Appendices to the Open Science Policy at ÅAU (published on 2 March 2017)


APPENDIX: Terminology

Research data
The term “research data” refers to the resources that the researcher uses or produces during the research process. It is necessary to give information on the research data, at least regarding the origin of the data, in order to make data usable. Concerning digital data, this means that descriptive and technical information needs to be given, explaining what the data contains, i.e. metadata. We need information on the structure of the file or the files, the time of origin and possible processing that they have gone through. This information can be stored, for example in the metadata catalog of the data archive, in code records or other documents. “Research data” refers to this information along with the files themselves.

Metadata can be stored as a part of the data or in a separate directory, for exampl in a database. Metadata can be divided into three types depending on their purpose: 1. Descriptive metadata describes the content and the character of the material. This information is produced by the researcher himself/herself or by a third party, such as staff at a data archive. The recommendation is to use existing dictionaries, thesauri, classification systems and ontologies, which are often integrated into the information systems. 2. Administrative metadata defines necessary information on technical characteristics and legal issues. This information is important, especially regarding the long-term preservation of data. 3. Structural metadata describes the structure, for example in which ways different parts of a dataset relate to each other. Administrative and structural metadata can often be created automatically.

Open access
“Open access” means that scientific results are made openly available on the internet. “Scientific results” are mainly scientific papers, theses and reports. However, books, research data and metadata are also included. Open access means that the author gives everyone the right to read, download, copy and distribute the work in digital form. Full account is taken of the author’s statutory non-profit copyright. The author must be specified and the work must not be distorted. The main methods for open access publishing are internationally described with the terms “green” and “gold.”

Green open access
“Green open access” means that the researcher, as soon as the publisher allows it, will self-archive a peer-reviewed and edited version of the article in a digital archive, so called respositorium. The final version of the article is already published in a traditional, subscription-based journal.

Gold open access
“Gold open access” means that the researcher publishes his/her article at an open access publisher. Then, the book or article immediately becomes openly available on the internet. Gold open access usually requires a publishing cost paid directly by the researcher or his/her organization.

Hybrid publishing
The researcher can publish an article in a traditional subscription-based journal, and, for a fee make the article immediately made openly available. This kind of publishing is called “hybrid”.

Creative Commons (CC) is a copyright license that allows you freely to distribute material that is otherwise restricted by copyright. CC licenses are used when the author wants to give others the right to share, use and develop material and results that he/she has created. Under the license, the author can choose to open only parts of data or the entire data. Thus, the author always need to define which parts of the material and results he/she opens under the license. BY 4.0 is the internationally accepted version of the license. The Finnish initiative for open science and research recommend the use of CC BY 4.0-license, unless the content requires otherwise.

APPENDIX: Directives for data management plan

The researcher (also: the doctoral student, together with the supervisor) is responsible for making a data management plan connected to the research project. The researcher (the doctoral student together with the supervisor) can use a recommended tool for making the data management plan, for example, DMPTuuli. Moreover, he/she can choose freely to frame the plan, considering characteristic aspects of the research or the discipline, the intention and use of the plan etc.

In making a data management plan, at least the following aspects need to be considered:

  • the type of data collected and/or created
  • in which ways the data is collected and/or created
  • rights connected to the data (ownership, administration, copyright etc.)
  • who decides on how the data can be used
  • in which ways the informants or other collaborators will be informed
  • software to be used for storage and processing
  • how to guarantee the technical quality of the data
  • methods and formats for storage
  • which kind of user rights will be given to which user group
  • how back up is managed
  • how documentation is made when the data is processed
  • how metadata is saved
  • how data security issues are managed and guaranteed
  • possible specific aspects regarding different kind of data (for example, in which ways legislation regarding personal data and anonymization will effect management and publishing of data and results)
  • what will happen to the data when the project is finished

Examples of secure and qualified data bases and services for data storage (by March 2017):

  • IDA (all disciplines, Finnish storage service)
  • FSD (social sciences, Finnish storage service)
  • FIN-CLARIN (humanities, especially languages, Finnish storage service)
  • Zenodo (all disciplines, international storage service)
  • EUDAT (all disciplines, European storage service)

For more details regarding storage at the storage services (type of data accepted and for which purposes, rules for storage etc.), visit the website for each service.

 More information on open science: