We care about enabling proper data management planning for everyone. So, we created a starter plan for small teams for FREE. You can start planning today!

There is really no better way to learn about something than to try it yourself. And you can do just that with FAIR Wizard. See how:

Missing data can lead to flawed conclusions. It’s important to ensure your datasets are complete and contain all necessary information to drive reliable analysis and decisions. • Establish clear data collection guidelines to capture all required fields. • Use data profiling tools to identify and fill gaps in your datasets. • Regularly audit datasets to ensure no critical data is missing.

When you both work with data but in completely different ways.

Collecting and analyzing data requires setting up structured workflows and organizing your data systematically. Don't forget to create and maintain metadata for easy management. • Set up data collection processes • Organize and structure data • Create and maintain metadata

Duplicate data can create confusion and disrupt analysis. Ensuring your data is unique prevents errors and ensures you get accurate insights without unnecessary repetition. • Implement deduplication tools that automatically flag and remove duplicate entries. • Set unique constraints in databases to prevent the same data from being entered multiple times. • Regularly audit your datasets for duplicates and resolve issues promptly.

Processing and documenting data ensures it's usable and understandable, but it’s resource-intensive. Consider these costs: • Data cleaning and transformation • Metadata creation • Time and software for data analysis Remember, proper processing and documentation are key to maintaining data quality.

Do you want to easily incorporate your local data into Data Management Plans? Say no more and check out Integration Hub!

Maintaining data integrity is crucial for trust and accuracy. Protect your data from corruption or unauthorized changes to ensure it remains reliable and secure for use. - Use encryption and secure access protocols to protect data from unauthorized access. - Implement regular backups to safeguard against data loss or corruption. - Audit data access and changes regularly to ensure integrity is maintained.

Where do you store your research data?

Metadata is vital. Without it, data loses its value—how can we effectively work with data if we don’t know where it’s stored or how it’s structured? Always ensure that your data is supported by thorough and clear metadata.

Transform your data into a strategic asset with unified Data Management Planning! Discover how a structured approach can drive efficiency, compliance, and collaboration 👇

Easy access to data is key to making timely decisions. Ensure your data is stored in a way that authorized users can quickly find and use it when needed, without unnecessary barriers. • Use cloud-based storage and tools that allow for easy and secure access to data. • Implement role-based access controls to ensure data is available to those who need it. • Organize and label data logically, with intuitive interfaces for easy navigation and retrieval.

A Data Steward’s Friday Checklist: ✅ Ensuring data integrity ✅ Reviewing metadata ✅ Cleaning up datasets ✅ Ready for a weekend of well-deserved rest!

Don’t create your Data Management Plans alone—research is a team effort! With the FAIR Wizard, you can collaborate and create your Data Management Plans together. #FAIRData #ResearchCollaboration #DataManagement #Teamwork #OpenScience #FAIRWizard

Do you often find yourself entering the same information over and over? Connecting your tools to share data effortlessly is essential. It does not only saves time but frees you up to concentrate on more important tasks, rather than on repetitive data entry. Do not copy-paste. Integrate.

Think data is only about collecting numbers? Not quite. Data stewards use detailed plans to map out where data lives, who uses it, and how it stays safe. It’s the difference between a data disaster and data done right.

Do you have a data steward in your institution?

Make your data easier to reuse by avoiding proprietary formats. For instance, consider how many external dependencies are required to read a table in Python: • CSV: 0 • XLSX: 14 Open, standard text-based formats are the best way to ensure your data remains accessible in the future.

Research data management isn’t just about organizing files. It’s about unlocking possibilities. Think outside the box and create systems that empower discoveries.

🔒Balancing Accessibility & Security in Data Stewardship A core part of data stewardship is balancing data accessibility with security. This means providing teams with the insights they need while keeping sensitive information protected.