Course name: Public Data Management

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Course name: Public Data Management

Teaching medium: English


2 credits, 24 Class Hours, 1st Semester etc.

This course is mainly about scientific data resources. Based on the theory of data life cycle, it discusses the core issues of the opening and sharing of scientific data, including data policy, data management plan, data acquisition, data organization, data analysis, data preservation, data publishing and sharing, data reuse, etc. This course enables graduate students to master the basic theories, methods and tools of scientific data management comprehensively and systematically, so as to lay a solid foundation for engaging in scientific data management research and solving practical problems.


classroom method of teaching; discussion method;case teaching method;group discussion;practice teaching method;heuristic teaching method

C. COURSE OBJECTIVES(five or six objectives; general but comprehensive)
Objective 1: This course enables students to understand the basic concepts of scientific data management.

Objective 2: This course enables students to understand thetheoretical basis of scientific research data management.

Objective 3: This course enables students to understanddata management policy.

Objective 4: This course enables students to understanddata collection and acquisition;data documents;data organization and metadata;data preservation and storage;data publishing and sharing;data analysis and reuse.

Objective 5: This course enables students to use scientific data management methods and tools to solve practical problems.


Chapter I background of scientific research data management (2 class hours)

1.1 Professional organization of scientific research data management

1.2 Scientific research data management report

1.3 Scientific research data management conference

Chapter II Research Progress of scientific research data management (2 class hours)

2.1Research progress of scientific research data management in China

2.2 Research progress of scientific research data management at abroad

Chapter III basic concepts of data management (2 class hours)

3.1 Scientific research data, scientific data, open government data

3.2 Data management, data governance

3.3 Data science, open science, citizen science

Chapter IV theoretical basis of scientific research data management (2 class hours)

4.1 Data lifecycle theory

4.2 Public management theory

4.3 Theory of scientific research process

Case 1 - Digital Culture Centre (DCC)

Chapter V data management policy (2 class hours)

4.1 US data management policy

4.2 UK data management policy

4.3 Australian data management policy

Case 2 - research data and records management policy of Oxford University

Chapter VI data management plan (2 class hours)

6.1 Data management plan elements

6.2 Data management plan writing steps and guidelines

6.3 Data management plan writing case

Case 3 data management plan of Stanford University

Chapter 7 data collection and acquisition (2 class hours)

7.1 data type

7.2 Ways and methods of data collection

7.3 Data collection steps and cases

Case 4 - data collection tools at Columbia University

Chapter 8 data documents (2 class hours)

8.1 Data file organization

8.2 Data file version

8.3 Data file cases

Chapter IX data organization and metadata (2 class hours)

9.1 Data organization overview

9.2 Metadata theory

9.3Data organization case

Chapter X data preservation and storage (2 class hours)

10.1 Data backup

10.2 Data saving

10.3 Long term data storage

Chapter XI data publishing and sharing (2 class hours)

11.1 Data intellectual property

11.2Theory and method of data publishing and sharing

11.3Data publishing and sharing cases

Case 5: dataverse data publishing platform of Harvard University

Chapter 12 data analysis and reuse (2 class hours)

12.1 Data analysis methods and tools

12.2 Data reference

12.3 Data analysis and reuse cases

Case 6: data analysis and reuse of the University of Sheffield

Textbook (required):

[1] Ladley J. Data Governance: How to Design, Deploy, and Sustain an Effective Data Governance Program[M]. Newnes, 2012.

[2] Plotkin D. Data stewardship: An actionable guide to effective data management and data governance[M]. Newnes, 2013.

[3] Henderson M E. Data Management: A Practical Guide for Librarians[M]. Rowman & Littlefield, 2016.

Supplies and/or tools:
[1] Rose Harvey. Digital Curation[M]. New York: Neal-Schuman Publishers, Inc., 2010.

[2] Briney K. Data Management for Researchers: Organize, maintain and share your data for research success[M]. Pelagic Publishing Ltd, 2015.

[3] Research data management: Practical strategies for information professionals[M]. Purdue University Press, 2014.

[4] Krier L, Strasser C A. Data management for libraries: a LITA guide[M]. American Library Association, 2014.

1. In-class participation (10%): (1) Full attendance; (2) Active participation in class discussion

2. Homework (40%):Judge according to the completion.

3. Research paper (50%): (1) At least 1000 words; (2) Complete article structure; (3) Good topics and innovation; (4) Compliance with academic ethics, no plagiarism.


Some data analysis tools are suitable for different grades and majors.

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