# Research Data Management (RDM) **Course Notes** ##### [[Part 0/Part 0 -- Introduction, Overview, & Conceptual Foundations|Part 0: Introduction, Overview, and Conceptual Foundations]] - [[Part 0/(0.1) Introduction to Research Data Management|(0.1) Introduction to Research Data Management]] - [[Part 0/(0.2) Foundational Concepts|(0.2) Foundational Concepts]] - [[Part 0/(0.3) The 10 Golden Rules of Research Data Management|(0.3) The Ten Golden Rules of Research Data Management]] - [[Part 0/(0.4) A Primer on the Modern Computer System|(0.4) A Primer on the Modern Computer System]] - [[Part 0/(0.5) Tools & Resources|(0.5) Tools & Resources]] ##### [[Part 1/Part 1 -- Data Storage, Files, & Organization|Part 1: Data Storage, Files, and Organization]] - [[Part 1/(1.1) The Four Layers of Data Organization|(1.1) The Four Layers of Data Organization]] - [[Part 1/(1.2) Tidy Data as a Structural Standard|(1.2) Tidy Data as a Structural Standard]] - [[Part 1/(1.3) Portability -- Importing & Exporting Data|(1.3) Portability -- Importing & Exporting Data]] - [[Part 1/(1.4) Collaborative Data Storage & Access|(1.4) Collaborative Data Storage & Access]] ##### [[Part 2/Part 2 -- Data Gathering & Entry|Part 2: Data Gathering and Entry]] - [[Part 2/(2.1) Guiding Principles|(2.1) Guiding Principles]] - [[Part 2/(2.2) Basic Manual Data Entry|(2.2) Basic Manual Data Entry]] - [[Part 2/(2.3) Navigating & Subsetting Data|(2.3) Navigating & Subsetting Data]] - [[Part 2/(2.4) Online Forms & Questionnaires|(2.4) Online Forms & Questionnaires]] - [[Part 2/(2.5) Working with Large Extant Data Sources|(2.5) Working with Large Extant Data Sources]] - [[Part 2/(2.6) Synthetic & Simulated Data|(2.6) Synthetic & Simulated Data]] ##### [[Part 3/Part 3 -- Data Preparation, Provenance, & Dissemination|Part 3: Data Preparation, Provenance, and Dissemination]] - [[Part 3/(3.1) Data Quality Assessment in Research Data Management|(3.1) Data Quality Assessment in Research Data Management]] - [[Part 3/(3.2) Data Cleaning|(3.2) Data Cleaning]] - [[Part 3/(3.3) Transforming & Restructuring Data|(3.3) Transforming & Restructuring Data]] - [[Part 3/(3.4) Dealing with Missing Data|(3.4) Dealing with Missing Data]] - [[Part 3/(3.5) Data File Organization & Naming Conventions|(3.5) Data File Organization & Naming Conventions]] - [[Part 3/(3.6) Provenance & Documentation|(3.6) Provenance & Documentation]] - [[Part 3/(3.7) Reproducibility & Workflow Control|(3.7) Reproducibility & Workflow Control]] - [[Part 3/(3.8) Exploratory Data Analysis|(3.8) Exploratory Data Analysis]] - [[Part 3/(3.9) Data Dissemination & Archiving|(3.9) Data Dissemination & Archiving]] ##### [[Part 4/Part 4 -- Data Security, Protection, & Ethics|Part 4: Data Security, Protection, and Ethics]] - (4.1) **Appendices** - [[Appendices/R & RStudio/Overview|Appendix A: R and RStudio]] - [[Appendices/Sublime Text/Overview & Setup|Appendix B: Sublime Text]] - [[Appendices/Regular Expressions/Overview|Appendix C: Regular Expressions]] %% Exploratory Data Analysis (EDA): At the initial stages of the research process (data preparation), no substantive research questions are being answered. There is no modeling, no inference, and no hypothesis testing. If we begin answering research questions, we stop. Full data analysis is treated as a subsequent phase of research to be addressed in various other methodology courses. %%