نوع مقاله : مقاله پژوهشی

نویسنده

• فرامرز صحرایی

استادیار علوم سیاسی و روابط بین‌الملل، پژوهشکده فرهنگ و ارتباطات دانشگاه علامه طباطبائی، تهران، ایران.

چکیده

هدف از انجام این مطالعه تبیین وضعیت کیفیت داده در دولت الکترونیک و تأثیر آن بر حکمرانی داده در ایران است. این مطالعه از نظر هدف کاربردی بوده و با استفاده از روش تحلیل محتوای کیفی انجام گرفته است. در این مطالعه با روش اسنادی به مدل‌های کیفیت داده، مدل‌های دولت الکترونیک، شاخص‌های حکمرانی داده، برترین تجربیات بهبود کیفیت داده و نیز پژوهش‌های پیشین مربوط به کیفیت داده مراجعه می‌شود. نخست به برترین تجربیات در این زمینه به روش مرور نظام‌مند در پایگاه‌های استنادی و اطلاعاتی مطالعه پرداخته می‌شود. سپس به روش مشاهده سندی، اسناد بالادستی همانند ﺳﻨﺪ ﺭﺍﻫﺒﺮﺩ ﻣﻠﻲ ﺗﻮﺳﻌﻪ ﺩﻭﻟﺖ ﺍﻟﻜﺘﺮﻭﻧﻴﻚ، برنامه ششم توسعه جمهوری اسلامی ایران، سند چشم‌انداز 20 ساله، قانون انتشار و دسترسی آزاد به اطلاعات، نقشه جامع علمی کشور، سند تحول دولت مردمی، سند ملی تحول دیجیتال، سند جامع دولت الکترونیک و سند راهبردی نظام جامع فناوری اطلاعات جمهوری اسلامی ایران مورد بررسی قرار می‌گیرد. در پایان، کیفیت داده در دولت الکترونیک و اثرگذاری آن بر حکمرانی داده در کشور ایران تحلیل گردیده و پیشنهادهایی برای بهبود سند راهبرد ملی توسعه دولت الکترونیک کشور از بعد اهمیت به کیفیت داده ارائه می‌شوند. در مجموع می‌توان بیان داشت، کیفیت داده نقش بسزایی در حکمرانی داده دارد. نخست، داده‌های باکیفیت بنیان تصمیم‌گیری هستند و تصمیم‌گیری‌های دولتی به ویژه در شرایط بحرانی نیازمند داده‌های دقیق و قابل اعتماد است. داده‌های دقیق و یکپارچه باعث کاهش دوباره‌کاری‌ها، صرفه‌جویی در هزینه‌ها و افزایش بهره‌وری می‌شوند. از سوی دیگر، با بهره‌گیری از داده‌های باکیفیت، دولت‌ها می‌توانند شفاف‌تر عمل نموده و به نیازهای شهروندان بهتر پاسخ دهند که در نهایت به اعتماد بیشتر شهروندان و مشارکت آن‌ها در سطوح گوناگون حکمرانی داده منجر خواهد شد.

کلیدواژه‌ها

• کیفیت داده
• دولت الکترونیک
• حکمرانی داده
• اثرگذاری
• مدل‌های دولت الکترونیک

عنوان مقاله [English]

An Analysis of Data Quality in E-Government and Its Impact on Data Governance in Iran

نویسنده [English]

• Faramarz Sahraei

Assistant Professor, Department of Political Science and International Relations, Faculty of Research Institute of Culture and Communication, Allameh Tabataba’i University, Tehran, Iran.

چکیده [English]

Introduction
In the digital transformation era, where technology and enterprise systems so much at the core of change for the way organizations and governments operate, data quality is considered one of the success factors for e-government. Due to particular dimensions and characteristics associated with data, data quality is vital for e-government. First, from the aspect of data quality, high-quality data records assist the Government in determining the right kind of service and addressing the needs of the citizens. Furthermore, data quality also plays an important role in government analysis and reporting. With quality data, the governments can carry out relevant and correct analyses and formulate their policies on factual evidence, real needs of the citizens, and information. Therefore, the purpose of this study was to examine the status of data quality in e-government and its impact on data governance.
Literature review
Numerous studies have been conducted in the e-governance models and structure. These studies can be categorized in three groups: studies related to e-governance and data governance, studies of data quality, studies that explain the role of e-governance in data governance. In the first group, Sarfarazi (2009); Nouri et al. (2019); and Zeynali Soume’eh, Pourazat, and Doodangah (2013) analyzed the e-governance models and frameworks. These studies identified factors, categories, concepts, functions and relationships between e-governance and developing new systems. In this regard, Meiyanti et al. (2018) had dealt with the problems inherent in the implementation of e-government in developing countries. They found organizational, managerial, human, and infrastructure challenges as the foremost with regard to e-government development in a given context.
The second category is followed by studies that revolve around data quality and its dimensions. Previous research Mollaii and Tahmasebi (2019); Khodizadeh et al. (2020); identified accuracy, validity, timeliness, and completeness as the main dimensions of data quality. These are also stressed in contexts of e-government and data governance. The third category embraces those studies that treat data quality specifically for e-governments. For instance, Bonyadi et al. (2023) designed a data quality management model for data governance by using the meta-synthesis method. They ended up with 12 main categories (including data characteristics, data, data files, data value, primary data value, data models, datasets, data access, data integration, data formatting, metadata, and objectivity) and 47 subcategories relevant to data quality management towards effective data governance.
Methodology
This study was applied in nature and employed a qualitative content analysis method. Using a documentary approach, models of data quality, e-government models, data governance indicators, best practices for improving data quality, and prior research on data quality were reviewed. In the first section, the best practices in this area were studied through credible reference and information databases. Subsequently, upstream documents such as the National Strategic Plan for E-Government Development, the Sixth Development Plan of the Islamic Republic of Iran, the 20-Year Vision Document, the Law on Freedom of Information, the Comprehensive Scientific Map of the Country, the Transformation Plan for a Popular Government, the National Digital Transformation Document, Comprehensive Document of Electronic Government, and Strategic Document of the Comprehensive Information Technology System of the Islamic Republic of Iran were analyzed. Finally, data quality in e-government and its impact on data governance were analyzed, and recommendations were proposed for improving the National Strategic Plan for E-Government Development with a focus on data quality.
Findings
The research revealed that e-government dimensions include: electronic services, intelligent processes, IT infrastructure, open government, services-oriented government, process improvement, legal and regulatory aspects, data analytics, data protection, transparency, efficiency, data liberation, data accessibility, citizen participation, and others. Data quality dimensions differ with every dimension of the government. They have a direct bearing on efficiency, transparency, effectiveness of service, and consequent outputs. In respect of electronic services, data accuracy and integrity are severely considered. On the other hand, the study shows that in data governance, the policymaking process, access management and permissions to data, monitoring and evaluation, data security, integrity management of data, data completeness with regard to data-related policies and regulations, privacy, data ownership, transparency and accountability, stakeholder participation, data ethics and equity, data interoperability, and value creation from data are of paramount importance. In this regard, various dimensions of data quality lay at the very foundation of each of these components of data governance.
Analysis of some of the key national policy documents in Iran shows that e-government is indeed considered as a major axis within the macro-level policymaking. They highlight transparency and ease of access to governments, which are part of the Law on Disclosure and Free Access to Information that also emphasizes transparency and better use of data. The quality of data—especially correctness, correctness, accessibility, and timeliness—is important in achieving this goal. It is clear from the dictates of these documents that processes in government such as taxation systems, health services, and civil registrations are all strongly dependent on the integration and standardization of data. Without access to high-quality data, inaccuracy becomes the order of the day in these systems, which are then prone to inconsistencies and errors in processing. It is worth noting that data security, integrity, and reliability are key components in achieving effective governance in e-government. The E-Government Transformation Document emphasizes the creation of intelligent systems, the elimination of redundancy, information accessibility, and the improvement of digital service quality. These goals can only be realized with accurate, up-to-date, and integrated data. In line with this, the Sixth Development Plan points to the development of information infrastructure and the participation of the private sector in electronic services. In this context, data quality not only requires trustworthiness and security but also the establishment of data exchange standards between public and private sector organizations.
Conclusion
The findings of this article indicate that various factors influence data quality in Iran’s governmental systems. One major factor affecting data quality is poor policymaking. Governments lacking clear policies for collecting, processing, and updating data often suffer from unstructured, outdated, and duplicate data, resulting in reduced accuracy and quality. A data-driven culture influences the recognition of the importance of accurate and reliable data in decision-making, ultimately enhancing overall data quality. E-government requires accurate and up-to-date data to deliver better services. In this context, the role of citizens must not be overlooked, as a portion of the data is provided directly by them—for example, during registration on government platforms or when submitting online requests. If citizens do not enter their information correctly, the quality of the data deteriorates. Therefore, governments should encourage citizens to provide accurate and complete information. Overall, it could be said that data quality goes beyond technical aspects and also includes managerial, human, and process-related dimensions. This holistic approach is necessary to improve data quality, as poor-quality data can lead to challenges such as flawed decision-making, inefficiency in public services, and diminished public trust. In contrast, high-quality data not only improves e-government services but also enhances government transparency, accountability, and efficiency. Thus, governments must adopt appropriate policies and invest in both technical and human infrastructures to ensure the quality of their data.

کلیدواژه‌ها [English]

• Data Quality
• E-Government
• Data Governance
• Impact. E-government models