Pre-award - Advice, forms, & templates
Faculty members in the Faculty of Social Sciences interested in applying for external research support or grants should discuss their plans with the Faculty’s Research Support Team. The Research Support team also manages a folder of
- ROADS Guidance Documents,
- Quick Guides,
- related templates (e.g., for budgets) and forms (e.g., the GAAP proposal routing form) and sample applications
Information is included for various SSHRC grants, including
- Connection,
- Insight Development (IDG),
- Insight (IG),
- Partnership Development (PDG) and
- Partnership Grants (PG).
To receive a password to access these resources, please email Cynthia Belaskie, Research Support Facilitator, at belaski@mcmaster.ca from your McMaster email address.
Pre-award Data Management Plans
Empirical research that involves the collection or creation of digital data should be guided by the Tri-Agency Statement of Principles on Digital Data Management, paying particular attention the Expectations, which include
- data management planning;
- balancing openness and other “commercial, legal and ethical obligations”; and
- following best practices in storing, archiving, sharing, and citing research data.
The Portage Network provides a number of tutorials and resources related to research data management, including an interactive tool to build research data management plans.
The SSHRC endorses these principles in its Research Data Archive Policy.
Research - Ethics & privacy
For research involving humans, researchers should consult the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans. The McMaster Research Ethics Board has additional guidance regarding research with humans.
Research involving humans and digital data should pay particular attention to Chapter 5, “Privacy and Confidentiality” of the Tri-Council Policy. The Tri-Council also has an interpretation document related to privacy and confidentiality.
Research - Document Storage and Security
Research data is central to any research project and must be securely stored and backed up. Keeping at least three copies of research data will help ensure that data is kept safe and reduces the risk of data loss. It is good practice to keep physical copies like CDs or DVDs in addition to electronic storage. It is also important to consider personally identifiable or sensitive information when storing data. If your research data contains sensitive or restricted information, it must be encrypted and secured.
McMaster Faculty and Staff all have access to MacDrive, which is a privately hosted, secure, cloud storage solution offering features similar to but without the potential security or legal concerns commercial providers. Other potential users will also be able to access MacDrive upon request from a faculty or staff member. This can include student staff members, RAs, TAs, community members, collaborators, and anyone else with whom you need to securely share your research data.
Data Collection & Availability
CRESS coordinates the activities of several labs that have data collections available for researchers, including the RDC and SEAL, McDSL has interviewing and focus group facilities as well as an experimental lab. Other labs, including CRUNCH, the Sensory Ethnography Lab, and Sustainable Archaeology Lab, have research equipment available for use by researchers.
The University Library has a data collection and maintains a membership in the Inter-University Consortium for Political and Social Research, which maintains a large data repository (login required). The Library also has a data service, which helps researchers find relevant research datasets and provides research data management advice.
Data Analysis
Facilties
CRESS coordinates the activities of several labs that have facilities for data analysis, including the RDC and SEAL. UTS-managed labs for students also have specialized software for data analysis, including Stata, SPSS, and R.
CRESS also organizes a speaker series on a range of topics related to qualitative, quantitative, or mixed-method empirical social science research.
Training
While CRESS hosts a Research in Focus series and occasional workshops to support training in social science data analysis methods, all McMaster affiliated students, faculty, and staff can access Lynda online tutorials for free. Lynda has several data analysis related modules, including learning paths for Introduction to Data Science, R for Data Science, Python for Data Science, and Data Visualization tools, among others.
Data analysis workflow
Similar to SSHRC data sharing recommendations, scientific journals sometimes require researchers to make publicly available their data and analysis scripts to the extent allowed by ethics protocols. These resources provide some guidance for researchers interested in establishing replicable workflows:
- General principles: Wilson, et. al. 2017. “Good enough practices in scientific computing.” PLOS Computational Biology.
- Stata: Long. 2009. The Workflow of Data Analysis with Stata. Stata Press.
- R: Grolemund and Wickham. 2017. R for Data Science. O’Reilly Press or Racine. 2019. Reproducible Econometrics Using R. Oxford University Press.
Knowledge mobilization - Research repositories
Researchers can often increase the accessibility and impact of their work by depositing copies of research papers or articles in open access repositories. Since 2015, Tri-Council policy requires that funded research be publically accessible. If the work has been previously published, search the SHERPA/RoMEO database to determine a publisher’s open access policies for self-archiving.
Social science researchers should consider two open access repositories for their work:
- MacSphere, McMaster’s institutional repository, which includes pre-prints, post-prints and final versions of journal articles as allowed by publishers. With some exceptions, MacSphere is fully open for everyone to access and read, with infrastructure that makes items fully searchable using search engines such as Google Scholar.
- SocArXiv, is a non-profit, open access repository for social science researchers to publish pre-print versions of their articles.
The SSHRC Research Data Archive Policy requires that research data be made publically available, within the constraints of research ethics requirements. Some scholarly journals also expect authors to make their data and analysis scripts available for replication.
For sharing and archiving data with the public, the library recommends the Scholars Portal Dataverse. SEAL has facilities for archiving and controlling future access to private or sensitive data.
Additional resources include:
- Transparency & Openness Guidelines from the Center for Open Science
- Christenson. 2016. Manual of Best Practices in Transparent Social Science Research. Berkeley Initiative for Transparency in the Social Sciences.