A Pattern to Recognition of Triggering Element of Open Government Implementation in Iran's Public Organizations (Case Study: Ministry of Interior)

Technology–oriented reforms, especially in the public sector, “with society being digital” has been put in the agendum of most countries throughout the world. It has become the topic of discussion for the contemporary governments. The pattern of “Open Government” by relying on “Open Data” is among the novel patterns for realizing such reforms. Data as driving forces for the government can result in values. Such value-added cannot be fulfilled without cooperation, participation and providing information to the people. It is regarded as the evolution of a closed system into an open system. Therefore, the present study aims at designing a pattern to the recognition of triggering elements of open government implementation.

This study is a fundamental one. The method of conducting in this research is qualitative and based on content analysis. The data and information have been collected through note taking based on library research. We have also tried to collect and analyze complementary data while interviewing academic and operational experts for the topic of study. The interviews took place purposefully with 16 skillful academic and operational experts in this field.

In the qualitative section of the study with open codification were extracted from the interviews, triggering elements of open government implementation, were recognized and prioritized.In the quantitative section of the study was done through a questionnaire and its validity was confirmed using CVR and CVI methods by academic expert.

 In open codification, 88 basic codes were extracted from the interviews with experts. This data was categorized into 5 major themes.Prioritization of qualitative section in this study was like a platform, accessing a real clarification for implementation of open government, free access to information, open governance data, employing technology as well as enjoying technological and governmental data.