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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-pilot-guide_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


Cameron, F. R (2021) The future of digital data, heritage and curation in a more-than-human world. London Routledge.


FAIR assessment tool. Available at: https://www.ands-nectar-rds.org.au/fair-tool.


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


Jones, S. et al. (2020) Data management planning: How requirements and solutions are beginning to converge. Data Intelligence 2(2020), 208–219. doi: 10.1162/dint_a_00043.


Konold C, Higgins T, Russel SJ, et al.(2015) Investigating data like a data scientist: Key practices and processes. Statistics Education Research Journal.  21(2).


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. DOI dx.doi.org/10.15497/RDA00005


Research Data Alliance Metadata Directory. Available at: http://rd-alliance.github.io/metadata-directory/standards/.


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

Teaching method

Theoretical-practical sessions, with reading of texts, presentation of case studies, discussion of concepts and active participation of students in searching for bibliography and in the definition and understanding of concepts. In-person classes will have a theoretical-practical nature, consisting of moments of theoretical presentation of the topics, practical exercises, oral presentations and debates participated by students. Students must read the material that is suggested before each class. Students' independent work should complement and deepen the knowledge transmitted in class, promoting autonomous learning on the part of students.

Evaluation method

Continuous assessment. The class will be organized into 3 work groups.


The first assessment - 8/10 (30%) focuses on:


. individual presentation of a text (15%)


- creation and presentation of a graphic summary based on the texts of the group members - Group work - (15%)


The second assessment - 12/11 (30%) focuses on:


- individual presentation of a text (15%)


- creation and presentation of the mapping of the group's information needs - Group wor (15%) 


The third assessment (10/12 and 17/12) (40%) Group work


- Presentation of the data management plan (25%)


- creation and presentation of the group's behavior model and information practices (15%)

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 Open Science Cloud (EOSC), FAIR principles, TRUST principles.


2. Information lifecycle and information curation: main concepts.


2.1. Data literacy and skills.


3. Research data management.


3.1. Data management plans.


3.2. Organization and documentation. Metadata, standardization 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.