• A data policy that defines strategic long-term goals and provides guiding principles for data management in all aspects of a project, agency, or organization.
• Clearly defined roles and responsibilities for those associated with the data, in particular of data providers, data owners, and custodians.
• Data quality procedures (e.g., quality assurance, quality control) at all stages of the data management process.
• Verification and validation of accuracy of the data.
• Documentation of specific data management practices and descriptive metadata for each dataset.
• Adherence to agreed upon data management practices.
• Carefully planned and documented database specifications based on an understanding of user requirements and data to be used.
• Defined procedures for updates to the information system infrastructure (hardware, software, file formats, storage media), data storage and backup methods, and the data itself.
• Ongoing data audit to monitor the use and assess effectiveness of management practices and the integrity of existing data.
• Data storage and archiving plan and testing of this plan (disaster recovery).
• Ongoing and evolving data security approach of tested layered controls for reducing risks to data.
• Clear statements of criteria for data access and, when applicable, information on any limitations applied to data for control of full access that could affect its use.
• Clear and documented published data that is available and useable to users, with consistent delivery procedures.

More in-depth information about these practices is provided throughout the rest of this document. Additional biodiversity-related information and resources covering some of the data management activities mentioned in the document are also provided in the appendices.

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