How can you improve your data management?

1 Plan ahead

One of the best ways to improve your data management is to plan ahead and document your data management strategy before you start collecting or generating data. This will help you to identify your data needs, requirements, and responsibilities, as well as the tools and resources you will use to manage your data. A data management plan (DMP) is a formal document that outlines your data management strategy and covers aspects such as data types, formats, standards, metadata, storage, backup, security, sharing, and preservation. You can use online tools such as DMPonline or DMPTool to create and update your DMP.

2 Organize your data

Another important aspect of data management is to organize your data in a clear and consistent way that makes it easy to find, understand, and reuse. This involves choosing appropriate names, labels, and folders for your files and directories, as well as using consistent and standardized data formats, codes, and conventions. You should also create and maintain a data dictionary or a codebook that explains the meaning, structure, and origin of your data elements and variables. Moreover, you should avoid duplicating, deleting, or modifying your original data files and instead use version control systems or tools such as Git or Dropbox to track and manage changes.

3 Document your data

Documentation is the process of providing information and context about your data that enables you and others to interpret and use it correctly. Documentation can include metadata, annotations, comments, notes, references, and citations that describe the characteristics, sources, methods, quality, and provenance of your data. You should document your data throughout the research lifecycle, from the design and collection stages to the analysis and publication stages. You should also use standard metadata schemas or vocabularies such as Dublin Core or DataCite to ensure the interoperability and discoverability of your data.

4 Secure your data

Securing your data is the process of protecting your data from unauthorized access, use, modification, loss, or damage. Securing your data involves following ethical and legal guidelines and regulations regarding data privacy, confidentiality, consent, and ownership, as well as applying appropriate technical measures such as encryption, authentication, authorization, and backup. You should also assess the level of sensitivity and risk associated with your data and implement data security policies and procedures accordingly. Furthermore, you should regularly review and update your data security practices and report any data breaches or incidents.

5 Share your data

Sharing your data is the process of making your data available and accessible to other researchers or stakeholders who may benefit from or contribute to your research. Sharing your data can enhance the visibility, impact, and credibility of your research, as well as foster collaboration, innovation, and reproducibility. However, sharing your data also requires careful consideration of the ethical, legal, and practical issues and challenges involved, such as data ownership, licensing, consent, anonymization, quality, and format. You should also choose suitable platforms or repositories to share your data, such as institutional, disciplinary, or general repositories, or online platforms such as Figshare or Zenodo.

6 Preserve your data

Preserving your data is the process of ensuring the long-term availability and usability of your data for future research or reference. Preserving your data involves selecting, preparing, and transferring your data to a trusted and reliable data repository or archive that can provide adequate storage, maintenance, and access services. You should also consider the criteria and standards for data preservation, such as the significance, value, and quality of your data, as well as the metadata, formats, and documentation that support its preservation. Moreover, you should follow the FAIR principles of making your data findable, accessible, interoperable, and reusable.

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?