Efficient Data Management Practices

September 20, 2019

Anna Sackmann, Science Data & Engineering Librarian 

Scholarly

Workflows

Data Management

Citation Management

LaTeX with Overleaf

Data Analysis

Practices in

Reproducibility

Why data management? 

  • Personal benefits
  • Funder and Publisher Policies
  • Ethical science

Break down data management planning into three stages. 

Before                    During                    After

1. Before you begin your research:

  • Computers: lab, personal, or both?
  • Shared instruments
  • Format of data
  • Measurements
  • Videos and images

Describe the design.

Describe the data.

Data type: numerical, image, video, simulations, etc.

 

Data format:  .txt, .csv, .jpeg, .tif, proprietary

 

How much and how often?

 

Who are you sharing the data with?

 

2. During your research

Follow the 3-2-1 rule.

3

2

1

Create 3 copies of your data. 

On at least 2 types of storage. 

With 1 copy offsite. 

Storage options at UC Berkeley

File Naming: 3 Rules

1. Pick a system that will work for you and your collaborators.

 

2. Document this system in a readme.txt file.

 

3. Create a system that is comprehensive and achievable.

 

Examples:

When was it produced? Who produced it?

What is it for? What is it about?

What factors should be clear at-a-glance?

ISO 8601: 20191011

 

date_datatype_location_researcher: 20191011_AQI_94619_Sackmann

3. After your research

 

  • Revisit funder data sharing requirements and project data management plan
  • Check on publisher requirements
  • Deposit data in a reputable repository

Activity:

 

Read the case study and select the applicable data planning attributes.

 

Make note of questions or anything you think should be changed.

 

http://bit.ly/TOMODEC

Questions:

 

Research Data Management Program

researchdata@berkeley.edu

 

http://bit.ly/TOMOslides

Dynamic data management plans; sharing and managing data; storage; final naming conventions; FAIR data; data publishing and citation

By asackmann

Dynamic data management plans; sharing and managing data; storage; final naming conventions; FAIR data; data publishing and citation

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