Plagiarism detection system’s privacy statement | SeAMK.fi

Plagiarism detection system's privacy statement

Articles 13 and 14 of the EU General Data Protection Regulation

Data Protection Act (1050/2018)

Articles 13 and 14 of the Combined Data Subject Information Document (EU Data Protection Regulation 2016/679)

1. Controller

Seinäjoki University of Applied Sciences, SeAMK Library
Kampusranta 11, Frami F
FI-60320 Seinäjoki, Finland
+358 20 124 3000
seamk(at)seamk.fi

2. Controller’s representative

Johanna Säilä-Jokinen, Director of Administration, Seinäjoki University of Applied Sciences
johanna.saila-jokinen(at)seamk.fi

2a. Official responsible for the personal data file

Jarkko Meronen, Planning Officer, Library Services, Seinäjoki University of Applied Sciences
tel. +358 40 8304250
jarkko.meronen(at)seamk.fi

2b. Contact persons in matters relating to the data file

Jarkko Meronen, Planning Officer, Library Services, Seinäjoki University of Applied Sciences
tel. +358 40 8304250
jarkko.meronen(at)seamk.fi

2c. Contact details of the Data Protection Officer

Jarmo Jaskari, Data Protection Officer, Seinäjoki University of Applied Sciences
tel. +358 40 868 0680
jarmo.jaskari(at)seamk.fi

3. Name of the data file

Plagiarism detection system

4. Purpose of processing personal data/data file use

The plagiarism detection system compares an electronic text document submitted by a SeAMK student or a SeAMK employee to publications, databases and websites available in the internet.

Personal data are used to identify users.

The personal data of server log files are used to:

  • Link the teacher to the right analysis in the programme.
  • Examine technical or support issues and to investigate any service misuse.

5. Purpose of maintaining the data file

Enables the use of this service by connecting the document reviewer, the analysed document and the document author.

5a. Data content of the file

The data stored on the teacher and supervisor when an ID is created: user ID, name, home organization email address, system analysis address.

When a student submits his or her work for review, his or her email address is stored to the file. Students have a choice to submit their names with their email address. Students can also create their own IDs in the system. In this case, the student’s user ID and name are saved in addition to his or her email address.

As a copyright holder, the student has the right to decide on the use of his thesis as a reference source in system in other organisations using same system. This is defined via the link in the submitting confirmation message. The work is recorded at the time of transmission of the work and the inspection analysis report.

The use of the plagiarism detection system is part of the assessment of the study unit, and the student cannot prohibit the use of the system in reviewing his or her work.

The teacher and the supervisor have the right to see the work submitted by the student for inspection, the time it was sent and the analysis report.

The personal data of persons with a user ID are stored in the system as long as the user is an system user. The right to log in to the system is discontinued when the person’s employment relationship with the university of applied sciences ends or the student’s right to study ends.

The analysis reports are stored in the system for 25 months.

5b. Information systems using the data file

  • Plagiarism detection system
  • Learning Platform

6. Regular sources of data

The teacher asks the students to submit their work to be reviewed by email to an system analysis address provided by the teacher or to a study unit activity in the learning platform .

When the student submits the text by email, the supervising teacher will receive an email message from the system once the analysis is complete. The email contains an overview of the analysis and a link to the analysis report.

The teacher can forward the analysis email to the student or any other supervisors.

7. Regular disclosure of data

Email messages sent from the system to the teacher (the percentage of similarity with comparison databases and a reference to the longest single quotation, the work submitted by the student for the analysis).

The analysis report can be linked to the activities in a learning platform study unit.

The student is informed of the text similarity percentage revealed by the analysis. The teacher can also determine the settings for the learning platform activity to make the entire analysis report available to the student.

Students must always be given an opportunity to familiarise themselves with the analysis report created by the system on their thesis.

Personal data are not disclosed to any third parties.

8. Transfer of data outside the EU or the EEA

No data stored in the file is transferred outside the EU or the EEA.

9. Principles of data file protection

A.      Manual material

B.      Computer-processed data

Users log in to the system and register with the system through the Haka joint user identification system of Finnish higher education institutions. The operator of the Haka trust network is CSC – IT Center for Science Ltd.

Alternatively, the data file administrator can use the management feature to create a user ID at the request of a specific user.

All system data are protected by firewall technology and access rights.

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