Yogyakarta, October 22nd 2021─DEMA FISIPOL UGM held a Research Class X Big Data on Big Data Visualization through Zoom Meeting on Friday (22/10). The speakers in this event were Wegik Prasetyo and Vendi A. Nugroho as Polgov Big Data researchers. The event started at 07.00 p.m. and was attended by a number of students and the general public.
Starting the discussion, Wegik explained about the big data research flow, namely the discovery of problem statements, followed by a research question containing key research questions, data resource selection, crawling, processing, and visualization. In presenting data, visualization is very important as a data representation to make it easier for readers to understand the data. Several kinds of data visualization are text visualization, table visualization, and graphic visualization consisting of point, line, and bar elements. Vendi explained, plain text is used to explain 1 or 2 numbers, while tables and graphs are suitable to explain many numbers.
“Text is usually used to visualize data with small data sets, tables are used when we need to communicate data to diverse audiences and present data with various metrics,” he said. The thing that should be avoided is visualizing data with tables when presenting data directly because usually visualizing data in front of an audience requires the extraction of patterns. That way only certain points are needed by the audience.
Regarding data triangulation, it is necessary to confirm the truth of the information/data by at least confronting the findings with similar topics. Meanwhile, in the context of big data, bots, buzzers, and online news duplication are often the question of whether to check or not. In this case, Wegik said that the way we confirm the truth of the information/data depends on how we as researchers treat the data. That is what is then called methodological consistency. “What is clear is that the truth in the social sciences group is very constructive, what certain parties believe to be true is very constructive, the key is when we believe in data it is methodological consistency,” he said.
The last presentation is about how we interpret data. Data is information that is still scattered, which describes a certain phenomenon. Data can turn into information when the data is classified according to its cluster. Then, information will become knowledge when the same information is connected to each other. Knowledge can also be a constructive insight when the knowledge that we have compiled meets other knowledge. Likewise, when several insights are connected, it will become wisdom or policy.