Increasing returns of scale and scope, which arises in the use of Data, has created a new concept called big Data that analysis of them leads to boosted productivity through Data Innovations. Since there is no model in the current literature of “Data innovation”, the purpose of this research is to provide a logical model of “Data innovation” to determine its impact on business development, and in particular the electronics business. In this model, the Data generated using electronic business tools are calculated as inputs of the model. Afterward, in the process of the model, the types of innovations and big Data technologies are performed, which ultimately leads to the development and improvement of the business. Also, when describing the types of “Data innovation”, the concepts of Open government Data information and Open innovation are employed. The use of e-business and the generating of new Data and the repetition of this process and the comprehensive model in “Data innovations” account the innovations of this research.

After offering an overview of some of the main themes of Popper’s political thought, the paper argues that his account faces two problems relating to institutions. The first is that while Popper stresses the ‘rational unity of mankind’, and the potential for any of us to furnish criticisms of public policy, it is not clear what institutional means currently exist for this to enable this to take place. Second, Popper has stressed the conjectural character of even our best theories. However, at any point, some theories will have fared better in the face of criticism than others, and they may give us important information about constraints on our actions. At the same time, as ordinary citizens we may not be in a good position to understand the theories in question, let alone appraise the state of the specialised discussion of them. There is, it is suggested, a case for thinking of ways to institutionally entrench such fallible theories, especially in the current setting in which social media play an important role

The neoclassical growth model is tested by use of panel Data procedure in this research. In the econometric test, simoultanously time series and cross detection will be compared on the basis of panel Data method through which their observed points increase and consequently the estimation efficiency will be increased. The examination of neoclassical growth theory has been done with reference to external & internal factors of 52 selected countries from 1960 to 2000. The independent variable of model has been selected on the basis of the result of previous research which explains the result in three separate models: developed countries, developing countries, and whole countries. These factors are such as: Gross National Products with lag of period, work force age, growth rate, education level, the change of capital accumulation and economic trade volum. The consequences of this research is that: neoclassical growth model can explain the major part of economic growth of the countries with use of internal variables. Also with the use of panel procedure of fixed effect, we can see the fundamental differences and structure of the growth process for different countries; and show how the economic, and social conditions affect on the growth.

Purpose: The purpose of this study is to investigate the general characteristics (technical dimension, access and communication and participation) and the general characteristics of the Data set of Iran's Open Data portals. Methodology: This is a descriptive survey study. A questionnaire with 28 criteria distributed among 30 Ph. D. students in Information Systems is based on the framework used in the research of Renata Má, chová, 1 and Martin Lně, nič, ka. Findings: The average score of general characteristics of the Open Data portal with 33. 22 is higher than general characteristics of the Data set with the average score of 24. 87. Overall score of the quality of components of Iranian Open Data portals is 91. 29. The highest score obtained among the portals is related to Iran's Open Data portal (108. 1). Conclusion: The results of comparing the average quality of Iran's Open Data portals show that the quality of these collections is at a low level. Comparing the average score of the quality of Iran's Open Data portals (108. 1) with the three leading countries in the field of Open Data included Britain, India, and the United States (higher than 124) shows that Iran is not in a favorable position. It is necessary to pay attention to policy in the field of Open Data quality.

The conversion of published Data by government to a value and social effect is not done automatically and requires a number of actors with different functions that by activating and connecting them with each other, we can use Data. The sum of these actors, stakeholders and their functions is called the Open Government Data Ecosystem. This study aims to understand the ecosystem of Open government Data and analysis of selected Open government ecosystem models is formed. Present study is an exploratory study that seeks to analyze international models of Open government Data ecosystem, and identify and monitor the elements and components of the Open government Data ecosystem. Open government Data ecosystem models were redefined and its contents were extracted by content analysis method and then compared and evaluated. Units in this study are Open government Data ecosystem models and sampling is targeted sampling. In the first stage, 36 models were identified by searching and reviewing the models of Open government Data ecosystems. Finally, by studying these models and identifying the similarities and aggregating of some models, based on targeted sampling, the researchers considered 12 models of Open government Data ecosystem and by examining them they extracted the Data and information from these models. The reason for choosing these 12 models is their reputation, influence, comprehensiveness and authority. By examining existing models, it has become clear that there is still no comprehensive model of an Open government Data ecosystem that could be the basis for developing an Open government Data policy. Summarizing or generalizing, paying attention to a part of the ecosystem, using a cyclic or value chain approach instead of ecosystems approach, and some of the models are an experience or specific area of the characteristics of ecosystem models.