Open Data Principles: Open Government Data (OGD)

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Open Data Principles” is referred to as Open Government Data (OGD).
“Open Government” is a term that is used to describes a worldwide trend for governments to become more open, transparent, accountable and efficient. Open
Government is a cultural change towards new relationships between governments and citizens and other stakeholders based on dialogue and collaboration. Open
Government policies embrace the use of modern Information and Communications
Technologies (ICT) as well as digital information and data as a means to create more meaningful interactions between citizens and governments and build better public services. Although OGD is a vital part and precondition for any successful Open
Government initiative it is also obvious that OGD …show more content…

As business technology has advanced exponentially in recent years, data-driven decision making has become a much more fundamental part of all sorts of industries, including important fields like medicine, transportation, and equipment manufacturing.
Data-driven decision making is also known as data-driven decision management or data-directed decision making. The idea of data-driven decision making is that decisions should be extrapolated from key data sets that show their projected efficacy and how they might work out. Businesses generally use a wide range of enterprise tools to get this data and to present it in ways that back up decisions. This is in stark contrast to the way that decision-making had been done throughout the history of commercial enterprise, where before the presence of new complex technologies, individuals often made decisions based on observation or informed guesswork.
These days, if one wants to know how a given product might perform in a market, what a customer might think of a slogan, or where to deploy business resources, decision support software can help. That has led to a much bigger demand for …show more content…

The dataset must be relevant to the question at hand. It also must be timely, accurate, clean, unbiased; and perhaps most importantly, it has to be trustworthy. I have often heard that data scientists spend 80% of their time obtaining, cleaning, and preparing data, and only 20% of their time building models, analyzing, visualizing, and drawing conclusions from that data. In my experience, this is entirely

plausible. Also, I want to remark, that even if we do have quality data, and even if we have a lot of quality data, we will only get so far and; despite the hype that we might hear, it does not make us data-driven. Some people, especially certain big data vendors and service providers, pimp big data as a panacea. The hard truth is that data alone is not enough. A small amount of clean, trustworthy data can be far more valuable than petabytes of junk. Data must be accessible and query-able. When we say that we have accurate, timely, and relevant data, though, is not sufficient to count as data-driven. It has to be also: Joinable, which mean, that the data must be in a form that can be joined to other enterprise data when necessary. Another important thing is that the data

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