How do you sustainably manage data?

1 Data management plan

A data management plan (DMP) is a document that outlines how you will collect, organize, store, protect, share, and preserve your data during and after your research project. A DMP can help you clarify your data goals, identify potential risks and challenges, and allocate resources and responsibilities. Many funders and journals require a DMP as part of your research proposal or publication process, but even if they don't, creating a DMP can benefit you and your research team. You can use online tools and templates to help you write a DMP, such as DMPonline or DMPTool.

2 Data quality and integrity

Data quality and integrity are essential for guaranteeing the validity, reliability, and reproducibility of research results. Data quality is about how well data meets the standards and expectations of the research domain, such as accuracy, completeness, consistency, and timeliness. Data integrity is about how well data is preserved from unauthorized or accidental changes, errors, or losses. To make sure data quality and integrity are maintained, good practices should be followed. This includes designing and testing data collection methods and instruments, performing regular data quality checks and audits, using standardized formats, codes, and labels for data, documenting data sources, methods, and procedures, backing up data regularly and securely, and implementing data security measures such as encryption, authentication, and access control.

3 Data documentation and metadata

Data documentation and metadata are essential for making your data understandable, discoverable, and reusable by you and others. Data documentation provides descriptive and contextual information about the data, such as its purpose, scope, limitations, and quality. Metadata is structured data that outlines the characteristics and features of the data, like its format, structure, content, and origin. To create effective data documentation and metadata, utilize clear terminology and definitions for your data, provide sufficient details and explanations for your data, use standardized metadata schemas and vocabularies for your data, include relevant keywords and identifiers for your data, and use tools that support data documentation and metadata creation and management.

4 Data storage and backup

Data storage and backup are essential for guaranteeing the availability, accessibility, and security of your data. Data storage refers to where and how you keep your data, such as on a computer, external hard drive, cloud service, or institutional repository. Data backup is about creating and maintaining copies of your data in case of loss, damage, or corruption. When selecting the best data storage and backup options for your data, you should take into account factors like the size, type, format, frequency and duration of access and use, cost, capacity and reliability of services, security and privacy requirements of providers, as well as the retention and preservation policies and practices of providers.

5 Data sharing and dissemination

Data sharing and dissemination are essential for increasing the visibility, impact, and reuse of your data. Data sharing involves making your data available and accessible to others, such as on online platforms or repositories. Data dissemination, on the other hand, is about how you communicate and promote your data to target audiences, such as through publications or presentations. To optimize your data sharing and dissemination strategies, you should identify the benefits and challenges of sharing and disseminating your data. Additionally, you should select reputable data platforms or networks for your data, follow the policies and guidelines of your funders, publishers, and institutions, apply the FAIR principles to make your data more accessible, use open and standardized data formats, licenses, and citations for your data.

6 Data preservation and archiving

Data preservation and archiving are essential for ensuring the long-term sustainability and usability of your data. Data preservation seeks to protect your data from degradation, obsolescence, or loss over time, while data archiving stores your data in a secure and stable environment for future access. To ensure effective practices, you should assess the value and potential of your data for future research and reuse. Additionally, determine the appropriate level and duration of data preservation and archiving for your data. Furthermore, choose trustworthy services or facilities for your data, as well as use durable and compatible formats, media, and software. Finally, monitor and update your plans and actions regularly.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?