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  3. Master Course on Digital Curation and Digital Humanities
  4. Area of ​​Specialization in Digital Curation
  5. Research data management and curation

Research data management and curation

Objectives

- How to identify the operational concepts of digital curation of research data.

- Knowing Open Science policies and identifying good data management practices.
- Understand the processes associated with data management throughout the research lifecycle: data management plans; licensing, protection and ownership of data; sharing and depositing data in repositories; sustainability, security and data interoperability.
- Develop open data management skills.
- Acquire knowledge and ability to link research data curation with digital humanities.

General characterization

Code

02111077

Credits

10.0

Responsible teacher

Paula Alexandra Ochôa de Carvalho Telo

Hours

Weekly - 3

Total - 280

Teaching language

Portuguese

Prerequisites

N/A

Bibliography

European Commission. 2017. Guidelines on Open Access to Scientific Publications and Research Data in Horizon 2020. https://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-pilotguide_en.p


Grupo de Trabalho BAD das Bibliotecas de Ensino Superior. (2016). Recomendações para as Bibliotecas de Ensino Superior de Portugal - 2016. Zenodo. http://doi.org/10.5281/zenodo.835758


Horstmann, W.; Nurnberger, A.; Shearer, K.; Wolski, M. (2017): Addressing the Gaps: Recommendations for Supporting the Long Tail of Research Data. DOI: 10.15497/RDA00023


Pinfield, S., Cox, A., Smith, J. (2014): Research Data Management and Libraries: Relationships, Activities, Drivers and Influences, PLOS. DOI: 10.1371/journal.pone.0114734


RDA Libraries for Research Data Interest Group (2016): 23 Things: Libraries for Research Data. DOIdx.doi.org/10.15497/RDA00005


Science Europe (2021) ‘Practical Guide to the International Alignment of research data. Brussels: Science 


In the supporting material you will find more bibliographic references.

Teaching method

Theoretical-practical sessions, with reading of texts, presentation of case studies, discussion of concepts and active participation of students in the search for bibliography and in the definition and understanding of concepts.
The classes will have a theoretical and practical nature, consisting of moments of theoretical exposition of the themes, practical exercises, oral presentations and debates participated by the students.


Students should read the suggested material before each class.
The autonomous work of students should complement and deepen the knowledge transmitted in the classroom, promoting autonomous learning by the students.

Evaluation method

Continuous evaluation


 


The assessment will be made based on the following considerations:


- Group work (Data management plan) – 30%


- Group work (scientific article) – 20%


- Presentation and Commentary on Texts (individual) – 40%


- Participation (individual) -10%

Subject matter

1. Open Science, open access, open data.



1.1. Sustainability, interoperability and scalability.



1.2. Main policies and good practices. The European strategy for data, Science Europe's strategy for 2021–2026, the
European Cloud for Open Science (EOSC), FAIR principles, TRUST principles.
2. Information life cycle and information curation: main concepts.



2.1. Skills and data literacy.



3. Research data management.
3.1. Data management plans.
3.2. Organization and documentation. Metadata, normalization and data preservation.
3.3. Data Repositories.
3.4. Data curation, sharing and reuse. data citation.
3.5. Data protection, consent management and confidentiality.



4. Case Studies.