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Open Science Policy


A core goal of the Hakai Institute is to generate long term ecological data.  Due to the long time frame of this type of research, datasets are created by multiple researchers at different times and on different components of an integrated ecosystem.  As such, data sharing across research projects and datasets is critical to achieve a full picture of the ecosystem, and detect long term patterns of change.

We are committed to ensuring that all the data generated with Hakai funding is made available to the broader research community and downstream users. To do so, we practice Open Science; the practice of science in such a way that other scientists, and the public, can collaborate and contribute, for non-commercial purposes. To do so, research data, methods documents, publications and other research processes are freely available under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods.


To implement Open Science, we outline our policy and standards for making data open and accessible below. We have adopted the NSF’s policy for data reporting and have created this document by modifying the NSF Directorate of Biological Sciences Data Management Reporting requirements and the US LTER Data policies to make sense within the Hakai Institute’s operational standards.

Making data open and accessible. We understand that studies will vary with regard to what types of data can be shared, with whom the data can be shared, and the time needed to get data into a shareable format after collection. Therefore, we expect each study to have its own data management plan which describes the nature of the data, any restrictions with data sharing, proper attribution of the dataset and timeline to make the data public.

Sharing and Attribution

We encourage the sharing of all data, when appropriate. Understandably, some data will never be appropriate for public distribution (e.g., data on endangered species, from culturally sensitive areas, on personal interviews, etc.). Data of this nature should be described in the data management plan, including the means to ensure this data remains private, including any permission-based terms attached to this type of data.

Attribution of open data. To ensure that shared data respects and acknowledges the creators of the data and the intellectual property associated with the data, datasets and publications should stipulate plans for on-going attribution of data in their data management plan.  Liberal open licenses (e.g.Creative Commons licenses, amongst others) are one mechanism that allow other scientists and the public permission to read and re-use the publicly funded research. Using these licenses, the creators of the data retain copyright, while allowing others to copy, distribute, and make some uses of their work, non-commercially. Hakai will ensure researchers get the credit they deserve for their work.

Distribution and Storage

Data sharing timeline: Research resulting from Tula Foundation funding (direct and in-kind) should be prepared and submitted for publication within a reasonable amount of time (usually within two-three years of initial data collection).  Along with the publication of research, the accompanying primary data created or gathered in the course of Hakai-affiliated work, along with essential metadata should be shared in the public domain.

To enable broadly dissemination with unrestricted access and reuse of all research and underlying datasets, we will work with researchers to make the data and publications discoverable, accessible and open online.  The Hakai Institute will provide free storage on the Hakai server for datasets and will advertise those datasets on the .  If journals require that accompanying data be submitted to another data storage service, details on that dataset and where it resides should be provide to Hakai in order to promote public access from our site.

Whether stored on Hakai servers or elsewhere, data will become a reflection of the quality of scientific research at the Hakai Institute.  We ask that you follow our guidelines while preparing your data and metadata package and recommend that you have a Hakai representative check the quality of the dataset before submission (e-mail:


The Hakai Institute is committed to respect and acknowledgment of all research partners producing data and research for the public domain. In addition, attribution to the Hakai Institute for all shared datasets should be sought. Open licences are one way to acknowledge the creation of datasets, and ensure attribution is passed on with the dataset. Likewise, if data is stored on Hakai servers, the creators of the dataset and instructions for communications with content creators, will be linked to data access.

Support and Authorship

The Hakai Institute supports inclusive co-authorship that accurately reflects the contribution of those involved in publications and datasets. The authorship plan should be discussed alongside data management plans. Formal acknowledgment of research support by the Hakai Institute and/or the Tula Foundation must also accompany any publication, report, presentation or media communications.

For all researchers who receive financial support from the Tula Foundation directly or via in-kind donations from the Hakai Institute, the Hakai Institute strongly supports the creation and implementation of a Data Management Plan (DMP) articulating goals for collection, management, and dissemination of data. Data management plans should describe the nature of the data and specific strategies for making research data publically available.

In collaborative proposals or proposals involving multiple sub-projects, the lead PI is responsible for the DMP for the entire project; i.e. the DMP must cover all the various data types being collected by all collaborators. The DMP should be developed with a Hakai Science Lead to describe how PIs will manage and disseminate data generated by the project in sufficient detail to enable evaluation of the plan.

Data Management Plans

The Hakai Institute recognizes that each program and research project may have its own data management standards, and that accepted norms are changing as science becomes increasingly multidisciplinary. Therefore, each DMP should be appropriate for the data being generated and reflect the best practices and standards in the area of research being proposed.

DMP components include, but are not limited to, the following components

  1. Overview of the data that will be collected, anticipated formats, and essential metadata.

  2. Description of QA/QC procedures and where the data will be stored throughout the research program and after its completion.

  3. Description of  how the data will be disseminated (anticipated downstream publication and media venues) after completion of the project. See Nature’s example Data Availability Statement.

  4. Description of the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate).

  5. Description of the roles and responsibilities of all parties (including university and Hakai Institute staff) with respect to the management of the data, communications about the data, and authorship of material based on the data, including a description of primary authors and potential co-authors for anticipated publications

  6. Identification of foreseen downstream users of the data, and restrictions on commercial use of the data or public use of the data (for culturally and ecologically sensitive datasets).