Code reproducibility

Code reproducibility rules

Data Management

Useful resources lis here

Introduction

1. Introduction to data management for life science researchers

2. Introduction to data management planning

3. Introduction to sections of a generic ​data management plan​

Issues in Data Management

1. Manage well and get preserved - 1. Research data management and digital preservation

2. Manage well and get preserved - 2. Open formats and data quality

3. Manage well and get preserved – 3. Persistent identifiers. Wow to create sustainable solutions for citation and research data management with the help of persistent identifiers

4. Manage well and get preserved – 4. Metadata standards.  They are structured way to document information about data objects

5. Manage well and get preserved - 5. Preservation metadata. What information is needed to preserve digital research data in the long term.

6. Manage well and get preserved – 6. Managing files and file naming.  It is important to take some time to plan file and folder structures and naming procedures in the beginning of your research

7. Manage well and get preserved – 7. Checksums (optional) A checksum means a numerical value calculated from binary data using an appropriate mathematical algorithm

FAIR

1. The Elements of FAIR - Interoperability

GUIDES

1. Johns Hopkins Institute for Clinical and Translational Research (ICTR) Best Practices for Research Data Management

2. Reynolds, T., Schatschneider, C. & Logan, J. The Basics of Data Management

3. The Turing Way Guide

Open Science