Data Management Plans

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.

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).