Learning how to manage, share and preserve data is essential for active researchers. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their...
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Hochschule für Wirtschaft und Umwelt Nürtingen-Geislingen, Bibliothek Nürtingen
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Learning how to manage, share and preserve data is essential for active researchers. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their data.
CONTENTS; ABOUT THE AUTHOR; ACKNOWLEDGEMENTS; 1 THE DATA PROBLEM; 1.1 WHY IS EVERYONE TALKING ABOUT DATA MANAGEMENT?; 1.2 WHAT IS DATA MANAGEMENT?; 1.2.1 Defining data; 1.2.2 Defining data management; 1.3 WHY SHOULD YOU DO DATA MANAGEMENT?; 2 THE DATA LIFECYCLE; 2.1 THE DATA LIFECYCLE; 2.1.1 The old data lifecycle; 2.1.2 The new data lifecycle; 2.2 THE DATA ROADMAP; 2.2.1 Following the data roadmap; 2.3 WHERE TO START WITH DATA MANAGEMENT; 2.4 CHAPTER SUMMARY; 3 PLANNING FOR DATA MANAGEMENT; 3.1 HOW TO PLAN FOR DATA MANAGEMENT; 3.1.1 The importance of planning for data management
3.1.2 How to customize data management to your needs3.2 CREATING A DATA MANAGEMENT PLAN; 3.2.1 Why create a written data management plan?; 3.2.2 What a data management plan covers; 3.2.3 Creating a data management plan for your research; 3.3 DATA POLICIES; 3.3.1 Types of policies and where to find them; 3.3.2 Data privacy policies; 3.3.3 Data retention policies; 3.3.4 Data ownership policies; 3.3.5 Data and copyright; 3.3.6 Data management policies; 3.3.7 Data sharing policies; 3.4 CASE STUDIES; 3.4.1 Example data management plan for a Midwest ornithology project
3.4.2 My data management plan for this book3.5 CHAPTER SUMMARY; 4 DOCUMENTATION; 4.1 RESEARCH NOTES AND LAB NOTEBOOKS; 4.1.1 Taking better notes; 4.1.2 Laboratory notebooks; 4.1.3 Electronic laboratory notebooks; 4.2 METHODS; 4.2.1 Definition of methods; 4.2.2 Evolving protocols; 4.2.3 Managing methods information; 4.3 OTHER USEFUL DOCUMENTATION FORMATS; 4.3.1 README.txt files; 4.3.2 Templates; 4.3.3 Data dictionaries; 4.3.4 Codebooks; 4.4 METADATA; 4.4.1 When to use metadata versus notes; 4.4.2 The basics of metadata; 4.4.3 Adopting a metadata schema; 4.5 STANDARDS; 4.5.1 General standards
4.5.2 Scientific standards4.6 CHAPTER SUMMARY; 5 ORGANIZATION; 5.1 FILE ORGANIZATION; 5.1.1 Organizing digital information; 5.1.2 Organizing physical content; 5.1.3 Organizing related physical and digital information; 5.1.4 Indexes; 5.1.5 Organizing information for collaborations; 5.1.6 Organizing literature; 5.2 NAMING CONVENTIONS; 5.2.1 File naming; 5.2.2 File versioning; 5.3 DOCUMENTING YOUR CONVENTIONS; 5.3.1 What to document; 5.3.2 Where to document; 5.4 DATABASES; 5.4.1 How databases work; 5.4.2 Querying a database; 5.5 CHAPTER SUMMARY; 6 IMPROVING DATA ANALYSIS
6.1 RAW VERSUS ANALYZED DATA6.1.1 Managing raw and analyzed data; 6.1.2 Documenting the analysis process; 6.2 PREPARING DATA FOR ANALYSIS; 6.2.1 Data quality control; 6.2.2 Spreadsheet best practices; 6.3 MANAGING YOUR RESEARCH CODE; 6.3.1 Coding best practices; 6.3.2 Version control; 6.3.3 Code sharing; 6.4 CHAPTER SUMMARY; 7 MANAGING SENSITIVE DATA; 7.1 TYPES OF SENSITIVE DATA; 7.1.1 National data privacy laws; 7.1.2 Ethics and sensitive data; 7.1.3 Other data categorized as sensitive; 7.2 KEEPING DATA SECURE; 7.2.1 Basic computer security; 7.2.2 Access; 7.2.3 Encryption
