eprintid: 10593 rev_number: 8 eprint_status: archive userid: 2 dir: disk0/00/01/05/93 datestamp: 2024-01-24 23:30:22 lastmod: 2024-01-24 23:30:23 status_changed: 2024-01-24 23:30:22 type: article metadata_visibility: show creators_name: Zahid, Reeba creators_name: Altaf, Ayesha creators_name: Ahmad, Tauqir creators_name: Iqbal, Faiza creators_name: Miró Vera, Yini Airet creators_name: López Flores, Miguel Ángel creators_name: Ashraf, Imran creators_id: creators_id: creators_id: creators_id: creators_id: yini.miro@uneatlantico.es creators_id: miguelangel.lopez@uneatlantico.es creators_id: title: Secure Data Management Life Cycle for Government Big-Data Ecosystem: Design and Development Perspective ispublished: pub subjects: uneat_eng divisions: uneatlantico_produccion_cientifica divisions: unincol_produccion_cientifica divisions: uninimx_produccion_cientifica divisions: uninipr_produccion_cientifica divisions: unic_produccion_cientifica full_text_status: public keywords: big data; data life cycle; GBDE; secure data life cycle abstract: The rapid generation of data from various sources by the public sector, private corporations, business associations, and local communities is referred to as big data. This large and complex dataset is often regarded as the ‘new oil’ by public administrations (PAs), and data-driven approaches are employed to transform it into valuable insights that can improve governance, transparency, digital services, and public engagement. The government’s big-data ecosystem (GBDE) is a result of this initiative. Effective data management is the first step towards large-scale data analysis, which yields insights that benefit your work and your customers. However, managing big data throughout its life cycle is a daunting challenge for public agencies. Despite its widespread use, big data management is still a significant obstacle. To address this issue, this study proposes a hybrid approach to secure the data management life cycle for GBDE. Specifically, we use a combination of the ECC algorithm with AES 128 BITS encryption to ensure that the data remain confidential and secure. We identified and analyzed various data life cycle models through a systematic literature review to create a data management life cycle for data-driven governments. This approach enhances the security and privacy of data management and addresses the challenges faced by public agencies. date: 2023-07 publication: Systems volume: 11 number: 8 pagerange: 380 id_number: doi:10.3390/systems11080380 refereed: TRUE issn: 2079-8954 official_url: http://doi.org/10.3390/systems11080380 access: open language: en citation: Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica Universidad Internacional Iberoamericana México > Investigación > Producción Científica Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés The rapid generation of data from various sources by the public sector, private corporations, business associations, and local communities is referred to as big data. This large and complex dataset is often regarded as the ‘new oil’ by public administrations (PAs), and data-driven approaches are employed to transform it into valuable insights that can improve governance, transparency, digital services, and public engagement. The government’s big-data ecosystem (GBDE) is a result of this initiative. Effective data management is the first step towards large-scale data analysis, which yields insights that benefit your work and your customers. However, managing big data throughout its life cycle is a daunting challenge for public agencies. Despite its widespread use, big data management is still a significant obstacle. To address this issue, this study proposes a hybrid approach to secure the data management life cycle for GBDE. Specifically, we use a combination of the ECC algorithm with AES 128 BITS encryption to ensure that the data remain confidential and secure. We identified and analyzed various data life cycle models through a systematic literature review to create a data management life cycle for data-driven governments. This approach enhances the security and privacy of data management and addresses the challenges faced by public agencies. metadata Zahid, Reeba; Altaf, Ayesha; Ahmad, Tauqir; Iqbal, Faiza; Miró Vera, Yini Airet; López Flores, Miguel Ángel y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, yini.miro@uneatlantico.es, miguelangel.lopez@uneatlantico.es, SIN ESPECIFICAR (2023) Secure Data Management Life Cycle for Government Big-Data Ecosystem: Design and Development Perspective. Systems, 11 (8). p. 380. ISSN 2079-8954 document_url: http://repositorio.uneatlantico.es/id/eprint/10593/1/systems-11-00380.pdf