News

02-2022- We are currently seeking senior researchers at or near retirement, or organizations, with legacy datasets to take part in our program. We will match you with a trained graduate student who will collaborate with you to archive your dataset using best practices. Contact any of the organizers to discuss the suitability of your dataset, see also criteria [below] and FAQs [below].

09-2020 - Find out more about the Living Data Project by viewing this information session presentation here.  

Organizers

Diane Srivastava, CIEE Director and Professor UBC Zoology
Mary O’Connor, CIEE Deputy Director, Assoc. Professor UBC 
Sally Taylor, Research Data Librarian and Adjunct Professor, UBC 
Timothée Poisot, Assistant Professor, Biological Sciences, Université de Montréal 
Kerri Finlay, Associate Professor, Biology, University of Regina 
Raymond Ng, Director Data Science Institute, Professor Computer Science, UBC
Jason Pither, Co-lead Fostering Open Science at UBC, Associate Professor, Biology, UBC Okanagan
Jennifer Sunday, William Dawson Scholar and Assistant Professor, Biology, McGill University
Laura Pollock, Assistant Professor, Biology, McGill University
Gavin Simpson, Adjunct Professor, Biology, University of Regina
Éric Harvey, Assistant Professor, Biological Sciences, Université de Montréal
Sandra Binning, Assistant Professor, Biological Sciences, Université de Montréal 
Dominique Roche, Marie Curie Global Fellow, Carleton University & Université de Neuchâtel

post-doctoral fellows

Sarah Amundrud, University of British Columbia (2020)
Ellen Bledsoe, University of Regina (2020-2021)     
Joseph Burant, Université de Montréal/McGill University (2020- )
Gracielle Higino, University of British Columbia (2021-)
Mike Lavender, University of Regina (2021-)  

Apply to host a Data rescue internship

Application deadline: April 1, 2022 for internships to start on or after October 1, 2022.

Application deadline: November 1, 2022 for internships to start on or after May 1, 2023.

Email completed applications to:
​ciee-icee at biodiversity.ubc.ca

living data project articles
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Read this article about ​the career and contributions of renowned ecology researcher Dr. Tony Sinclair.  As part of the Living Data Project,  PhD student Francisco Henao Diaz worked with Tony to preserve decades of Serengeti bird data.

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Read this article about the career and contributions of ecology researcher Dr. Roy Turkington.  As part of the Living Data Project,  PhD student Sandra Emry worked with Roy to preserve data on understory plants in the Yukon.
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Read this article about marine bird surveys in Stanley Park, Vancouver, BC, dating back to 1995.  As an intern of the Living Data Project PhD Student Jenny Munoz assisted with this comprehensive dataset.
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Read this article about the Green River Project which ran from 1945 to 1959 in northwestern New Brunswick following a widespread spruce budworm outbreak.   As an intern of the Living Data Project MSc Student Skye Butterson assisted with this dataset.

living data project working groups

Detecting and attributing synchrony in cross-ecosystem community dynamics using long-term observational data in coastal oceans
Group leaders: Dr. Jarrett Byrnes (University of Massachusetts Boston) and Dr. Kylla Benes (University of Montana)
Working group dates: 01 March to 05 March 2021
Project description
Finding indicator species by assessing the utility of sampled abundance indices 
​Group leaders: Dr. Robin Freeman (Zoological Society of London), Dr. Jessica Currie (WWF-Canada), and Dr. Valentina Marconi (Zoological Society of London)
Working group dates: 30 August to 03 September 2021
Project description
The Living Data Tutorials: Data Packages for Teaching in Ecology and Evolution Working Group 
​Group Leaders: Jennifer Sunday (McGill University) and Joey Bernhardt (McGill University)
Working group dates: 4 April to 8 April 2022
Project description

living data project information

Criteria for legacy datasets
1.     The dataset includes biological data that is relevant to ecology, evolution or environmental science. The dataset does not need to be entirely biological; physical and chemical data is acceptable if in the context of an ecological or evolutionary process. For example, water chemistry is an important part of understanding aquatic ecology.
 
2.     The dataset should be important in one of the follow ways: (1) extensive in either space or time (e.g. bird surveys over more than a decade, or national surveys of caribou density); (2) describes a study that was ground-breaking in the history of science; (3) concerns a species or ecosystem that is considered at risk in Canada, or of high cultural or societal value.
 
3.     Priority will be given to datasets that concern a Canadian species or ecosystem, or have been collected by a Canadian researcher or Canadian organization.
 
4.     The owner of the dataset commits the data to be permanently archived, and open and accessible. We realize that some dataset owners may need to temporarily delay the publication of their data, and in such cases we may consider a short-term embargo.​

Frequently Asked Questions by data owner
1.     Is the Living Data Project setting up its own repository?
No. There are now a large number of excellent data repositories that have been set up by government agencies, university libraries, synthesis centres, non-profit organizations and international consortia. We will work with you to decide what repository fits your dataset best – this is your data, and you can decide on its home as long as the repository meets our criteria for long-term digital archiving. We also realize that some employers (e.g. Canadian government) mandate particular repositories.
 
2.     What if the data owner is no longer alive or the data belonged to a defunct organization?
No problem. In this case, the intern will be doing a lot of data forensics, piecing together the meaning of each variable by cross-referencing other sources or by interviewing contemporaneous researchers.
 
3.     If I make my data public, won’t other people use it erroneously because they do not understand the context?
Misuse of data is a valid concern, but we have an important tool to combat it: metadata. You and your intern will work together to develop detailed descriptions (metadata) of each variable in the dataset to explain the complexities of each variable. Furthermore, we have the ability to create additional variables that describe any heterogeneity in data quality or context. The goal is to provide enough information about the data that no further explanations are needed to use it.  
 
4.     I can’t make my data public yet because I still have publications planned.
Just because your data is archived doesn’t mean that you cannot publish papers based on it. In fact, many journals now required data to be properly archived before accepting a manuscript for publication. You may also worry that another researcher will ‘scoop’ you on your own data. This is often more fear than fact. Instead, what tends to happen when other researchers see your data carefully organized is that you receive more invitations for collaborations.
 
5.     If I make my data public, won’t I lose credit for all the time I invested in collecting this data?
Not necessarily. You can decide the type of Creative Commons open licence associated with your archived dataset. If you choose a CCBY licence, future researchers are required to acknowledge you as the data collector.
 
6.     I already have planned to give my data to a younger colleague so I don’t need to archive it.
That’s great that you have found such a colleague. However, it would be much more valuable to pass on this dataset if it was already properly documented, validated, organized and archived – otherwise they will be stuck doing this without your valuable input or, even worse, not at all. We would be happy to work with both you and your junior colleague to design your data archiving project so that it meets both of your needs as well as that of the greater research community.
 
7.     If my data is in [database program X], isn’t it already archived?
Unfortunately not. If it isn’t in a data repository, in a simple machine-readable format like a .csv or a .txt file, then it isn’t futureproof. Any data held in a proprietary software package may become unreadable if that package is no longer supported by the software company or the company ceases to exist. Remember those Lotus 1-2-3 files you used to have? Good luck opening them.
 
8.     What will I get out of this?
A lasting legacy for your research career, and the satisfaction that your data will continue to inform future generations of scientists. You will also have a career summary posted on the CIEE – Living Data Project website honouring your achievements and the importance of your dataset.

Available internships
Available Internships for Summer 2022 have been posted on the OSF website here.
Courses, workshops and online training
The Living Data Project offers these four one-month courses, all presented virtually in fall 2021.  

To register click here.

Productivity and Reproducibility in Ecology & Evolution - Sept 7- Sept 30, Tu Th 8:00am-9:30am PDT / Tu Th 9:00am-10:30am CST / Tu Th 11:00am-12:30pm EDT

Scientific data management for ecology and evolution - Sept 7 - Sept 30, Tu Th 10:00am-11:30am PDT / Tu Th 11:00am-12:30pm CST / Tu Th 1:00pm-2:30pm EDT

** the above two courses satisfy in part the requirements for the CIEE “Certificate in Data Management and Reproducible Research.” 

Synthesis Statistics for Ecology and Evolution - Oct 5 - Nov 4  (no class Oct 18-22), Tu Th 8:00am-9:30am PDT / Tu Th 9:00am-10:30am CST / Tu Th 11:00am-12:30pm EDT

Scientific collaboration in Ecology, Evolution and Environmental Science - Oct 5-Nov 4  (no class Oct 18-22), Tu Th 10:00am-11:30am PDT, Tu Th 11:00am-12:30pm CST, Tu Th 1:00pm-2:30pm EDT​
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**the above two courses satisfy in part the requirements for the CIEE “Certificate in Synthetic and Collaborative Science.”
 
Eligibility. These courses are open to graduate students conducting thesis research in ecology, evolution or environmental science at any CIEE member university (see list here) and CSEE members (graduate students who are CSEE members themselves or who have a faculty advisor who is a CSEE member).  Several courses also require basic coding skills (see syllabus for each course). Information for course registration is being circulated internally by your university.

Obtaining credit for courses. Course credits are currently being offered for students from these universities: McGill, Université de Montréal, UBC (Vancouver and Okanagan) and University of Regina. Students in other CIEE universities seeking course credits should contact their CIEE Management Board representative (here). Normally each module is 1 credit. In universities without 1-credit graduate courses, students may need to bundle three modules into 3 credits. 

If you are not at a CIEE member university. If you are a member of the Canadian Society for Ecology and Evolution (CSEE) or have a Faculty Supervisor who is a member you can apply to take these courses. If would like to apply for a three course Directed Studies credit at your university, you will need to find and request a Faculty member at your university to arrange for this.

Certificate program
Why?
Dramatic shifts in the scientific workflow mean that Canadian graduate students urgently require high-demand skills from data management, reproducible research, scientific synthesis and team science in order to remain globally competitive. However, there is currently no formal program for certification in these competencies. Our nationwide certificate program will provide highly sought-after qualifications for both the Canadian and global job market.

The certificates.
The CIEE offers two certificate programs: Certificate in Data Management and Reproducible Research and Certificate in Synthetic and Collaborative Science. Each Certificate program consists of two courses (12 hours each) and one immersive activity (either a data rescue internship or working group participation). Both certificates also require EDI training and participation in a workplace transition evening. You will be mentored by Living Data Project leaders throughout your certificate, and we will help you discover other customized training that can complement these elements. 
Certificate in Data
Management and
Reproducible Research
Certificate in Synthetic and
Collaborative Science
Immersive activity
(mandatory)
Data rescue internship
Working group participation
Workforce transition
evenings (mandatory)
Roundtables with representatives from non-academic sectors
EDI training (mandatory)
List of trainings
National workshops
(optional)
Data management, synthesis, collaboration skills
Customized training
(university-specific
courses, QCBS, Mitacs) (optional)
Data wrangling (UBC BIOL 548O, UBC STAT 45, Software Carprentry), high-performance computing (UdeM DDES), statistics (UofR BIOL 440, UBC FRST 507C, QCBS)
Scientific writing (UBC BIOL548I, McGill Graphos Program, Mitacs), scientific communication (UBC BIOL 548L, Mitacs, UofR BIOL 803), project management (Mitacs, McGill Leading effective discussions).
​Eligibility. 
Funding for data rescue internships is currently restricted to graduate students in McGill, Université de Montréal, UBC (Vancouver and Okanagan) and University of Regina. Interested students from other universities currently will need to find independent funding for the data rescue internship. Working group participation and technical and professional skills courses are open to graduate students in any CIEE member university. Students who have completed coursework in a certificate program will be prioritized for internships and working groups. We recognize that some students may have constraints (e.g. research-related, family-related, etc.) around their ability to fulfil all certificate elements in a certain order; in such cases, we can be flexible and/or consider equivalencies in training – please contact us to discuss.

Certificate Application.
Please send a single PDF listing all the mandatory and optional training  you have completed including the dates of completion for each training to [email protected].
Please specify which certificate you are applying for and include your full name as you would like it to appear on the certificate.
​We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC).
Cette recherche a été financée par le Conseil de recherches en sciences naturelles et en génie du Canada (CRSNG).

We acknowledge the support of this research project the by the University of British Columbia, McGill University, the Université de Montréal, and the University of Regina.