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Elaborate a publication: research data

 

The data generated during an investigation begin to be recognized as a source of own knowledge and independent of the publications that have given rise (books, articles, papers) and not only because they serve to validate the conclusions presented in these publications, Can generate new knowledge and be exploited in an interdisciplinary way.

A good management of the data generated in the development of an investigation guarantees its storage, accessibility and possible reuse.

 

 

 

 

What are the research data

Although there are multiple definitions due to the complexity of the topic, the OECD considers research data to:

  • All material that has been registered during the research, recognized by the scientific community and used to certify the results of research (Research Data)
  • The material that comes from a single source and it is difficult, or impossible, to obtain it again.

Data include statistics, results of experiments, measurements and observations resulting from the field study, surveys or interviews, images, etc.

Types of research data
  • According to the format
    • Text
    • Number
    • Images
    • Audio recordings
    • ...
  • According to the collection procedure
    • Experimental
      • Genetic Sequences
      • Chromatographs
    • Simulations
      • Climate models
      • Economic models
    • Observational
      • Surveys
      • Unrepeatable experiments

Management of research data

Research Data Management (RDM) encompasses all activities associated with the organization, structure, storage and processing of data used or generated during a research project.

This management consists of making decisions and actions, prior to the creation of the data, during its creation and use and throughout its life cycle, with the purpose of guaranteeing its storage, accessibility and possible reuse.

Improper data management can lead to loss of data or violation of privacy.

Publish data in open

Although data management does not imply open access, it is important to emphasize that open research data allow access and dissemination, freely and universally, and comply with the requirements of the official bodies that finance this research.

The Open Data movement, under Open Access, defines open data as those that can be used, reused and redistributed without any restriction other than the allocation or sharing requirement.

To identify usage permissions, there are several types of electronic licenses specific to open data sets. The most commonly used licenses are the Open Data Commons and the Creative Commons .

Benefits of publishing open data:

  • Encourages collaboration and avoids duplication of effort
  • Validate the results presented in scientific publications
  • Based on the results of previous research
  • Accelerates innovation and improves the transparency of the scientific process

Horizon 2020 and research data

Since January 2017 European projects funded by the European Union Research and Innovation Framework Program H2020 (with justified exception) will ensure open access to research data.

Projects participating in H2020 will develop a Data Management Plan (DMP), a first version of which is to be delivered during the first 6 months of the project and must deposit the data open in a repository.

These projects should make the research data available locatable, accessible, interoperable and reusable.

The philosophy with respect to the data is that they are:
"As open as possible, as closed necessary"
(As open as possible and restrict only what is essential)

The ethical and legal conditions impose a series of restrictions that must be taken into account during the entire data life cycle (intellectual property, industrial property, privacy or secrecy and protection of personal data).

Data management plan

A Data Management Plan (DMP) is a formal document to be carried out at the beginning of the research, which describes what we will do with the data during and after the end of the research, and which can be modified to Throughout the project.

The DMP specifies the topics on collection or creation, organization, documentation, sharing and preservation of data.

As we have indicated is mandatory for the projects participating in H2020 and should include the following steps (PGD Online).

Guidelines for elaborating the Data Management Plan

Support guides developed by the CSUC

Free tools to elaborate the Data Management Plan
  • DMP Online : developed by the Digital Curation Center with a template for the European Commission's H2020 projects.
  • PAGODA : translation into Spanish of the DMP Online tool, made by the Consorcio Madroño.
  • DMP CSUC : translation into Catalan of the DMP Online tool, carried out by the CSUC.

Repository for data

The data can be stored in repositories or in the editorial platforms along with the publications in the case of certain magazines that allow this option.

The repository selected to deposit the data must guarantee long-term preservation, ease of recovery and access to them.

Types of Data Repositories:

  • Thematic repositories: include research data from a specific disciplinary field. They can be located through the re3data irectory .
  • General Purpose Repositories: Any researcher can use it to preserve any type of research data. We can stand out :
    • Zenodo : multidisciplinary and international repository of research data, funded by the OpenAIRE project and recommended for European projects.

Comparative table of repositories made by the Library of the UPC

How to cite the data

Citing the research data guarantees its identification, location and a correct attribution to its creators.

The data should be cited just as it does with the publications. There are different formats for citing data sets and each discipline usually uses a particular style of appointment, as with articles, monographs, chapters, etc.

DOI Citation Formatter is a service offered by DataCite that automatically builds appointments according to the style we select from the DOI assigned to the data.


 

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