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FAQ
About the Playbook Template
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Frequently Asked Questions (FAQ)

The answers to these questions may vary based on the resources, policies, and capacities of different organizations. Always refer to your institution’s guidelines and data management policies for specifics.

1. Will you re-use existing data for this research?

  • This depends on your research. If you're re-using data, ensure it is properly cited and conforms to data-sharing agreements. If you're generating new data, detail the types, formats, and volumes of data expected, such as species occurrence records or environmental data.

2. How much data storage will your project require?

  • Estimate your storage needs early on. For example, raw sequencing data may generate several terabytes (TB) of data. Image and sound files can vary significantly in size based on resolution and length. Your institution should have guidance on where to store this data, such as on institutional servers or cloud-based solutions.

3. What metadata and documentation will accompany the data?

  • Essential documentation may include a Data Management Plan (DMP), README files, and codebooks. Metadata standards like Ecological Metadata Language (EML) and Darwin Core (DwC) are common for environmental and biodiversity data.

4. How will you store and back up data during the research?

  • Data storage options include institutional networked storage, cloud-based services, or repositories like Zenodo, GitHub for smaller datasets. Backup procedures should be clearly defined, ensuring data is regularly copied to secure storage locations. Also check with your national resources as well (often provided by a science foundation or a similar organization).

5. How will issues regarding personal information and intellectual property (IP) rights be managed?

  • If handling personal data, ensure compliance with legal frameworks like GDPR. Define data ownership clearly, especially when collaborating with multiple institutions. Institutional data-sharing agreements should outline how IP is protected.

6. How will data be selected for long-term preservation?

  • Select data for long-term preservation based on scientific value, uniqueness, and reusability. Data repositories such as GBIF and ENA can be used, with licensing arrangements like Creative Commons (CC-BY).

7. What data will be made available for re-use?

  • Data such as species occurrence or environmental data will often be made available under licenses that encourage re-use, like Creative Commons. Ensure this data is well-documented and accessible through appropriate repositories.

8. What data management costs should be expected?

  • Data management costs can include data curation, repository fees, and training. Some costs, such as cloud storage or software licenses, can be minimized by using open-source tools or institutional resources. Check with your organization's data and ICT support for guidance.