a project.

The DMP is a living document which should be updated as the research project develops.

Your research data management practices should follow the FAIR  principles which dictate how your data will be Findable, Accessible, Interoperable, and Re-usable.

Good luck with your DMP!

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

Types of data

What kinds of data are being collected or reused?

 

 

Briefly describe what kind of research data you will use, collect and produce in your project.

Shortly outline how the data will be collected: e.g. literary survey, survey, interview study, case study, observation, measurement, collected by machine or instrument, laboratory work, programming.

Describe in short what types of data will be used and is expected to be produced e.g. tables, texts, images, photographs, videos, statistics, diagrams, chemical or physical reactions, physical samples, sequences, codes, modeling, meta-analysis.

Tips for best practices

  • Explain your methods, experimental arrangements and data content in more detail in the research plan.
  • Clearly distinguish the data which is produced in this project from the study data that has been produced earlier.
  • By reusing data produced by you or others, you will avoid duplicating work already done.

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

What file formats will the data be stored in?

 

Your choice of file format is a primary factor in the accessibility and reusability of your data in the future. The format and software in which research data are created usually depend on how researchers collect and analyse data. Once data are prepared for storing, researchers should consider converting their research data to standard, open, non-proprietary and commonly used formats.

Tips for best practices

  • List the file formats for every type of data that will be stored and shared in; e.g. excel tables as .csv, word documents as .txt and videos as .mp4.
  • When listing the file formats you will be using, make sure to include any software necessary to view the data.
  • Favour software and formats based on open standards to enable data reuse, interoperability and sharing.

Links to general guides about

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

 

Documentation and quality control

How will the data be documented?

 

Data documentation explains the terms, variable names, codes or abbreviations used. What information is needed to find, use and interpret the data in the future? Describe the types of documentation that will accompany the data.

Metadata provides standardized structured information explaining the purpose, origin, time, location, creator, access conditions and terms of use of a data collection.

Tips for best practices

  • How will the data be organized during the project? Describe e.g. your file naming conventions, version control and folder structure.
  • Check what kinds of requirements data repositories (relevant to your subject) have for metadata.
  • In the beginning of the project you might not know what metadata standards you will be using, but you still need to ensure that “all variables will be described and suitable metadata standards will be used, if available”.

Links to general guides about

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

How will the consistency and quality of data be controlled and documented?

Miten aineiston eheys ja laatu varmistetaan ja dokumentoidaan?

Data quality control ensures that no data will be lost or accidentally changed during the research process. Quality control of data is an integral part of all research and takes place during data collection, data entry or digitization, and data checking phases.

Tips for best practices

  • Explain how the data collection methods used will affect the quality of data. You can provide evidence of data quality by documenting in detail how the data is collected.
  • Quality control can include e.g. using standardized methods and protocols for documenting observations, recording forms with clear instructions, taking multiple measurements, observations or samples, and calibration of instruments.

Links to general guides about

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

Storage and backup


How will the data be stored and backed up?

 

 

 Describe where you will store and back up your data during your research project. Methods for preserving and sharing your data after your research project has ended are explained in more details in Section 5.

Consider who will be responsible for backup and recovery. If there are several researchers involved, create a plan with your collaborators and ensure safe transfer between participants.

Tips for best practices

  • The use of storage services provided and maintained by IT services at the University of Helsinki is preferable. 
  • Do you have sufficient storage or will you need to include charges for additional services?
  • Remember to state your intention to specify your data management costs in the budget. 
  • If you need larger volumes of storage space, please contact the UH Helpdesk and describe your needs.
  • If using commercial cloud services ( e.g. Google Drive) make sure you do not have personal or sensitive data

Links to general guides about

 

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

How will you control access to keep the data secure?

Create a brief data security plan where you describe your processes on how you access, handle, and store the data safely. Keep your research data safe and secure during the research project. Determine who has access to your data and what they are authorized to do with it. Providing unauthorized people with access to the data may be illegal. Access controls should always be proportionate to the kind of data and level of confidentiality involved.

Tips for best practices

  • The use of a personal or shared network drive provided by IT services at the University of Helsinki enables you to control who can access and use your data. Personal and shared network drives are also backed up.

Links to general guides about

 

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.


Ethics and legal compliance

How will ethical issues be managed?

Describe how you will maintain high ethical standards and comply with relevant legislation. Ethical issues must be considered throughout the research life cycle, from planning to publication as well as in paving the way for future reuse. For example, following the guidelines regarding informing research participants is considered an ethical requirement for most research. Moreover, if you will manage personal or sensitive information, describe how you will ensure privacy protection and data anonymization.

Tips for best practices

  • Check whether an ethical review is required of your research project (see Ethical review of research at the University of Helsinki)
  • If your research is to be reviewed by an ethical committee, outline in your DMP how you will comply with the protocol (i.e. how to remove personal or sensitive information from your data before sharing it to ensure privacy protection, or use restricted access procedures).

Links to general guides about

 

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

 

How will copyright and Intellectual Property Right (IPR) issues be managed?

Describe who will own the data and who can issue permissions to reuse it. If you use research material or data collected or produced by a third party, consider the copyright issues and potential licenses which may affect its distribution. These issues should be solved already at the planning stage of the research project. If ownership issues have not been considered early enough in the research life cycle, sharing and reusing the data may become impossible.

Tips for best practices

  • "Principal investigators are responsible for concluding contracts on the ownership and user rights of research data at as early a stage as possible or, where applicable, before the beginning of the research project." [University of Helsinki research data policy]
  • Consider the relevant funder, institutional or departmental policy on copyrights or IPR
  • It is recommended to make all research data, code and software created within a research project available for reuse e.g. under Creative Commons, GNU, MIT or another relevant license. The recommended CC license according to open science principles is the CC-BY.

Links to general guides about

If you have any questions regarding your data management plan, please contact the UH DataSupport at researchdata@helsinki.fi OR tel. 02 941 23000.

Data sharing and long-term preservation

 

How, when, where and to whom the data will be made available?

 

Please describe how your data will be shared. Consider data sharing both during and shortly after the research project. Will all of your data be shared, or parts of it? When will the data be made available for re-use?

Linking to research products like publications and research data creates a more complete understanding of the study. If your data or parts of it will not be shared, please explain why.

Tips for best practices

  • “As a rule, research data produced under the auspices of the University of Helsinki and related to published research results are open and available for shared use. The discoverability and citability of research data must be ensured.” [University of Helsinki research data policy]

  • Early selection of a specific data sharing repository helps to prevent unpleasant surprises at the end of your research when you deposit your data.

  • Choose a data repository which uses persistent identifiers (PID) to enable access to the data via persistent links (e.g. DOI, URN).
  • Good reasons why data will not be shared might include confidentiality, trade secrets or ownership issues (license, copyright).
  • Sometimes data cannot be shared due to the unreasonable effort required for its sharing (e.g. big volumes of analog data, legacy data).
  • Too often data can't be shared because of poor data management planning in the beginning of the research project.

Links to general guides about

If you have any questions regarding your data management plan, please contact the UH DataSupport  at researchdata@helsinki.fi OR tel. 02 941 23000.

How and where the data with long-term value will be made available?

Unlike the previous question the aim of long-term preservation is to store and keep data usable and comprehensible for dozens or even hundreds of years. Digital materials can be unstable and difficult to access or use after decades in storage. A long-term preservation strategy will ensure your data can be found, understood, accessed and used in the future.

Please describe which parts of your data are valuable enough to warrant long-term preservation (over 15 years). Describe how data with long-term value will be made available. Data selected for long-term preservation will normally be submitted to a data repository or data archive.

Tips for best practices

  • If you are at a very early stage in your project and you can not yet answer this question, please explain why. 
  • Remember to check funder, disciplinary or national recommendations regarding the use of data repositories, data archives or data banks.

Links to general guides about

If you have any questions regarding your data management plan, please contact the UH DataSupport  at researchdata@helsinki.fi OR tel. 02 941 23000.

Have you estimated the costs in time and effort that go into preparing the data for preservation and sharing?

 

 Putting data into a usable format and making it meaningful to other researchers takes time and costs money in terms of software, hardware, and personnel. Read your plan and make sure that there are rows in the budget to provide for the people who manage the data as well as paying for the required hardware, software, and services.

Tips for best practices

  • Consider the additional computational facilities and resources you need access to, and estimate the associated costs.
  • How will the responsibilities for data management and costs be divided across partner sites in collaborative research projects?

If you have any questions regarding your data management plan, please contact the UH DataSupport  at researchdata@helsinki.fi OR tel. 02 941 23000.