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Data Management

Data are products of research and proper data management allows for reusability, reproducibility, and repeatability. Data Management Plans are often required by funding agencies and research departments at the University of Louisville. Data Management Considerations During the Data Life Cycle:1. Plan: Determine what data will be collected or created and how it will be managed and made accessible throughout its lifetime. 2. Collect: Identify data collection methods and create standards for systematic backups and organization of the data files. 3. Assure: Develop protocols to assure the quality of the data. 4. Describe: Create documentation and metadata needed for the interpretation and use of the dat a. 5. Preserve: Identify appropriate repositories for long-term storage. 6. Discover: Develop mechanisms for sharing the data and address any sharing restrictions in regards to privacy and embargo periods. 7. Integrate: Determine protocols for data integration from multiple sources. 8. Analyze: Ensure the integrity of the data remain intact during analysis, transformation, or modeling. Questions that shape your data management plan: What types of data will be produced? How will the data be archived for preservation and long-term access? What steps will be taken to protect privacy, security, confidentiality, intellectual property, or other rights? If you allow others to reuse your data, how will data be discovered and shared? What standards will be used for documentation and metadata? Watch the video to learn more about creating your data management plan with D M P Tool.

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