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Challenges and opportunities with using cognitive computing for mapping personal data in order to help comply with the GDPR

Hedqvist, Lukas LU and Månsson, Henrik LU (2018) INFM10 20181
Department of Informatics
Abstract
As the world is becoming more digital, the use of data is rapidly increasing. To protect all EU citizens from privacy and data breaches, the regulations will become stricter. The General Data Protection Regulation (GDPR) will become effective on the 25th of May 2018. This will mean big structural changes for organizations, but it will also mean tougher requirements for gathering and maintaining personal data. The GDPR changes how personal data is defined, meaning that the same laws will apply to all personal data. Furthermore, the GDPR requires organizations to map and identify personal data in both structured and unstructured data sources before the it becomes effective. In this thesis, a case study of a project has been conducted, in... (More)
As the world is becoming more digital, the use of data is rapidly increasing. To protect all EU citizens from privacy and data breaches, the regulations will become stricter. The General Data Protection Regulation (GDPR) will become effective on the 25th of May 2018. This will mean big structural changes for organizations, but it will also mean tougher requirements for gathering and maintaining personal data. The GDPR changes how personal data is defined, meaning that the same laws will apply to all personal data. Furthermore, the GDPR requires organizations to map and identify personal data in both structured and unstructured data sources before the it becomes effective. In this thesis, a case study of a project has been conducted, in which the challenges and opportunities with using cognitive computing for mapping personal data in order to help comply with the GDPR, have been identified. The findings present several challenges and opportunities with using cognitive computing in this specific context. Identified challenges were amongst others the need for manual work and human contributions. Identified opportunities were amongst others that it can understand structured and unstructured data and be learned to identify personal data. (Less)
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author
Hedqvist, Lukas LU and Månsson, Henrik LU
supervisor
organization
course
INFM10 20181
year
type
H1 - Master's Degree (One Year)
subject
keywords
GDPR, personal data, cognitive computing, unstructured data, mapping data
report number
INF18-013
language
English
id
8949538
date added to LUP
2018-06-19 13:31:14
date last changed
2018-06-19 13:31:14
@misc{8949538,
  abstract     = {{As the world is becoming more digital, the use of data is rapidly increasing. To protect all EU citizens from privacy and data breaches, the regulations will become stricter. The General Data Protection Regulation (GDPR) will become effective on the 25th of May 2018. This will mean big structural changes for organizations, but it will also mean tougher requirements for gathering and maintaining personal data. The GDPR changes how personal data is defined, meaning that the same laws will apply to all personal data. Furthermore, the GDPR requires organizations to map and identify personal data in both structured and unstructured data sources before the it becomes effective. In this thesis, a case study of a project has been conducted, in which the challenges and opportunities with using cognitive computing for mapping personal data in order to help comply with the GDPR, have been identified. The findings present several challenges and opportunities with using cognitive computing in this specific context. Identified challenges were amongst others the need for manual work and human contributions. Identified opportunities were amongst others that it can understand structured and unstructured data and be learned to identify personal data.}},
  author       = {{Hedqvist, Lukas and Månsson, Henrik}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Challenges and opportunities with using cognitive computing for mapping personal data in order to help comply with the GDPR}},
  year         = {{2018}},
}