Core Facilities and Platforms

Centre for Journalology

Centre for Journalology

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Reporting guidelines

Our team works to develop and update reporting guidelines including CONSORT, SPIRIT, PRISMA, PRISMA-P, and STARD. We also evaluate the implementation and uptake of reporting guidelines. 

Researcher assessment

We are interested in evaluating researcher assessment and in developing, implementing, and testing novel metrics for assessing research(ers). We seek to contribute to the creation of responsible metrics that reduce research waste and promote transparency, sharing, and integrity. You can learn about some of our recent work in this space below. 

The Hong Kong principles for assessing research

Summary

For knowledge to benefit research and society, it must be trustworthy. Trustworthy research is robust, rigorous, and transparent at all stages of design, execution, and reporting. Assessment of researchers still rarely includes considerations related to trustworthiness, rigor, and transparency. We have developed the Hong Kong Principles (HKPs) as part of the 6th World Conference on Research Integrity with a specific focus on the need to drive research improvement through ensuring that researchers are explicitly recognized and rewarded for behaviors that strengthen research integrity. We present five principles: responsible research practices; transparent reporting; open science (open research); valuing a diversity of types of research; and recognizing all contributions to research and scholarly activity. For each principle, we provide a rationale for its inclusion and provide examples where these principles are already being adopted.  

More information

For knowledge to benefit research and society, it must be trustworthy. Trustworthy research is robust, rigorous, and transparent at all stages of design, execution, and reporting. Assessment of researchers still rarely includes considerations related to trustworthiness, rigor, and transparency. We have developed the Hong Kong Principles (HKPs) as part of the 6th World Conference on Research Integrity with a specific focus on the need to drive research improvement through ensuring that researchers are explicitly recognized and rewarded for behaviors that strengthen research integrity.  

The Hong Kong Principles for assessing researchers: Fostering research integrity | PLOS Biology 

Endorsing the principles

Both institutions and individuals can endorse the Hong Kong Principles.

Media interviews, resources, and dissemination tools related to the Hong Kong Principles can also be found on the World Conferences on Research Integrity page. 

Hong Kong Principles - WCRIF - The World Conferences on Research Integrity Foundation) 

Principles

Principle 1: Assess researchers on responsible practices from conception to delivery, including the development of the research idea, research design, methodology, execution and effective dissemination.

Principle 2: Value the accurate and transparent reporting of all research, regardless of the results.

Principle 3: Value the practices of open science (open research) — such as open methods, material and data.

Principle 4: Value a broad range of research and scholarship, such as replication, innovation, translation, synthesis and meta-research.

Principle 5: Value a range of other contributions to responsible research and scholarly activity, such as peer review for grants and publications, mentoring, outreach and knowledge exchange. 

Academic criteria for tenure and promotion in biomedical sciences faculties

Summary

Research Question: What is the proportion of traditional (e.g., number of publications) and non-traditional criteria (e.g., data sharing) that are present within promotion and tenure guidelines? 

Methods: 170 randomly selected universities from the Leiden Ranking of world universities list were considered for inclusion in this cross-sectional study. Two reviewers searched for guidelines applied when assessing scientists for promotion and tenure among institutions that had biomedical faculties. Where faculty-level guidelines were not available, institution-level guidelines were sought. Available documents were reviewed and the presence of traditional and non-traditional criteria was noted in guidelines for assessing assistant professors, associate professors, professors, and the granting of tenure. The percentage of criteria that were included in promotion and tenure guidelines were compared through a paired sample t-test, and exploratory regression analyses were conducted to consider factors related to the presence of traditional and non-traditional criteria. 

Study answer and limitations: Across countries, institutions with faculties of biomedicine or health sciences (n=92) focus on rewarding traditional research criteria (peer-reviewed publications, authorship order, journal impact, grant funding, and national or international reputation) as opposed to non-traditional criteria. There was substantial variability across continents on whether any guidelines were available at all with a substantial rate of non-response from specific regions. 

What this study adds: This study demonstrates that the current evaluation of scientists described within biomedical faculties promotion and tenure guidelines emphasizes traditional criteria as opposed to non-traditional criteria. This may reinforce research practices that are known to be problematic while insufficiently supporting the conduct of better-quality research and open science. Institutions should consider incentivizing non-traditional criteria. 
 

Read more about this study

Ottawa Data Champions

The Ottawa Data Champions team is funded by the Alliance’s Data Champions Pilot Project. Our goal is to develop a pan-Ottawa data champion program and research data management (RDM) training program to improve the quality of data management and sharing in biomedicine. The team represents a collaboration between the University of Ottawa Heart Institute, the Ottawa Hospital Research Institute, and the Faculty of Medicine, Library, and Office of Continuing Education at the University of Ottawa.

Our team includes content experts in RDM in different areas of medicine (e.g., pre-clinical, Indigenous, genetic sequences, clinical, routinely collected, and big data), implementation scientists, and information scientists. We have expertise in patient data privacy and, in continuing education methods, and in launching RDM education. Learn more about our team members. 

Ottawa Data Champions project

We will conduct activities in five areas: training and mentoring, promoting and advancing RDM, addressing disciplinary challenges, informing future initiatives and driving culture change.

Our activities will include launching an RDM in medicine speaker series, launching a website of discipline specific data resources (e.g., case examples of data management plans (DMPs) for different types of medical research), and implementing Data Champions program and a train-the-trainer RDM course.

Our vision is to launch this program in Ottawa with the view that it could be scalable nationally, after our initial pilot, and could be used as a core framework with customization across other disciplines. We are committed to evaluating the effectiveness of our program. 

RDM in the Canadian Landscape

Research Data Management (RDM) has become a renewed priority for the Canadian Tri-agencies (CIHR, SSHRC, and NSERC). They released a new policy which will require: 

  • Researchers to submit data management plans (DMPs) as part of grant proposals.
  • Research institutions to develop and make public RDM strategies.
  • Research institutions to develolp a goal to implement data deposits of funded research.

The Digital Research Alliance of Canada has funded Data Champions groups to build research capacity and address the educational, infrastructure, and community needs of the research community to implement the Tri-Agency RDM policy.

Would you like to become a data champion?

Data Champions are volunteers who help members of the research community properly process research data. They promote good practices on RDM and support FAIR (searchable, accessible, interoperable, and reusable) research principles. 

Any member of the University of Ottawa or affiliated institutes who is interested in research data management (RDM), sharing data, and open science, and would like to provide guidance on RDM can apply. You don’t need to be an expert to become a Data Champion. Several trainings and workshops will be provided to help you and expand your knowledge. We welcome members of different career stages and positions to apply. 

A Data Champion will advocate and promote good practices on RDM and data sharing in different ways. All the expected activities are flexible and depend on the personal availability. The activities can include: 1) providing one-to-one or group guidance and discussions on RDM; 2) promoting RDM in their institutes, groups, or departments; 3) participating on research and studies on RDM; 4) helping in the development of RDM tools and data management plans (DMP). 

  • Learning new skills in RDM and open science.
  • Collaborating with other researchers and having opportunities to be part of research projects and resource development on RDM.
  • Increasing your visibility by becoming a local expert in RDM.
  • Boosting your CV.

If you are a biomedical researcher and would like to learn more about how to join the Ottawa Data Champions Team, please provide us with your contact information here. 

Ottawa Data Champions resources

Research data management workshop series 

The Ottawa Data Champions Team organized an online workshop series on Research Data Management for biomedical researchers from September to December 2022. The weekly sessions included both generalized (e.g., FAIR Principles) and specialized training (e.g., Indigenous health data, sharing genetic sequence data) to address the diverse needs of the medical research community.

The workshop program has been developed to discuss the new policies, tools, and best practices in research data management and to address the challenges of the Canadian Tri-agencies’ new policy. The new policy will require: 

  • Researchers to submit data management plans (DMPs) as part of grant proposals.
  • Research institutions to develop and make public RDM strategies.
  • A goal to implement data deposits of funded research. 

Participants

The workshop was designed for researchers, reviewers, graduate students, postdocs, residents, and librarians involved in biomedical research. 

Registration

The webinar series is free and consists of weekly sessions from September to December, with fourteen sessions in total. The registration for each session will be open 3 weeks before the event. The registration for the first sessions will be open on August 22nd. 

Accreditation

This event is an Accredited Group Learning Activity (Section 1) as defined by the Maintenance of Certification Program of the Royal College of Physicians and Surgeons of Canada, and approved by the University of Ottawa’s Office of Continuing Professional Development. You may claim a maximum of 1.00 hour per session (credits are automatically calculated). 

Watch past sessions

External resources

UNESCO Recommendation on Open Science

The UNESCO Recommendation on Open Science provides an international framework for open science policy and practice that recognizes disciplinary and regional differences in open science perspectives. It takes into account academic freedom, gender-transformative approaches and the specific challenges of scientists and other open science actors in different countries and in particular in developing countries, and contributes to reducing the digital, technological and knowledge divides existing between and within countries. 

Digital Research Alliance of Canada – DMP assistant

The DMP Assistant is a national, online, bilingual data management planning tool developed by the Digital Research Alliance of Canada (the Alliance) in collaboration with host institution University of Alberta to assist researchers in preparing data management plans (DMPs). This tool is freely available to all researchers and develops a DMP through a series of key data management questions, supported by best-practice guidance and examples. Access DMP Assistant. 

NIH Data Management and Sharing resources

The National Institutes of Health (NIH) provides several resources on data management and sharing. The NIH website includes information about planning and budgeting for data management, best practices for data management and sharing, and different methods for data sharing and selecting data repositories.