Data Sharing FAQ
This FAQ section is intended to supplement the JCHLA / JABSC Data Sharing Policy, please refer to the full policy for more details.
Table of Contents
Why should I share my data?
What kinds of research data should I share?
What types of data formats should I use to share my data?
Do I have to publish my data publicly as soon as I submit my manuscript to JCHLA/JABSC
Do I retain copyright of my data?
How do I make my data open and discoverable?
How do I know which repository is right for me?
What happens if I have data that is sensitive in nature
How do I de-identify my data?
Where can I find more information about sensitive data and best practices in managing that data type?
What resources can help with managing data?
RDM Resources
Why should I share my data?
Data sharing enables researchers to validate research findings, strengthen analyses, reuse data that is difficult to capture, and spark new research discoveries. For more information about why JCHLA / JABSC has implemented a Data Sharing Policy, please refer to our editorial: Embracing the value of research data: Introducing the JCHLA / JABSC Data Sharing Policy.
What kinds of research data should I share?
The JCHLA / JABSC Data Sharing Policy defines data as the materials collected and reported as evidence for the results or outcomes in either a Research Article or Program Description, including but not limited to spreadsheets, text files, interview recordings or transcripts, images, videos, outputs from statistical software, and computer code or scripts.
What types of data formats should I use to share my data?
JCHLA / JABSC recommends using open file formats so that your files can be opened using common hardware and software (e.g., .csv preferred over .xslx, when feasible).
The Open Data Handbook provides a detailed description of open formats and will help you decide which to use.
Do I have to publish my data publicly as soon as I submit my manuscript to JCHLA / JABSC?
You can set an embargo date on deposited data to prevent others from having access until after your research is complete and published. In the meantime, your data is safe, well-documented, and available exclusively to you and your research team.
Do I retain copyright of my data?
Depositing data into a repository does not generally affect copyright ownership. Depositors can specify conditions that secondary users must adhere to when accessing deposited data. Data are normally shared for research and teaching purposes only -- not for commercial purposes. You may consider using Creative Commons’ License Chooser for considerations of attribution.
How do I make my data open and discoverable?
By making your data open and discoverable, you not only increase its potential to drive new discoveries, but enable a wider audience for your research. The best way to do this is by depositing your data in a trusted data repository. Here are some how-to guides on popular data repositories used by Canadian researchers:
Federated Research Data Repository How-To Videos
Open Science Framework Training Resources:
Using the Open Science Framework to Enhance your Research Projects (Video)
Open Science Framework Help Guide
How do I know which repository is right for me?
If the above platforms are not suitable for your data, the OpenAIRE Open Data Repository Guide will help you make informed decision on which repository to choose.
What happens if I have data that is sensitive in nature?
Sensitive data may require serious consideration of privacy and laws regarding collection of personal information. Some kinds of data are sensitive, and cannot be shared for legal or ethical reasons. These can include:
- Personal identifiers
- Sensitive ecological data
- Sacred or protected cultural practices
How do I de-identify my data?
One crucial component of sharing sensitive data is de-identification. De-identification means removing identifying data from a dataset. Once a dataset has been de-identified, the dataset can be shared without disclosing identifying information.
There are several ways of approaching de-identification. Both anonymization and pseudonymization are the most common, each of which has benefits and drawbacks:
See this guide from Johns Hopkins University for resources and tools on de-identification:
For more information about what sensitive data sharing and how to maintain study participant privacy, please see guidance from the Personal Information Protection and Electronic Documents Act (PIPEDA).
Where can I find more information about sensitive data and best practices in managing that data type?
First Nations Principles of OCAP™ (ownership, control, access, and possession)
Data sharing for qualitative research:
Tsai AC, Kohrt BA, Matthews LT, Betancourt TS, Lee JK, Papachristos AV, Weiser SD, Dworkin SL. Promises and pitfalls of data sharing in qualitative research. Social Science & Medicine. 2016 Nov 1;169:191-8. https://doi.org/10.1016/j.socscimed.2016.08.004
ICPSR Guide to Social Science Data Preparation and Archiving
What resources can help with managing data?
Practicing good RDM can help you:- meet funding agency requirements;
- write more competitive grant applications;
- get credit for your data and increase its impact and visibility;
- encourage the discovery and use of your data to explore new research questions;
- improve your data's accuracy, completeness, and usability;
- ensure long-term preservation of data for future researchers
- comply with ethics and privacy policies.
RDM Resources
Your institution may have data management services including workshops and consultations. We recommend the following resource from the Portage Network to help you get started:
DMP Assistant (software to develop a data management plan)
If you have further questions, please contact the JCHLA / JABSC Editor in Chief (editor@chla-absc.ca).