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Open Science

What is “Open Science”?

Open Science is a set of principles and practices that aim to make the entire research process more transparent, accessible, inclusive, and collaborative. The concept includes publications, data, software, or infrastructure and applies to the entire scientific process from conception to dissemination and reuse, in order to make it more transparent, accessible, inclusive, and collaborative.

What are the main pillars of Open Science?

The main pillars are:

Open access to scientific publications and results.
Open data: making data used in research available for reuse.
Open infrastructures (repositories, tools, platforms).
Participation and involvement of society (“citizen science”).
Collaborative networks, open research and open innovation.

Why is Open Science important for researchers?

Greater visibility and impact: making results accessible increases the potential for citation and use by the scientific community and society.
Transparency and rigour: it allows methods and data to be audited, which strengthens the credibility of the research.
Efficiency and resource savings: it avoids duplication of effort and promotes the reuse of data and methodologies.
Innovation and collaboration: it facilitates inter- and intradisciplinary partnerships and partnerships with society and can generate new products, services or ideas.
Justice and equity: promotes access to scientific knowledge for all, regardless of geographical or institutional location.

Does Open Science require everything to be 'open' without exception?

No. The principle is ‘as open as possible, as closed as necessary’. There are cases where restrictions are justified — for example, to protect sensitive personal data, intellectual property, confidentiality or traditional knowledge.

To what extent can Open Science benefit society in general, beyond the scientific community?

It makes it easier for decision-makers, public managers, NGOs and citizens to access scientific evidence for policies, practices and innovations.
It contributes to scientific literacy and public trust in science.
It allows innovations and applications to be derived more quickly from research results.
It reduces inequalities in access to scientific knowledge, especially in countries or institutions with fewer resources.

How can I implement Open Science practices in my research work?

Some practical actions:

Depositing scientific articles in open access through different alternative ways (Via Dourada, Via Verde, and Via Transformativa)
Publishing research data in reliable repositories, with clear metadata and licences that allow reuse.
Using open source software and tools.
Adopting practices of documentation, version management, and transparency in methods.
Involving citizens or communities in the project, when appropriate (citizen science).
Choosing open and clear licences (e.g. Creative Commons licences, CC-BY).
Complying with the open access policies of funding and host institutions.

How do I start the process of integrating good Open Science practices into my project– Data Management Plan?

Plan from the outset: include a Data Management Plan (DMP).
Define sharing licences for publications, data and software (e.g. Creative Commons, GPL, MIT).
Select reliable and interoperable repositories for publications and data.
Ensure compliance with funder and institutional policies.
Identify ethical or legal restrictions in advance (privacy, confidentiality, intellectual property).

Follow the FAIR principles: data should be Findable, Accessible, Interoperable, Reusable.
Use standardised metadata and open formats.
Document the data (methods, instruments, variables, codes, versions).
Note the provenance (who created it, when and how).
Use certified repositories (e.g. Zenodo, institutional repositories, thematic repositories, OpenAIRE, POLEN).
Ensure anonymisation of personal data in accordance with the GDPR.

How to apply good practices when publishing scientific results?

Opt for Open Access: publish in open access journals or deposit versions in repositories.
Prefer open licences that allow reading and reuse.
Avoid unnecessary paywalls or restrictive contracts.
Clearly describe data and methods to promote reproducibility.
Publish negative or null results when relevant — they help avoid duplication of effort.

What type of information can be considered for open access publication?

Scientific publications
Open research data
Open software and source codes
Open hardware
Open educational resources

What precautions should I take with Open Science software and code?

Use version control systems (GitHub, GitLab).
Adopt open software licences (e.g. MIT, GPL, Apache).
Include clear documentation on dependencies, installation, and usage.
Provide examples and reusable scripts.
Share in recognised repositories (e.g. GitHub, Zenodo, Software Heritage, RCAAP network).

What are the best practices for ensuring integrity and ethics in Open Science?

Respect copyright and third-party rights.
Protect sensitive data (personal, clinical, cultural data).
Acknowledge the contributions of all those involved (co-authorship, acknowledgements, technical contributions).
Avoid manipulation or distortion of results.
Promote transparency in methods, reviews, and conflicts of interest.

What tools and infrastructure can support good Open Science practices?

Publication repositories: Portuguese Open Access Scientific Repository (RCAAP), OpenAIRE, Zenodo.
Data repositories: Open Data Portal, Figshare, Dryad, institutional repositories.
Reference management and collaboration: Zotero, Mendeley, Overleaf, OSF.

What common mistakes should I avoid when applying Open Science practices?

Publishing data without proper documentation or without an explicit licence.
Using formats that require paid or proprietary software, making reuse difficult.
Not planning for openness from the outset of the project.
Ignoring ethical and legal aspects of data sharing.
Confusing openness with a lack of rigour — open science requires planning and responsibility.

How can I be recognised and evaluated positively for applying good Open Science practices?

Include evidence of open practices in reports, CVs, and applications (e.g., DOIs for datasets, software, repositories).
Value alternative metrics (downloads, reuses, community contributions).
Publicise the social impact of your research.
Look for programmes and awards that recognise open science practices (e.g. Open Science Awards, FCT initiatives, OpenAIRE, UNESCO).

Where can I learn more about good Open Science practices?

UNESCO – Open Science: unesco.org/en/open-science
Open Science Portugal Portal: ciencia-aberta.pt
FCT – Open Science: fct.pt/apoios/cienciaaberta
OpenAIRE: openaire.eu
GO FAIR: go-fair.org

What is the link between Open Science and the Data Management Plan (DMP)?

The DMP is a central tool of open science:

It promotes transparency, reproducibility and responsible access.
It ensures that data is well described and shareable.
It guarantees that openness is achieved in an ethical, secure and sustainable manner.

A good DMP transforms data management into a practice of scientific quality and social responsibility.

Good Practices in Research Data Management

What is 'research data management'?

It is the set of processes and decisions that ensure that data created, collected or analysed in a research project is organised, documented, stored, shared and preserved in a secure, ethical and reusable manner — from the beginning to the end of the research life cycle.

Why is it important to manage data well?

It increases the quality and transparency of research.
It facilitates the reproducibility of results.
It promotes reuse by other researchers.
It meets the requirements of funders (e.g. FCT, Horizon Europe).
Reduces the risk of information loss.
It enhances the impact and credibility of research.

What is a Data Management Plan (DMP)?

It is a strategic document that describes how data will be managed throughout the project:

What data will be produced or collected;
How it will be stored, documented and shared;
What restrictions may exist (ethical, legal, commercial);
How it will be preserved in the long term.

The FCT and Horizon Europe require a DMP for many funded projects. Examples of DMPs can be found online from funders and/or in repositories (e.g. Horizon Europe).

What are the best practices when creating a Data Management Plan?

Draw up the plan from the start of the project.
Update it periodically (it is a living document).
Describe formats, software, and metadata.
Include sharing and licensing policies.
Define responsibilities and timelines.
Plan costs and resources (storage, curation, preservation).
Ensure compliance with the General Data Protection Regulation (GDPR) if you process personal data.

What is FAIR data and how do I apply it?

FAIR data follows principles that make it:

Findable: it has unique identifiers and explicit, informative metadata.
Accessible: it is available via open protocols and with clear access conditions.
Interoperable: it uses standardised formats and vocabularies.
Reusable: they are well documented and licensed for reuse.

Applying FAIR principles is more than just making data ‘open’; it is about enabling data to be well managed and reusable.

What types of data should be managed and shared?

These include:

Raw and processed data;
Tables, codes, images, sound, models, software;
Protocols and methodological descriptions;
Metadata (information about the data).

Not all data needs to be open, but all data must be well described and preserved.

When should I prepare the DMP?

The DMP should be created at the beginning of the project (application or start phase) and updated periodically as the research progresses.

It is a dynamic document — it should reflect changes in the project and the data.

What should a good DMP contain?

An effective DMP includes at least the following sections:

1. General description of the data

Data types (numerical, textual, images, software, etc.)
Origin (collected, observed, simulated, derived)
Estimated volume and formats (e.g. CSV, TXT, TIFF)

2. Documentation and metadata

Standards used (e.g. Dublin Core, DataCite, ISO, Darwin Core)
Description of variables, methods, instruments, codes
How future comprehensibility of data will be ensured

3. Storage and security

Where and how data will be stored (institutional servers, cloud, secure drives)
Backup and recovery strategies
Access control and protection of sensitive data

4. Sharing and reuse

When and where data will be made available (repositories)
Licences for use (CC BY, CC0, ODC-BY, etc.)
Restrictions or exceptions (ethics, confidentiality, intellectual property)

5. Long-term preservation

What data will be preserved and for how long
Preservation formats (open and sustainable)
Permanent identifiers (DOI, handle)

6. Responsibilities and resources

Who is responsible for data management
Expected costs (storage, curation, preservation)
Institutional support and tools used

What tools can I use to create a DMP?

ARGOS (OpenAIRE) – free tool aligned with European policies.
DMPonline (Digital Curation Centre, UK).
DMPTool (USA).
Horizon Europe
FCT templates
Institutional templates (many Portuguese universities offer adapted templates).

Choose the template that best suits your funder’s requirements.

How can data quality and integrity be ensured?

Use open and stable formats (e.g. CSV, TXT, TIFF, XML).
Apply version control to record changes.
Document processes and scripts used in processing.
Validate and verify data before sharing.
Avoid duplication and maintain a consistent folder structure.

What file formats should I use?

Prefer open formats over paid or proprietary software to ensure longevity and reusability:

Text: TXT, CSV, XML, JSON
Images: TIFF, PNG
Audio/video: WAV, MP4
Documents: PDF/A
Code: TXT, R, Python, Jupyter

Indicate in the DMP which formats are used and why.

Where and how can I store my data securely throughout the project?

During the project: use institutional servers, secure drives, or platforms with automatic backup.
After the project: deposit the data in certified repositories (e.g. Zenodo, Figshare, institutional repositories, OpenAIRE, RCAAP).
Avoid storing data only on personal devices or in commercial cloud storage without institutional protection.
Encrypt sensitive data and limit access as necessary.

Institutional repositories (e.g. RCAAP, university repositories)
Thematic repositories (e.g. GenBank, ICPSR, PANGAEA)
Generic repositories (e.g. Zenodo, Figshare, Dryad, OSF)

Choose certified and interoperable repositories that assign DOIs and FAIR metadata.

How to handle confidential or personal data?

Apply anonymisation or pseudonymisation.
Obtain informed consent when necessary.
Follow the GDPR and the institution’s ethics policies.
Restrict access and use appropriate licences (e.g. ‘restricted access upon request’).
Document exceptions to full sharing.

The principle is: “as open as possible, as closed as necessary“.

Steps for handling sensitive or confidential data in the DMP?

Identify them clearly.
Describe the protection measures (anonymisation, pseudonymisation, encryption).
Indicate who will have access and under what conditions.
Explain how you comply with the General Data Protection Regulation (GDPR).
Justify any access restrictions (“as open as possible, as closed as necessary”).

Creative Commons (CC BY, CC0) — for open data.
Open Data Commons (ODC) — for databases.
Restricted licences (e.g. “controlled access”) — for sensitive data.

Always include an explicit licence — it defines what others can and cannot do with the data, namely whether or not it can be reused.

How can long-term preservation be ensured?

Deposit the data in repositories with preservation policies (minimum 10 years recommended).
Avoid paid or proprietary software.
Keep track of versions and updates of the software used.
Include metadata and complete documentation.

Who is responsible for data management in a project?

Usually, the principal investigator (PI) takes on the coordination.
A data manager may be appointed, or responsibilities may be shared within the team.
The institution should provide technical and legal support (libraries, open science offices).

How should the cost of data management and preservation be addressed?

Include in the project budget:

Secure storage space.
Data curation and cleaning costs.
Repository deposit fees (where applicable).
Data management training.

Many funders allow these costs to be included in the total project budget.

How should I update the DMP?

Review it periodically (e.g., in each progress report).
Record changes in data, formats, repositories, or responsibilities.
Document decisions about disposal, anonymisation, or preservation.
Keep previous versions archived for traceability.

What are the most common mistakes when drawing up a DMP?

Treating the DMP as a mere bureaucratic requirement.
Not updating it during the project.
Lack of adequate documentation.
Storing it in unsafe or personal locations.
Using paid or proprietary software without conversion.
Failure to define licences or sharing repositories.
Ignoring legal and ethical aspects.
Failure to plan for preservation.
Failure to anticipate costs or responsibilities.
Ignoring the GDPR and ethical aspects.

Where can I find examples of well-designed PGDs?

OpenAIRE ARGOS Template Gallery: https://argos.openaire.eu
DMPonline Example Plans: https://dmponline.dcc.ac.uk
FCT / Ciência Aberta Portugal — examples and templates in Portuguese: https://www.ciencia-aberta.pt

Who can help me with data management?

Research support offices at your institution.
University libraries and data services.
Data managers or digital curators.
FCT, OpenAIRE and UNESCO Open Science — they provide guides and training.

Where can I learn more about research data management?

Useful resources:

Open Science Portugal Portal: https://www.ciencia-aberta.pt
UNESCO Open Science: https://www.unesco.org/en/open-science
FCT – Data Management Guide: https://www.fct.pt/apoios/cienciaaberta
OpenAIRE – Data Management: https://www.openaire.eu
GO FAIR Principles: https://www.go-fair.org/fair-principles

How does good data management contribute to my scientific career?

It increases the credibility and reproducibility of your research.
It facilitates collaborations and new publications.
It meets the requirements of funding bodies (e.g. FCT, EU).
It allows for greater impact and visibility, with citations of datasets (DOIs).

Open Access publication according to FCT Policy

What is open access?

Open Access means that the results of scientific research — articles, books, chapters, theses or dissertations — are available free of charge for reading and consultation, without payment barriers. The new policy of the Foundation for Science and Technology (FCT), in force since February 2025, requires that all publications resulting from FCT-funded research be made available in open access, without embargo periods.

To whom does the FCT policy apply?

The policy applies to all publications resulting, in whole or in part, from FCT funding. This includes scientific articles, books, chapters, monographs, doctoral theses and master’s dissertations. Authors must ensure that their publications comply with open access requirements, even when they share authorship with researchers from other entities or countries.

What types of publications are covered?

Peer-reviewed scientific articles;
Books, book chapters and monographs;
Doctoral theses and master’s dissertations.

For all these types, the publication must be available in open access through an RCAAP network repository or by direct publication in open access publishers/journals.

What are the possible open access publication routes?

There are three alternative routes recognised by FCT policy:

Gold Open Access: direct publication in journals or publishers that make the content available in open access from the moment of publication. This may involve the payment of fees, provided they are eligible and comply with FCT rules.
Green Open Access: deposit of the final accepted version (accepted manuscript) in an RCAAP network repository, without embargo. Even if the publisher keeps the final version under subscription, this route complies with FCT policy. No fees are payable.
Via Transformativa: publication in hybrid journals that are transitioning to the open access model, under recognised transformative agreements. No fees are payable. The conditions negotiated for open access publication under transformative agreements are negotiated and reviewed cyclically. The journals included in the transformative agreements can be consulted on b-on, with searches carried out by publisher.

What are the steps for publishing in open access?

Plan ahead — select journals and publishers that are compatible with open access routes. Confirm the journal’s policy in Open Policy Finder
Retain rights — negotiate the right to deposit the accepted manuscript in the institutional repository.
Submission — check whether the journal/publisher allows deposit in RCAAP and adopts open licences (e.g. CC BY). Confirm the journal’s policy in Open Policy Finder
Deposit — after acceptance, deposit the accepted version in the institution’s repository or in RCAAP, with complete metadata.
Dissemination — include the repository link in ORCID profiles, CVs and other scientific channels.

Frequent situations

If the journal does not allow deposit: choose another publication channel or negotiate the retention of rights.
Embargo periods are not permitted — access must be immediate.
The version to be deposited is, as a general rule, the manuscript accepted after peer review.
If there are international co-authors, the FCT policy remains applicable.

Benefits of open access

Publishing in open access increases the visibility, impact and reuse of research results. It promotes transparency, scientific collaboration and public return on investment in science.

Putting it into practice. How to publish?

The FCT offers a step-by-step guide to searching for open access publications depending on the type of document you wish to submit (article; book chapter; thesis and dissertations), in order to ensure compliance with the FCT’s Open Access Policy.

Guide available at this link: https://acessoaberto.fct.pt/

Official sources and useful resources:

– FCT – Open Access: https://acessoaberto.fct.pt

– FCCN – New Open Access Policy: https://www.fccn.pt/atualidade/nova-politica-acesso-aberto-promove-visibilidade-investigacao-cientifica/

– RCAAP – Portuguese Open Access Repositories Network: https://www.rcaap.pt