Research Data Guide
The purpose of this guide is to aid researchers at the University of Cádiz (UCA) with the correct management of research data as part of best practices in scientific research and with the drafting of a Data Management Plan (DMP). The manner in which data will be used during any research project should be defined from the outset. 

The guide is made up of different sections outlining aspects to be taken into account when managing research data. It includes a series of general and UCA-level guidelines and recommendations. Links to resources for further information, tools, etc. are also included.
Research Data and Open Data
According to the OECD (Organization for Economic Cooperation and Development), research data are factual records used as primary sources for scientific research, and that are commonly accepted in the scientific community as necessary to validate research findings. Research data generally comes from a unique source and is difficult or impossible to replace. (OECD Principles and Guidelines for Access to Research Data from Public Funding, 2007).

Research data may include:
  • numerical scores, textual records, images and sounds.
  • raw, processed, experimental or observational data.
Data include: field notebooks, primary research data (including paper and computer data), questionnaires, audio tapes, videos, model development, photographs, films and test checks and responses.

The following are not considered final research data: laboratory notes, partial data sets, preliminary analyses, drafts of papers, plans for future research, peer reviews, personal communications with colleagues and physical objects, e.g. laboratory samples.

Open data is data that can be freely used, re-used and redistributed by anyone and subject, at most, to measures that preserve provenance and openness.  and that is subject, at best, to the requirement of attribution and sharing in the same way that it appears. This concept is related to Open Science.

Open research science is a broad concept relating to open access to science. It encompasses open access, usually referring to open access to publications, and open research data, which is open access to research data.
If you have any queries regarding the content of this guide, please contact CAU Repositorio institucional RODIN.

Contact person for the guide

Charo Gestido

Carmen Franco Barroso

Latest update of the guide
This guide was last updated in December 2023.
Regulations at European level

The European Commission has been promoting open access policies and measures since 2006, notably the Open Access Mandate of the European Research Council and the Open Access Pilot Project (European Commission, FP7) in 2008. To support this project, the OpenAIRE network (with FECYT as the Spanish National Office) and the DRIVER project were created. The programme currently in force is Horizon Europe.

Horizon Europe - EU Framework Programme for Research and Innovation (2021-2027)

Horizon Europe is the new framework programme for investment in research and innovation for 2021-2027, continuing and reinforcing the support for open science promoted under the previous programme.

Open science includes open access, open replicable research, open science assessment and open data. To this end, the Horizon Europe Programme focuses on two actions:
  • Mandatory open access for publications: the beneficiaries must retain sufficient intellectual property rights to comply with open access obligations.
  • Ensuring open access to research data in line with the principle “as open as possible and as closed as necessary”: mandatory FAIR (findable, accessible, interoperable and re-usable) data management plan and open research data.
Source: Presentación del Programa [Presentation of the Programme]

Horizon 2020 - EU Framework Programme for Research and Innovation (2014-2020)
Adopted by the European Commission in December 2013, Horizon 2020 integrates previous funding programmes such as the 7th R&D Framework Programme (FP7). It prescribes mandatory open access to peer-reviewed research articles resulting from Horizon 2020-funded projects within 6 months of publication (12 months for social sciences and humanities)(Guidelines to the Rules on Open Access to Scientific Publications and Open Access to Research Data). It also includes the launch of a pilot programme for research data.

Open Research Data Pilot

This provides for the open access deposit of research data needed to validate the results presented in scientific publications deposited in repositories (known as “underlying data”) (Guidelines on FAIR Data Management in Horizon 2020).

As of 1 January 2017, this pilot scheme was extended to all areas of the framework programme with the aim of improving and maximising access to and re-use of research data generated by projects.
Plan S

This is an initiative for open-access science publishing launched in 2018 by Science Europe through “cOAlition S”, a consortium set up by the European Research Council and the main national research agencies and funding organisations of twelve European countries. The final version was launched following a revision in 2019 under the slogan ‘Making full and immediate Open Access a reality’.

The plan consists of 10 principles, guidance on its implementation and a single objective: to accelerate the transition to open access to publications.

The main objective of the plan is to ensure that with effect from 2021 all scholarly publications on the results from research funded by public or private grants provided by national, regional and international research councils and funding bodies must be published in Open Access Journals, on Open Access Platforms, or made immediately available through Open Access Repositories without embargo.
Open Science
How to comply with Open Access Mandates
How to comply with Horizon 2020 Mandates
Regulations at national level
National Mandate

The deposit of publications in open access repositories is regulated at national level by Spanish Law 14/2011 of 1 June on Science, Technology and Innovation. This mandate is also included in the Spanish Science, Technology and Innovation Strategy and in the State Plan for Scientific and Technical Research and Innovation.
- Ley 17/2022, de 5 de septiembre, por la que se modifica la Ley 14/2011, de 1 de junio, de la Ciencia, la Tecnología y la Innovación
This reform furthers the goal of making research results immediately available in open access, whether scientific publications, data, codes or methodologies. The title of section 37 has been changed to ‘Open Science’.

 Ley 14/2011, de 1 de Junio, de la Ciencia, la Tecnología y la Innovación

Section 37: Open access. The amended section refers to the development of open access repositories for the publications of researchers whose research activity is mainly financed by public funds.

Estrategia Española de Ciencia, Tecnología e Innovación 2021-2027 (EECTI)

 The EECTI 2021-2027 includes open access as one of its guiding principles and views open science as an opportunity for our national R&D system, as well as underscoring the role of institutional repositories. 

Plan Estatal de Investigación Científica y Técnica y de Innovación (PEICTI)

The State Plan is the main instrument of the General State Administration to develop and achieve the objectives of the EECTI. The current EECTI for 2021-2027 is developed under two State Plans, with the State Plan for 2021-2023 currently being implemented.
Doctoral Theses
Real Decreto 99/2011 of 28 January regulates official doctoral studies, establishing the obligation to deposit approved doctoral theses in open access in the corresponding institutional repository.
– Real Decreto 99/2011, de 28 de Enero de 2011, regulating official doctoral studies

Section 14.5: This section expressly states that once a doctoral thesis has been approved the University will be responsible for its deposit in open electronic format in an institutional repository.

Spanish Universities

Commitments by Universities to Open Science

In 2019, the General Assembly of Crue Universidades Españolas approved a document outlining ten specific actions to promote Open Science in line with other similar European institutions and associations.
FECYT recommendations
The Spanish Foundation for Science and Technology (FECYT) supports the implementation of open access policies in Spain.
Commitments by Universities to Open Science
University of Cádiz
Universities are adopting measures to promote open access for both research projects and articles deriving from grants issued by them and doctoral theses. In the case of the UCA:


– Regulation UCA/CG06/2012, of 27  June 2012, regulating the organisation of doctoral studies at the University of Cádiz

Section 33: This section provides that the UCA is responsible for depositing doctoral theses in open electronic format in its Institutional Repository.

Framework regulation UCA/CG07/2012, of 13 July 2012, on Bachelor`s Degree and Master`s Degree Final projects of the University of Cádiz

Section 7.3: This section provides that papers receiving a grade of 9 or higher will merit incorporation of a digital copy in the Institutional Repository with open access.

Institutional Repository of the UCA

RODIN is the Institutional Repository of the UCA. Established in 2010, it allows authors to deposit their documents in compliance with the institutional regulations and enhance their visibility and impact.
Benefits of Open Access
RODIN, Institutional Repository of the UCA
Research Data Management
Research Data Management (RDM) is present in all phases of research and encompasses the collection, organisation, documentation, storage and preservation of the data used or generated during a research project.

Proper data management helps researchers to carry out better research and ensures:
  • Compliance with the requirements of funding agencies.
  • Greater transparency for the validation of research results.
  • Improved data protection and minimisation of the risk of data loss.
  • Findable, accessible, interoperable and re-usable data (FAIR).
  • Time savings by avoiding duplication and making efficient use of available resources.
  • Enhanced researcher profiles, impact and visibility of projects.
Data management phases

Research planning 
  • Policies and mandates 
  • Data management Plan 
  • Data collection or generation

Organisation and storage
  • Data processing and analysis
  • Data preservation
  • FAIR Principles

Dissemination and sharing
  • Data deposit
  • Assignment of licences
  • Data citation
The data cycle
Recommendations for Research Data Management
​Managing research data: best practices

Informative guide on best practices in research data management prepared by the Servei de Biblioteques, Publicacións i Arxius of the Universitat Politècnica de Catalunya and translated in the Information and Reference Section of the Library Service of the Universidade da Coruña.
Research planning

Good planning is the best way to ensure data quality, multiplying its value both during the research project and following its completion. This requires the development of a Data Management Plan (DMP) for each project. The agencies funding public and private research require not only availability in open access of scientific publications deriving from the research, but also appropriate dissemination and management of the underlying data of those publications.

The Data Management Plan (DMP)

The DMP is not a final document and will evolve over time, acquiring more precision and content throughout the course of the project. The first version of the DMP should be delivered within the first 6 months of the project. More detailed and complete versions may be delivered at later stages of the project. The DMP should be updated at least once in the middle of the project and again at the end to make any necessary adjustments, given that not all data or potential uses of the data are clear from the outset. New versions of the DMP must be created whenever there are major changes to the project due to the inclusion of new datasets.
Funding agency requirements
Under the Horizon 2020 Programme (2014-2020) the open access mandate was bolstered and extended to cover research data, including establishment of an Open Research Data Pilot.

Under the current Horizon Europe Programme (2021-2027), DMPs are mandatory for all projects generating or re-using data within the first six months of the project in order to:
  • Guarantee open access to research data according to the principle “As open as possible, as closed as necessary” by depositing data in a trusted repository under a Creative Commons (CC BY), public domain (CC0) or equivalent licence.
  • Comply with the requirement to prepare a Data management Plan for FAIR (findable, accessible, interoperable and re-usable) data and open research data.

If open access (to some or all data) is not provided, this must be justified in the DMP (Horizon Europe Model Grant Agreement).
Data Management Plan
 A Data Management Plan (DMP) is a document that describes how research data collected or generated in the course of a research project will be processed, what data will be collected or generated, which methodology and standards will be applied, how data will be shared and/or made open access and how data will be curated and preserved.

Guidelines for preparation of a Data Management Plan  

Tools for the Data management Plan  Tool developed by the Digital Curation Centre (DCC), UK. Free tool by the MADROÑO Consortium, adaptation and translation into Spanish of the DMPonline management tool and the Guidelines on FAIR Data Management in Horizon 2020. Online tool developed by OpenAIRE for creation, management, dissemination and linking of DMPs. Service included in the European Open Science Cloud (EOSC), an initiative promoted by the European Commission. Factsheet Argos

Recommendations for researchers 
The Spanish Network of Open Research Data (Maredata), published recommendations for research data management in 2018

Funding agency policies
The Sherpa Juliet  directory provides information on the policies and requirements of project funding agencies.
Designing a Data Management Plan
A Data Management Plan should address the following aspects:
Project Information

This includes: Project name and identification, Project description, Institution, Funding agency, Principal Investigator and identifier (ID), Contact details, DMP (versions).
1. Data summary

The data to be used in the project should be described in general terms, including the type and format, purpose, size and source of the data, as well as its utility.
2. FAIR Data

2.1. Making data findable, including provisions for metadata
Include identifiers, keywords and metadata standards describing them to optimise the possibility of discovery.

2.2. Making data accessible (Repository, Data and Metadata) 
Indicate the repository where the data will be deposited and whether it assigns an identifier to the data, justification for any closed data, how long any embargoes apply for and whether there are any restrictions on use, as well as whether the metadata will be open access.

2.3. Making data interoperable
Describe the data vocabularies, standards, formats or methodologies to be used to allow data exchange and interoperability.

2.4. Increase data re-use
Document the provenance of the data and provide the necessary information to validate data analysis and facilitate its re-use, e.g. with readme files. Indicate the licences for use of the data.
3. Other research outputs

Consider issues relating to FAIR data which may be applied to the management of other research outputs generated or re-used under the project such as software, workflows, protocols, new materials, samples, etc. and how these will be managed, shared or made available for re-use in line with the FAIR principles.
4. Allocation of resources 

Indicate the costs to make the data FAIR (e.g. direct and indirect costs relating to storage, archiving, re-use, security, etc.) and who will be responsible for managing the data.
5. Data security

Ensure that the data is securely stored in trusted repositories for long-term preservation and curation.
6. Ethical aspects

Outline any ethical or legal issues that may have an impact on data sharing. In addition, where the research uses personal data, reference should be made to aspects such as informed consent and long-term preservation.
7. Other issues

Describe whether other national/funder/sectorial/departmental procedures will be used for data management..
Summary based on the Horizon Europe Data Management Plan (DMP)Template.
Data collection
In order to collect data on a certain scientific field, certain tools may be used to consult or re-use data already stored by other researchers such as directories of research data repositories and data repositories: The Registry of Research Data Repositories is an important source of information on more than 2,450 research data repositories which may be browsed by subject, type or country.

ZenodoEuropean repository providing access to research results in Europe as part of the OpenAIRE initiative.

Figshare. Research data repository for preservation and sharing of all the data and results generated by research processes.

Dimensions. Platform that indexes datasets, facilitating access to data deposited in repositories and databases.

DataCiteSearch. Search engine for open datasets equipped with DOI.

European Union Open Data Portal. Open data portal of the EU. Open data portal of the Spanish Government.

Data Gov.  Open data portal of the US Government.
Data Management Plan
DMP guide and template UCA
Guide and template based on the Horizon Europe Data Management Plan Template. It may be used with tools such as DMPonline, PGDonline, Argos, etc. as it addresses the issues raised in a Data Management Plan.

Data Protection
Regulations to be taken into account for the processing of personal data: 

Implementing legislation 

Transparency and Data Protection Good Practice Guide (CRUE)

UCA Data Protection Officer
Go to the section Anonymisation
Organising and storing data
In order to organise and document the data, the following aspects need to be taken into account:

Choosing the right format
At the research planning stage, it is important to consider the format your files will be stored in. Following selection of the data, in order to ensure preservation, open access and usability the data should be converted into standard formats that most programs are able to interpret.

File naming and structure
A well organised and coherent file structure with clearly defined, meaningful names helps to find information quickly and accurately. It is very important to consider the hierarchy, structure, names and versions of files, especially when working in a team.

Storing data securely
It is important to choose an adequate means of storing the research data you are working with in your project.

Describing research data
The description of the data should include the information necessary to know who created the data or the source of the data if collected, the data type and format, any related data, who can use the data and when it can be used. This documentation should be available together with the data to aid with its interpretation where required. This detailed description (metadata) is essential for correct interpretation of the data.
Processing and analysing data
The format and software for creation and digitisation of research data generally depends on the type of analysis to be done by the researcher, the hardware used, the availability of software or even the customs of a specific discipline.

Even if researchers use the data format and software best suited to their analysis, once completed they should consider conversion to more interchangeable and durable standard formats for storage.

To ensure access and long-term preservation, the following considerations should be taken into account [FECYT, 2012]:
  • Open, non-proprietary formats should be used whenever possible.
  • The format used must allow indexing of the content for potential retrieval.
  • A data compression format uses less storage space.
  • The format chosen should be standard (IANA MIME types) or de facto standard for the research community.

Set out below is a list of recommended file formats depending on the type of data they contain:
  • Databases: XML, CSV
  • Text: TXT, ODT, RTF, XML
  • Statistics: ASCII, DTA, POR, SAS, SAV
  • Tabulated data: CSV, TSV
  • Geospatial: SHP, DBF, GeoTIFF, NetCDF
  • Video: OGG, MP4
  • Sound: FLAC, WAV, AIFF, MP3
  • Images: TIFF, BMP
  • Compressed files: the use of compressed files is not recommended

Further information on recommended formats for files containing research data may be obtained from the UK Data Service.
Preserving data
It is essential to choose the most appropriate way to store ‘active’ research data, i.e. data being used in the research project. The following should be taken into account:
  • Ease of access for authorised persons while restricting unauthorised persons
  • Backup system compatible with the storage system
  • Data security, especially when working with personal and/or sensitive data
  • Security issues relating to sending of data via email and sharing copies of data
  • The specifications, if any, of the funding agency

Data may be stored in:
  • PC/laptop
  • Optical storage (CDs, DVDs)
  • External drives (USB, hard drives)
  • Institutional storage services
  • Cloud services (OneDrive, Google Drive...)

Storage services at the University of Cádiz

The use of institutional storage services is recommended. At UCA Cloud Storage  you can find information regarding the storage systems existing at the UCA:
  • UCA Drive (open source software Nextcloud, 500 GB/user)
  • Google Drive (500 GB/user)
  • Microsoft OneDrive (1 TB/user)
FAIR Principles
The research data must comply with the FAIR (Findable, Accessible, Interoperable, Re-usable) principles so it is essential to attach metadata describing the research data in a complete and standardised manner.

The  FAIR Data Principles  were introduced in 2016 to help provide a set of guiding principles to be considered by all stakeholders involved in the research ecosystem to ensure that research results are findable, accessible, interoperable and re-usable.

In order for a dataset to comply with the FAIR Principles it is important to consider the following:
  • Does the dataset have a persistent identifier (handle, DOI)?
  • Is there documentation/metadata to help understand the data properly?
  • Is the metadata accessible?
  • Has a usage licence been attached to the dataset? Is it a standard licence? Does it impose any restrictions? Does it specifically allow for re-use?
  • Are the dataset files in open or widely supported proprietary formats?
  • Is the dataset/metadata encoded according to a global standard?
  • Is the dataset linked to other datasets or other research results? How?
Organising files

Infographic prepared by Grup de treball de Suport a la Recerca of the CSUC and translated by the Research Support Section of the University of Seville.
When working with personal data, it is mandatory to guarantee the privacy and anonymity of the persons involved. For this purpose, it is necessary to anonymise the data.

Data anonymisation is the process of removing the possibility of identifying individuals. 

To anonymise data, OpenAire recommends using the Amnesia tool.
UCA Cloud Storage

UCA Drive
Based on the open source software Nextcloud.

We can access our data in three different, non-exclusive ways:

1. Through a web application at

2. With a synchronisation client, by installing a programme on our PC or laptop, the Nextcloud synchronisation client, and configuring a local folder to synchronise with our cloud.

3. With a mobile client. Without synchronisation, by remote access with the application for Android or iOS mobile devices.
Help for integration from the old UCA Drive system (Owncloud, 5 GB/user).
Dissemination and sharing
The following options exist to disseminate and share data:

Repositories: Many funding agencies, institutions and academic journals have mandates and policies on Open Access publication of research data. Compliance with these mandates and policies is usually achieved through the deposit of research data in a data repository.

Data Journals: In addition to Open Access dissemination of research data through repositories, the option also exists of publishing the data in data journals. These journals publish data papers, which are articles that focus on the data itself (description, methodology, motivation, etc.) and not on the hypotheses, analyses and conclusions drawn from the data.

Licences: As stated in the Guidelines to the Rules on Open Access to Scientific Publications and Open Access to Research Data in Horizon 2020, it is desirable to attach user licences to the datasets generated.

Data citation: It is important to cite research data. Like articles, monographic publications, etc., datasets are also research results. Citation facilitates identification and access to the data and thus its location, validation and re-use, allows the authorship of its creators to be recognised, facilitates determination of the metrics and impact of the data and favours the transparency of scientific research.
Data deposit
Funding agencies and bodies are required to deposit data in open access via thematic data repositories or institutional repositories.

The Institutional Repository of the UCA. RODIN  grants free access to the scientific and academic works generated by the University of Cádiz and allows the deposit of research data.

It is possible to deposit research data in RODIN via delegated archiving by sending the necessary data to

The following documentation must be sent:: 
The Readme file contains additional information for interpretation and re-use of the data.

RODIN assigns a DOI identifier to datasets to facilitate data verification, citation, dissemination, re-use, impact and long-term access.
Data may also be deposited in thematic repositories (by consulting directories such as Re3data or Data Repositories), multidisciplinary repositories (such as Zenodo or Figshare) or together with scientific publications.
Institutional Repository of the UCA
RODIN is the repository of Teaching and Research Objects of the University of Cádiz, the purpose of which is to compile, preserve and disseminate the documentation resulting from the UCA’s scientific, teaching and institutional activity.
Assignment of licences
The Guidelines on Open Access to Scientific Publications and Open Access to Research Data in Horizon 2020  state that “as far as possible, projects must then take measures to enable third parties to access, mine, exploit, reproduce and disseminate (free of charge for any user) this research data.” The use of widely recognised licences is recommended in order to define the terms of use to be complied with for re-use of the data.

Creative Commons 4.0 licences may be uses to indicate permitted uses.  CC0 y CC-BY licences are recommended for open research data. Data-specific licences such as the Open Data Commons may also be used.

It is important to note that depending on the research project and the agreement with the project funding agency it may be necessary to apply an embargo period during which data cannot be accessed. Alternatively, the agency should explicitly state the mandatory deadlines for public dissemination and under what terms. The policies of funding agencies may be consulted on Sherpa Juliet.

Also in line with the general principle “As open as possible, as closed as necessary” contained in the Guidelines on FAIR Data Management in Horizon 2020, there are situations that justify not making research data openly available, such as: existence of confidentiality clauses, possibility of commercial or industrial exploitation, etc.
Data citation
The data must be cited correctly following a specific citation format and must appear with the rest of the bibliographic references of the resulting publication. 

DOI Citation Formatter  is a service offered by DataCite that automatically builds citations according to the style selected based on the DOI assigned to the data.

Citing research data:
  • Facilitates identification and correct attribution to their creator
  • Facilitates data re-use and verification
  • Allows monitoring of their impact
  • Creates an academic structure that recognises and rewards data producers

For proper citation of research data, the following is recommended:
  • Include as a minimum: Author, Date, Title, Resource Type and Persistent Unique Identifier
  • Uniquely identify research data by means of a Persistent Unique Identifier (DOI)
  • Cite each dataset independently
Citing your research data
SEA-EU policies on Research Data Management


reSEArch-EU is an H2020 Project by the European University of the Seas (SEA-EU). The University of Cádiz coordinates the project together with the partner universities of the European consortium SEA-EU, the universities of Western Brittany (France), Kiel (Germany), Gdansk (Poland), Split (Croatia) and Malta.

Among other actions, it is working on the development of a joint research plan, the generation of open science platforms and joint databases, the promotion of co-creation policies with the main socio-economic actors of the territory and the scientific exploitation of research results, along with various activities to bring science, technology and innovation closer to people of all ages and from all backgrounds.

The goals of the reSEArch-EU  project are:
  • To implement research data management policies in SEA-EU partner universities.
  • To provide common principles and guidelines for policy makers responsible for research management in SEA-EU partner universities.
  • To facilitate the research data management, preservation and dissemination process.
  • To facilitate the dissemination, visibility and impact of research data generated by the SEA-EU AllianceSEA-EU Research Data Management Policy Framework.
SEA-EU policies for the promotion of open science in the consortium developed by the University of Malta and agreed by the other partners of the Alliance.
SEA-EU Research Data Management Toolkit
The SEA-EU Alliance recognises research data as a valuable asset, pivotal for academic research and its contribution to society. To this effect, the implementation of Research Data Management principles and practices within the SEA-EU partner universities is fundamental to ensure that research data is organised in a harmonised fashion throughout the entire research lifecycle. It also supports the protection, archiving and sharing of data, as and where appropriate. 

The purpose of this RDM Toolkit is to serve as a guideline with relevant information on how to effectively manage, preserve and disseminate research data in order to maximise the potential of research. Additionally, it equips researchers with the necessary resources to develop Data Management Plans (DMPs) in line with the FAIR data principles.
The Open Access movement
Open Access is a movement that aims to facilitate access to scientific information through the internet for use by the scientific community. The author of an open access publication retains control over the integrity of his or her publications, which must be cited and acknowledged as his or her own.

The benefits of publishing in open access include:
  • Increased impact of researchers’ scientific output due to the greater visibility of publications.
  • Visibility brings with it an increase in the number of citations.
  • Repercussion of its impact on the University which, as an institution, also benefits from better positioning of its authors.
  • Access to a greater number of papers without subscription costs.
  • Guaranteed long-term electronic preservation of research results
The Institutional Repository of the UCA

RODIN is the Repository of Teaching and Research Objects of the University of Cádiz, the purpose of which is to compile, preserve and disseminate the documentation resulting from the UCA’s scientific, teaching and institutional activity.

More information