How do you develop and implement a data management policy for your library research unit or department?

1 Assess your data needs

The first step is to assess your data needs and requirements, based on your research objectives, methods, and outputs. You should consider questions such as: What types of data do you produce or use? How much data do you generate or store? How do you organize and document your data? How do you ensure the quality and validity of your data? How do you protect the confidentiality and privacy of your data? How do you comply with the ethical and legal standards of your discipline and institution? How do you plan to share and reuse your data?

2 Define your data roles and responsibilities

The second step is to define your data roles and responsibilities, by identifying the key stakeholders and their expectations and obligations. You should consider questions such as: Who owns the data? Who is responsible for managing the data? Who has access to the data? Who can modify or delete the data? Who can use or cite the data? Who can monitor and audit the data? How do you communicate and coordinate with your data stakeholders? How do you resolve any conflicts or issues that may arise?

3 Choose your data standards and formats

The third step is to choose your data standards and formats, by selecting the appropriate conventions and specifications for your data. You should consider questions such as: What are the common or preferred data standards and formats in your field or community? How do you ensure the interoperability and compatibility of your data? How do you maintain the consistency and clarity of your data? How do you avoid or minimize the loss or corruption of your data? How do you optimize the performance and efficiency of your data?

4 Select your data tools and platforms

The fourth step is to select your data tools and platforms, by evaluating the available options and resources for your data. You should consider questions such as: What are the best tools and platforms for creating, processing, analyzing, and visualizing your data? How do you integrate and automate your data workflows and processes? How do you secure and backup your data? How do you archive and preserve your data? How do you disseminate and publish your data? How do you track and measure the impact of your data?

5 Implement your data policy

The fifth step is to implement your data policy, by applying the principles and practices that you have defined and chosen for your data. You should consider questions such as: How do you train and educate your data stakeholders on your data policy? How do you monitor and evaluate your data policy? How do you update and revise your data policy? How do you document and report your data policy? How do you enforce and reward your data policy?

6 Review your data policy

The final step is to review your data policy, by assessing the outcomes and feedback of your data policy. You should consider questions such as: How well does your data policy meet your data needs and requirements? How effectively does your data policy support your research objectives and outputs? How efficiently does your data policy use your data resources and capabilities? How satisfactorily does your data policy address your data challenges and opportunities? How beneficially does your data policy contribute to your research impact and reputation?