On a day when the CIARD initiative convenes a small group in Rome to work on some principles and pathways to more accessible research outputs, we can glean useful lessons from the "checklist for guiding principles for data management" put together in the NLWRA/ANZLIC Natural Resources Information Management Toolkit:
See the Toolkit
- Don't reinvent the wheel: Expedite the project process by not reinventing the information management wheel. Look for efficiencies in data collection: Where possible data should be captured once for multiple/generic use.
- Share wherever possible: Where possible share data and foster the development of networks and partnerships.
- Present a sound business case: Data collection is expensive. There must be good business justification to support any data collection activity.
- Reduce duplication: Avoid duplication in data acquisition. Where possible team up with others.
- Look before you collect: Find out what already exists. Look for existing point-of-truth and authoritative datasets.
- Fitness-for-purpose: Undertake fitness-for-purpose assessments prior to using external datasets.
- Classification systems: Check for standards and existing classification systems or methodologies. Use existing systems and facilities wherever possible.
- Think beyond your immediate use: Manage data to maximise their value both during and after the project. Give priority to the broadest value data that are of benefit to multiple processes.
- Data custodianship: Select the most robust organisation with the broadest span of interest as the most appropriate custodian of high-value general use information. Reinforce and support data custodians and where possible negotiate access arrangements.
- Metadata: Complete metadata documentation is required for every dataset to demonstrate best practice. Metadata provides information about datasets such as accessibility, currency, completeness, fitness-for-purpose and suitability for use.
See the Toolkit