Transferable Skills: Research Data Management
Keywords |
Classification |
Keyword |
CNAEF |
Informatics |
Instance: 2023/2024 - 2S (of 05-02-2024 to 31-07-2024)
Cycles of Study/Courses
Teaching language
Portuguese and english
Objectives
- Identify funder requirements for sharing research data;
- Understand the FAIR principles for data management: findability; accessibility; interoperability; reusability;
- Obtain an integrated view of the entire data lifecycle in a research project;
- Develop a Data Management Plan.
Learning outcomes and competences
This course aims to enable participants to develop research data management skills, which support the development of Data Management Plans.
Learning outcomes:
- Planning and scheduling management activities appropriate to the different phases of the research data life cycle;
- Application of best practices for documenting and publishing data in accordance with FAIR principles;
- Identification of resources available to support activities related to research data management;
- Identification of key privacy and ethical issues in relation to investigation data.
Working method
Presencial
Pre-requirements (prior knowledge) and co-requirements (common knowledge)
Program
- Introduction to Research Data Management:
- FAIR Principles and the Data Management Plan;
- Typology and life cycle of research data;
- FAIR data: data documentation, metadata models;
- FAIR data: data publishing, repositories and services;
- Resource allocation and data organization: resources and strategies;
- Privacy and ethics issues;
- Presentation of Data Management Plans developed by students
Mandatory literature
European Commission ;
Guidelines on FAIR Data Management in Horizon 2020, 2016
European Commission;
Turning FAIR into reality. Final Report and Action Plan from the European Commission Expert Group on FAIR Data., 2018
RDA FAIRSharing Registry: connecting data policies, standards & databases WG ;
FAIRsharing: standards, databases, repositories and policies – Final Recommendation, 2018 (doi: 10.15497/RDA00030)
RDA Metadata standards directory Working Group ; Metadata Standards Directory WG Recommendations, 2016 (http://rd-alliance.github.io/metadata-directory/)
RDA /WDS Publishing Data Workflows WK Recommendations ;
Workflows for Research Data Publishing: Models and Key Components., 2016 (doi: 10.15497/RDA00004)
Sarah Higgins ;
The DCC Curation Lifecycle Model, 2008 (International Journal of Digital Curation)
William Michener ;
Ten simple rules for creating a good Data Management Plan, Plos Computational Biology, 2015 (doi:10.1371/journal.pcbi1004525)
Teaching methods and learning activities
In this context, it is proposed an interaction of 14 hours of contact, in a total of 40.5 hours.Classes will be theoretical-practical, in which students develop practical work related to the component in question, building the Data Management Plan incrementally throughout the training. In the last session, students present the DMP for evaluation purposes.This TC supposes a substantial work of autonomous study, for the study and analysis of cases of data management plans and for the construction of a plan to be discussed and presented in a class session. We estimate these at about 1/3 of the hours with the rest of the work being done autonomously, as is expected at the level of students to be admitted.
Evaluation Type
Distributed evaluation without final exam
Assessment Components
Designation |
Weight (%) |
Apresentação/discussão de um trabalho científico |
25,00 |
Trabalho escrito |
75,00 |
Total: |
100,00 |
Amount of time allocated to each course unit
Designation |
Time (hours) |
Estudo autónomo |
28,50 |
Frequência das aulas |
12,00 |
Total: |
40,50 |
Eligibility for exams
active participation in face-to-face activities
Calculation formula of final grade
75% DMP report + 25% oral presentation