Webinars will be held on Friday afternoons and will last about 60 minutes. Those interested are asked to register and will then be notified of the next available course.

Date of next edition of RDM courses:
25 november 2022 FAIR data, Dataverse, Data Management Plan

From november 14, 2022 incoming subscriptions will be considered for next edition that will be scheduled on last friday of 2023 january, 27.

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

Registration Form next edition: 27 January 2023

    * required

    * Training choices

    * Course language