Open Data | - CCMAR -

Digital and Data Management Policy


Digital data management is becoming increasingly important as national and European research infrastructures promote Open Science policies throughout the European Research Area. The EU Open Science policy encourages the sharing of scientific data and knowledge to enable greater scientific and industrial innovation and to increase the public understanding of the importance of science to society and social policy. These goals are primarily achieved through open access publication of scientific results, the deposition of scientific data in repositories and catalogues following FAIR data principles (data should be Findable, Accessible, Interoperable, and Reusable), and the dissemination of scientific knowledge to the public through outreach initiatives and the promotion of citizen science.


            EU-wide Open Science policies are designed to promote:

  • Research efficiency by sharing data and knowledge openly
  • Transparency of the scientific work process
  • Academic rigour and research quality
  • The development of new cross-cutting research themes
  • The development of public scientific literacy
  • The economic and social impact of science
  • Scientific recognition of research infrastructures and institutions


A useful guide to the issues surrounding data management is provided by Science Europe’s Practical Guide to the International Alignment of Research Data Management.



CCMAR promotes the principles of Open Science in all of it’s research activities, except where data may be restricted by private contract. It is mandatory for all research output from ESFRI (the European Strategy Forum on Research Infrastructures) RIs to follow the Open Science principles of open access and FAIR data publication. At the national level, open access publication of research studies is mandatory, while strict adherence to a FAIR data publication policy is dependent on the funding call. It is widely anticipated that future SR&TD Project Grant calls will enforce a FAIR data publication policy, so adhering to these principles for current research is strongly encouraged.


FAIR Data:

FAIR data principles encourage the publication of scientific data so that they are Findable, Accessible, Interoperable, and Reusable. They emphasise the need for scientific data to be accessible to automated computer-driven systems. In short, these goals can be achieved by providing sufficient metadata and depositing the data in appropriate open repositories. Metadata is information describing the data for publication, and typically includes unique identifiers and descriptors that follow standardised protocols, vocabularies, and ontologies. Many protocols and ontologies have been designed by research communities for specific research fields. For instance, the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) describes a conceptual checklist of metadata required to adequately describe a plant phenotyping experiment using an agreed upon vocabulary that has been designed by the research community. Likewise, individual research fields and topics may have dedicated open access data repositories where researchers can deposit their FAIR data, e.g. European Nucleotide Archive (EMBL-EBI). However, general data repositories also exist, such as EUDAT (EOSC) and Zenodo (CERN, OpenAire).


Data Management Plan (DMP):

A Data Management Plan describes the data management life cycle for the data to be collected, and the protocol to be followed to make the data findable, accessible, interoperable and reusable (FAIR). At present EU funding agencies require researchers to provide a DMP; a requirement that is likely to be standard at the national level in the near future, as they were on PT2020 grant applications.

A DMP should include information on:

  • what data will be collected, processed, and/or generated
  • which methodologies and standards will be used
  • how the data will be made FAIR and open access, and
  • how data will be curated and preserved at the end of the project

Various online tools are available to help researchers design an effective DMP.



Science Europe:

Open Science:

Open Science in Portugal:

European Research Area:

Portuguese National Bioinformatics Infrastructure|

European Open Science Cloud – EOSC-Life:

Portuguese Forum on Research Data Policy:

FAIR Data – Horizon 2020:

FAIR principles publication:

The Ontology Lookup Service (OLS):


Repositories and Services:


Zenodo (CERN, OpenAire):

OpenAire (Portugal):


Dataverse (Harvard):

GFBio (Germany):




Data Stewardship Wizard:

Data Stewardship Wizard (Portugal):


Marine Domain Catalogues and Services:




EMBL-EBI Magnify Marine Domain: