Knowledgebase: Research
Research Data Management
Updated: 13 July 2020 03:29 PM

Research Data Management



Research Data Management (RDM)  refers to the creation, storage, access and preservation of data produced from a given investigation.

Good data management practice allows reliable verification of results and permits new and innovative research built on existing information. This is important if the full value of public investment in research is to be realized. Canadian Government policies are in the process of being developed and policies such as the Tri-Agency Research Data Management Policy are still in the draft stage as of May 26, 2020. As such, Canadian digital data management strategies, concepts and techniques are in a state of development.

DRAFT Tri-Agency Research Data Management Policy

RDM helps ensure the protection of data during a research project and beyond, helping to meet the increasingly stringent requirements of good research ethics and reproducibility.


What is Research Data?

  • Primary sources supporting research, scholarship or artistic endeavours
  • Can be used as evidence to validate findings and results
  • May take the form of experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, or repurposed data
  • All other digital and non-digital content have the potential to become research data


The Research Data Lifecycle

Plan > Create > Process > Analyze > Disseminate > Preserve > Reuse

Research data management involves the active organization and maintenance of data throughout the research process, and suitable archiving of the data at the project’s completion. It is an on-going activity throughout the data lifecycle.

Plan: Planning can include reviewing existing data sources, addressing informed consent, considering costs, and preparing a plan.

Create: Researchers produce data (experiment, observation, measurement, simulation) and/or collect and organize third-party data and materials. Metadata and related materials are captured and created.

Process: Data is converted to digital format (transcribed, converted, digitized, curated) according to quality assurance standards. Data is checked, validated, cleaned, recoded, versioned, and as needed, anonymized. All these processes are documented, and the data is described using the appropriate discovery metadata standard.

Analyze: Data is interpreted and analyzed to produce research findings, publications, and intellectual outputs. Data sources are cited.

Disseminate: Access rights are confirmed (ethics and intellectual property considerations). The data, along with user documentation and metadata, are made accessible, e.g. on a public domain server, or in a controlled repository.

Preserve: Data is saved to formats that conform to curation best practices, user documents and discovery metadata are created, a Digital Object Identifier (i.e. DOI) is added and data is linked to any published products, consideration is given to Security and Intellectual Property.

Reuse: Potentially useful data, user documentation and metadata are located and obtained. Secondary analysis is conducted after any necessary data transformations are complete. Transformations are documented and data sources are cited.

Data Management Planning and the DMP Assistant

DMP Assistant is a Canadian bilingual tool for preparing data management plans (DMPs). The tool follows best practices in data stewardship and walks researchers step-by-step through key questions about data management.

DMP Assistant is designed to meet the Data Management Plan recommendations of these Canadian funders:

Canada Foundation for Innovation (CFI)
Canadian Institutes of Health Research (CIHR)
Natural Sciences and Engineering Research Council (NSERC)
Social Sciences and Humanities Research Council (SSHRC)

Portage provides a collection of guides to assist researchers:


Research Data Storage

The link below provides details of commonly used research data storage systems available to researchers at OCAD University.



Encryption is the process of encoding digital information in such a way that only authorised parties can view it. It is especially useful when you are transmitting personal or confidential data.

When you encrypt a file, the information it contains is “translated” into meaningless code. To translate this code back into meaningful information a key is required. Attacks with ransomware such as the Locky virus ("Locky", 2017) have demonstrated that recovering information from encrypted files without the key is nearly impossible. It is therefore extremely important that you do not lose the key to decrypt your files.

IMPORTANT! If you lose the the key to decrypt your files you have lost your data forever.

Do: encrypt confidential data, especially before transmitting it online, uploading it to the cloud, or transporting it on portable devices. When working in a team, make sure that the key can be accessed by everyone who needs to access it (but only those people).
Do: ensure that you do not lose the key to decrypt your files, e.g. by keeping it in a sealed envelope in a secure location such as a safe room.

Encryption software

Commonly used encryption software includes:

Standard on selected editions of Windows. For the encryption of disk volumes and USB devices.

Standard on Apple Macs. For full disc encryption.

PGP (Pretty Good Privacy) Encryption utilities.

There are free/open source (e.g. Gnu Privacy Guard (GnuPG)) and commercial (e.g. by Symantec (Symantec Corporation)) programs available.

If you are unfamiliar with PGP/GPG you will want to have a look at this guide.

GPG free/open source

PGP commercial by Symantec


There are commercial programmes (e.g. by Symantec (Symantec Corporation, 2017)) and free/open programmes (e.g. Gnu Privacy Guard (GnuPG, 2017)) available.

VeraCrypt (n.d.)
Multi-platform encryption software (Windows, Mac and Linux). For full disk and container encryption.

Further resources:


Research Dissemination and Repositories

Making your research available increases exposure to your work, which can lead to increased citation of research overall. Research data are a valuable resource, usually requiring much time and money to be produced. Many data have significant value for usage beyond the original research. The ease with which digital data can be stored, disseminated and made easily accessible online to users means that many institutions are keen to share research data to increase the impact and visibility of their research. 


Institutional Repository

Open Research ( is a digital archive managed by the University Library to collect, preserve, and distribute scholarly and creative output generated by the OCAD U community.


Domain Repository

A repository search tool for domain repositories is available from DataCite

 And another from the Registry of Research Data Repositories


Federated Research Data Repository (FRDR)

The FRDR is a platform for Canadian researchers to deposit and share research data, and to facilitate discovery of research data in Canadian repositories. FRDR is particularly suitable for archiving and sharing large data sets (300 GB or 25,000 files).


 Which repository should I use?

This Data Deposit Tree provided by UBC can help you decide which type of repository you should use for your research.




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