نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه مدیریت فن آوری اطلاعات ، واحد بین المللی کیش، دانشگاه آزاد اسلامی، جزیره کیش، ایران
2 گروه مدیریت فناوری اطلاعات، دانشکده مدیریت و اقتصاد، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
3 گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه آزاد اسلامی، واحد کرج، دانشگاه آزاد اسلامی، واحد کرج، ایران
4 گروه مدیریت فناوری اطلاعات، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In the digital age, data governance has become one of the key issues in information technology policy-making and law. Given the expansion of processing and exchange of personal data, there is an increasing need for a native model for data governance in Iran. The absence of an integrated and indigenous framework in this field has led to various challenges, including privacy violations, inconsistency in the implementation of data policies, and reduced user trust in digital services. Therefore, this research aims to propose a framework for the establishment of data governance with a focus on privacy in Iran.
Data governance is one of the most important topics related to emerging technologies, especially in developing countries like Iran, where it requires special attention. While developed countries, particularly in the European Union and the United States, have comprehensive laws and regulations for personal data protection, Iran faces numerous challenges due to the lack of a coherent and unified framework in this field. Some of these challenges include privacy violations, breaches of legal principles in data management, and the weakness in establishing supervisory and judicial bodies. In this context, offering a native model designed with attention to Iran's cultural, social, and legal conditions is deemed essential.
The research method of this study is applied-developmental and has been implemented using a mixed approach (quantitative and qualitative). In this study, efforts have been made to gather reliable data through various methods to design a data governance model. The required data have been collected through document analysis, interviews with 58 experts in the fields of technology and law, and the Delphi method. Data analysis has been carried out using content analysis and confirmatory factor analysis.
The proposed model in this study consists of three main dimensions: legal-political, technical-technological, and organizational-supervisory, with six key components and 24 operational indicators in total. The legal-political dimension involves the formulation of laws that are appropriate for Iran's context and the creation of effective supervisory frameworks. In this dimension, it is essential to update existing laws on personal data protection and to pass laws to address privacy violations. Lawmakers must pay attention to models like the European Union's General Data Protection Regulation (GDPR) and adapt them to Iran's cultural and legal conditions. Additionally, this dimension requires the establishment of effective and independent regulatory bodies.
The technical-technological dimension focuses on the development of data security infrastructure and the adoption of modern technologies to protect information. In today's world, where cyber threats are rapidly increasing, security infrastructures are essential to protect personal data and prevent its breach. This dimension emphasizes that emerging technologies such as encryption, blockchain, and AI-based systems should be incorporated into data governance processes to ensure data security. Furthermore, the development of these technologies should be in line with privacy laws and policies.
The organizational-supervisory dimension emphasizes the need to create independent and accountable institutions to effectively implement data policies. In this regard, various governmental and non-governmental institutions must have clear responsibilities in overseeing the execution of data policies. These institutions must actively protect users' rights against potential breaches of privacy and have sufficient executive authority to deal with offenders. Additionally, creating synergy between governmental, private, and public institutions is essential for the effective implementation of these policies.
The research results indicate that implementing this model can reduce privacy violations and increase user trust in digital services. A comparison of the proposed model with international regulations such as the EU's GDPR and the California Consumer Privacy Act (CCPA) showed that it can be adapted to Iran's legal infrastructure. This adaptability could pave the way for improving domestic laws and establishing national standards in the field of data governance.
The successful implementation of this model requires the reform and updating of related laws, the creation of independent regulatory bodies, and the adoption of a combined approach to data policy-making and security technologies. The establishment of this framework could play a crucial role in improving personal data protection, reducing cybercrimes, and increasing public trust in digital services. Moreover, the implementation of this model could enhance transparency in data processes, improve collaboration between the public and private sectors, and contribute to the development of the digital economy.
Ultimately, the results of this research could serve as a foundation for policy-making decisions in the field of data governance in Iran, paving the way for sustainable development in the realm of data governance. It is recommended that future studies assess the operational impact of this model and examine new indicators to improve its effectiveness. This research could serve as a starting point for legal and executive reforms in the field of data governance in Iran.
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