In language Translation System, the way Google does is testing algorithms with a trillion words, which means large also much messier dataset that come from the entire global Internet. The result turns out that the translation system runs better than any other systems else. In some fields, which can’t accept messiness like conventional sampling analysts, the way they deal with data is using multiple error-reducing strategies. In this way, specially trained experts collect samples according exact protocol, which is costly and long log. Thinking about not categorized content by tags for example; they are not well standardized and predefined. On the other hand, it makes the vastness of the Web’s content more navigable especially images, videos and music.
How to get access to data we need through such messy environment of Big Data seems require the Internet becomes more methodic. Since the birth of network science, people are tracing a more effective way to organize data on the Internet. The network science in some ways at first connected to physics, economics, biology, computer science, sociology and ecology. And the first documented mathematical analysis process is Euler’s (1783) analysis of the famous seven bridges crossing problem, which then he came up with the graph theory. And that was the first time a real space issue listed in an abstract term to show the bridges as links while isolated lands as resources. The development of graph theory dose influenced the principles of network science, because it established basic structure and form that interpret relationships between different links and resource on the Internet. There is no doubt that a well-structured network will considerably enhance the awareness of the hierarchy of resource. Graph drawing and network visualization are great helps for realize that target. And network visualization is under information visualization that employing elementary design principles, which aims at efficient and comprehensible representation of the targeted system. This will explores numerous phenomena such as technological networks, knowledge networks and biological networks. As a potential visual decoder of complexity, the practice is commonly driven by five key functions as: document, clarify, reveal, expand and abstract. In this case, the messy Big Data will promote its accuracy by being well structured.
Big Data has already shows its powerful aspects in the worldwide scale, and it dose provide possibilities for people to realize the arrangement of global resources as well as helps to the IoT better functioning.