RDM Training: Publish research data with the Research Data Repository
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Presentació del curs "Publicar dades de recerca amb el Repositori de Dades de Recerca (en anglès)
![4.8 Adding files
Add all the files you need!
Attention!
Every dataset must contain a
Readme.txt that describes
the content of the data
(variable and value labels,
units of measurement, etc.)
If your dataset has a certain
file structure, upload it to ZIP
to preserve its structure
Save dataset [not yet public]
Accept the Terms and condicions](https://image.slidesharecdn.com/2025rdmtrainingrdr-250519134543-568d88c1/85/RDM-Training-Publish-research-data-with-the-Research-Data-Repository-28-320.jpg)
RDM Training: Publish research data with the Research Data Repository
- 1. RDM Training: Publish research data with the Research Data Repository Learning, Research and Open Science area
- 2. Contents 1. Open science and research data management 2. Funding agency requirements 3. Research data and publication 4. RDR, the repository for publishing FAIR data
- 3. Contents 1. Open science and research data management 2. Funding agency requirements 3. Research data and publication 4. RDR, the repository for publishing FAIR data
- 4. What is open science? New approach to the research process based on an open environment, that is, on a communication ecosystem that facilitates that research results are transparent, accessible, interoperable and reusable, and that science is made with and for society. https://cora.csuc.cat/ M. Imming & J. Tennant
- 5. Open Science at CSUC Impulse open science Open access Research data management Repositories Catalonia Research Portal https://cora.csuc.cat/
- 6. What do they have in common? Compilation of the percentage of abstention in different European countries Photographs of an excavation Prints of an archaeological intervention Interview scripts Samples from colon cancer patients It's all RESEARCH DATA!
- 7. Therefore... What do we mean by? (CT CORA.RDR) DATASET: "set of files, descriptive metadata, associated documentation, together with the rights and the license of use, which validates a search activity" (CT CORA.RDR) OPEN SEARCH DATA: "are online, at no cost of use, accessible and can be reused and distributed as long as the source of the data is cited"(FOSTER) RESEARCH DATA: "any information that has been collected, observed, generated or created to validate a research process" (FOSTER) FAIR DATA: "data that has been processed to be findable, accessible, interoperable and reusable" Terms Medium
- 8. Research Data Management (RDM) It is the set of practices related to the creation, organization, structuring, storage, preservation and sharing of data 1.5 Why is it necessary to manage data?
- 9. 1.7 Data types There are different types of data: -Observational: data captured in real time -Experimental: data captured on laboratory equipment -Simulation: data generated from test models -Derived or compiled: reproducible data, but difficult to reproduce -Reference: conglomerate or dataset And these usually go through different stages: -Raw data: data as originally collected, without processing or analysis. -Curated data: processed and analyzed data -Published data: made public in an environment -Metadata: data that accompanies the data and describes the resource
- 10. Contents 1. Open science and research data management 2. Funding agency requirements 3. Research data and publication 4. RDR, the repository for publishing FAIR data
- 11. 2.1 A European desire for national and institutional implementation
- 12. 2.2 Funding agency requirements Generally, funding agencies ask for: • Make a data management plan (DMP) and update it periodically • Deposit data following FAIR principles in a trusted repository OpenAIRE
- 13. Contents 1. Open science and research data management 2. Funding agency requirements 3. Research data and publication 4. RDR, the repository for publishing FAIR data
- 14. 3.1 Research process Planning 1 Acceptance 2 Analysis and management 3 Publication (preservation) 4 Discovery 5
- 15. 3.2.1 Criteria for selecting a repository What happens in each case? We cede the rights to the data and replicate the current business model of the journals The project ends and we lose all information We do not know the viability of the project and usually do not have quality processes
- 16. 3.2.2 Criteria for selecting a repository Document about criteria for selecting a repository Consult if your institution has policies or recommendations about how to select a research data repository. It you have a funded research project, check the funding agencies requirements. Check if you can deposit your research data in a disciplinary research data repository Use a general- purpose and trustworthy data repository
- 17. 3.2 Criteria for selecting a repository What should be taken into account when choosing? • Is there a specific repository for the discipline? • Do needs match requirements? (formats, size, openness level, etc.) • Do they assign a persistent identifier? DOI? • Is it certified as a trusted repository?
- 18. 3.2.2 Criteria for selecting a repository Re3Data, the catalogue par excellence -More than 3,000 repositories -Search by name or discipline -Possibility of adding filters (certification, license, PID...)
- 19. Contents 1. Open science and research data management 2. Funding agency requirements 3. Research data and publication 4. RDR, the repository for publishing FAIR data
- 20. Dataset-federated repository -Universities -CERCA research centers Multidisciplinary For Teaching and Research Academic Staff and PhD students Open (as open as possible but as closed as necessary) Complies with funding agency requirements and FAIR principles 100 GB per dataset by default 4.1 What is CORA. RDR? https://dataverse.csuc.cat/
- 21. 4.2 What does it offer?
- 22. Collection 4.3 How RDR is organized? https://dataverse.csuc.cat/
- 23. 4.4 RDR registration There are two ways to register A) If your institution has UNIFICAT:
- 24. 4.4 RDR registration There are two ways to register B) If your institution does not have UNIFICAT:
- 25. 4.5 Start depositing With the right permissions, you can start depositing datasets
- 26. 4.6 First of all, essential metadata must be added Predefined info A descriptive title is required; if it is the same as the article, add "Replication Data for" at the beginning Add as many authors as you need ORCID! Designates a contact to receive communications from other researchers Describe the dataset (content, formats, files, variables, etc.) It's not the abstract of the article!
- 27. 4.7 Adding more metadata by discipline Choose your discipline from a drop-down list Add as many keywords as you need. If it's controlled language, even better! Relate the dataset to associated publications Explain anything you want in your notes Indicate the language of the dataset The producer and distributor are pre-established Depositor credit can be given The deposit date is predefined The type of data must be indicated
- 28. 4.8 Adding files Add all the files you need! Attention! Every dataset must contain a Readme.txt that describes the content of the data (variable and value labels, units of measurement, etc.) If your dataset has a certain file structure, upload it to ZIP to preserve its structure Save dataset [not yet public] Accept the Terms and condicions
- 29. 4.9 Dataset in draft Fields Metadata At the top of the screen, different informative messages will appear The dataset has been created The dataset is a draft The tab file is being ingested Dataset title License Versions Citation (with DOI!) of the dataset Dataset status
- 30. 4.10 After this point... MANY MORE metadata can be added Especially by discipline The default license is CC0 But it can be modified
- 31. 4.11 Add more data by discipline Geospatial metadata Social Science and Humanities metadata Astronomy and Astrophysics metadata Life sciences metadata Journal metadata Computational workflow metadata
- 32. The deposit and publication workflow Contact your institution the first time you want to make a deposit! Researchers... DEPOSIT SUBMIT FOR REVIEW Dataset Draft
- 33. Creating a unpublished dataset preview URL You can ask your institution's support service to create a private URL so that others can view the dataset even if it's in draft
- 35. The deposit and publication workflow
- 36. Dataset published following the FAIR principles Persistent identifiers (DOIs) for dataset and metadata indexing by search engines (EOSC, Google, OpenAIRE, Recolecta...) Licenses that clearly state how the data can be used and that ensure that the data is well documented and retained for long-term use (CC Licensing Recommendation; Metadata CC0) Possibility of making versions and having access to each one It provides standardized metadata schemas (generic and by discipline) and allows the integration of data with research tools and platforms. Guarantee that data can be downloaded in machine-readable formats (depending on the level of openness: open, embargoed or restricted)
- 37. How can we reuse and access data? Search by spaces, datasets or files • Facets for metadata Basic search Advanced search
- 38. How can we reuse and access data? If a tree structure has been established for the files, the first display option will be this. Files can be viewed in tree or table format
- 39. How can we reuse and access data? – Open access To download the file individually To select all dataset files To download all selected files File preview File in open access Available formats
- 40. How can we reuse and access data? - Embargoed It will be possible to access from 25-07- 2025
- 41. How can we reuse and access data? - Embargoed We choose the date on which we want the file to stop being restricted
- 42. How can we reuse and access data? - Restricted File restricted, but access can be requested
- 43. How can we reuse and access data? - Restricted We can enable request access for only one dataset file
Editor's Notes
- #14: Però, què entenem per dada? Doncs una dada és qualsevol informació que ha estat recollida, observada, generada o creada per validar un procés de recerca. Si el que volem és entendre que són les dades de recerca en obert, també hi haurem d’afegir conceptes com que son en línia, sense cost d’ús, accessibles i que es poden reutilitzar i redistribuir, sempre que se’n citi la font. I què entenem per dataset? Doncs aquell conjunt de fitxers (que poden ser dades, codi, documentació) i les metadades que les descriuen. Per tant, aquest conjunt de fitxers, per la raó que sigui, té sentit que estiguin agrupats. A vegades, la raó pot ser que formen part d’un mateix projecte, pot ser que donen veracitat, validen els resultats d’un article, etc. I finalment, a mesura que s’anava estenent la publicació de dades es va veure que no totes les dades sempre s’havien de publicar en obert i, per aquest motiu, al al 2014 va sorgir aquest concepte que ha tingut molt d’èxit i que és el FAIR. FAIR no és res més que un acrònim de Findable, Accessible, Interoperable and Reusable i el que fa és que, per cadascun d’aquests conceptes, hi ha un conjunt bàsic de principis per tal d’optimitzar la reutilització de les dades. Per exemple, per a que les dades siguin trobables, és a dir, la F, cal que se’ls hi assignin un identificador únic, com és el DOI, per a que siguin accessibles, han d’estar disponibles , per a que siguin reutilitzables, han de seguir les convencions i les normes de la disciplina i s’han de poder exportar de manera automàtica entre diferents portals i, finalment, per a que siguin reutilitzables, han de tenir definida clarament la llicència i quin ús se’n podrà fer.
- #38: Els datasets a l’RDR tenen tres nivells d’obertura: oberts, embargats i restringits. Independentment del nivell d’obertura dels dfitxers, veurem això de la diapo
- #40: Afegir enable access request
- #42: Treure el restringit, no explicar el retention period
- #43: Treure el restringit, no explicar el retention period