Data Management Lab: Session 4 Review Outline
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The document outlines the curriculum for the IUPUI University Library's Center for Digital Scholarship Data Management Lab in Spring 2014, focusing on essential aspects of research data management (RDM). It covers topics including data management plans, ethical and legal obligations, quality assurance, and the importance of data sharing and citation. The sessions aim to equip participants with the skills and knowledge needed for effective management and sharing of digital research data.
Data Management Lab: Session 4 Review Outline
- 1. IUPUI University Library Center for Digital Scholarship Data Management Lab: Spring 2014 Review Outline Session 1 1. Introduction to RDM a. Describe key challenges associated with managing digital research data b. Identify the potential consequences for irresponsible or inattentive data management c. Understand the life cycle approach to managing research data 2. Data Management Plans & Planning a. Summarize the basic components of US federal funding agency requirements for data management and sharing b. Define expected outcomes for data 3. Ethical & legal obligations a. Identify your legal obligations as they affect data management and protection b. Identify your ethical obligations for ensuring data confidentiality, privacy, and security c. Describe intellectual property issues for data that result in a patentable or commercial product 4. Storage & backup a. Prepare a comprehensive storage and backup plan Heather Coates, 2014
- 2. IUPUI University Library Center for Digital Scholarship Data Management Lab: Spring 2014 Review Outline Session 2 1. Project & data documentation a. Outline planned project and data documentation in a data management plan b. Identify metadata to describe the data set 2. Organizing data & files a. Develop a consistent and coherent file organization and naming convention scheme for all project files b. Select appropriate non-proprietary hardware and software formats for storing data c. Create protected copies of files at crucial points in your study d. Use versioning software or documentation for tracking changes to files over time Session 3 1. Quality assurance & control a. Develop data quality standards b. Develop procedures for quality assurance and quality control activities 2. Data collection a. Describe key considerations for selecting data collection tools Heather Coates, 2014
- 3. IUPUI University Library Center for Digital Scholarship Data Management Lab: Spring 2014 Review Outline 3. Data coding a. Use best practices for data coding 4. Data entry a. Use best practices for data entry 5. Data screening & cleaning a. Develop a screening and cleaning protocol and/or checklist 6. Automating tasks for better provenance a. Explain why automation provides better provenance than manual processes b. Identify effective tools for automating data processing and analysis Session 4 1. Ethical & legal obligations a. Identify your legal obligations for sharing and long-term preservation b. Identify how ethical and legal obligations affect data protection and sharing 2. Data protection, rights, & access a. Identify tools and platforms for storing, managing, and preserving data 3. Data sharing & re-use a. Identify the benefits to researchers of data sharing Heather Coates, 2014
- 4. IUPUI University Library Center for Digital Scholarship Data Management Lab: Spring 2014 Review Outline b. Evaluate resources for sharing data and openly or publicly available data 4. Data attribution & citation a. Identify two technologies enabling data citation 5. Synthesis Heather Coates, 2014