Dataverse

Goal: 
Discover how and why deposit datasets in Dataverse, the institutional data repository for the University of Milan.

Description: 
Do you want to publish data related to your research or a publication? Your funder asks you to open your data and deposit them in a repository that respects the FAIR principles? This workshop combining theory and practice will give you an introduction to Dataverse.unimi.it the university institutional repository: discover why and how to deposit your research data there.

Target audience: 
PhD, Post-Doc, researchers, and Faculty

Prerequisite: 
none

Format:

• 60 min. workshop
• Registration needed
• English or Italian

Contents:

• Know the advantages of depositing data in a FAIR compliant repository (and possible alternatives)
• Understand the structure of Dataverse.unimi.
• Creating a dataverse and deposit a dataset

Themes: 
research data ; repository ; FAIR data; Dataverse; Open Science

Data Management Plan

Goal: 
Analyze the key elements of a data management plan (DMP) of the European Commission.

Description: 
Since October 2017, researchers have to include a data management plan (DMP) in their funding application. During this workshop, you will see what are the requirements from EC and how to fill the DMP.

Target audience: 
Researchers, Post-doc, PhD students,

Prerequisite: 
none

Format:

• Online
• Registration needed
• 60-minute-workshop
• English or Italian

Contents: 

Understand the requests of the DMP and learn how to respond consistently and comprehensively

Subjects: 
DMP, EC

FAIR data

Goal: 
To improve the visibility, accessibility and reuse of your research data. To be compliant with the requests of funders.

Description: 
The FAIR Principles are good practices for the dissemination of research data, ensuring its visibility, discoverability and reusability.

Target audience: 
Students, PhD students, post-docs, researchers,

Prerequisites: 
None

Format:

• Online
• Registration needed
• 60-minute-workshop
• English or Italian
  
  Contents:

• presentation of the FAIR principles
• requirements of funders
• how to make your data FAIR (in practice)

Topics: 
FAIR principles, research data