Today you can easily find software or web applications to visualize graph data of various natures. Bakamap is a web application to visualization your spreadsheet data as interactive graphs. Companies started to provide enterprise-ready graph visualization solution, as did Linkurious back in 2013. Others understood the potential of graph visualization and how such tools could help organizations and businesses in other fields: network management, financial crime investigation, cybersecurity, healthcare development, and more. However, graph visualization is no longer the preserve of the academic and research worlds. ![]() More recently in 2016, the research project OSoMe (the Observatory on Social Media) released an online graph visualization application to study the spread of information and misinformation on social media. For instance, Palladio, a graph visualization web application for history researchers was created in 2013. Other research projects emerged, as web technologies simplified their creation. Co-founded by Linkurious’ CEO, Sébastien Heymann, Gephi played a key role in democratizing graph visualization methods. In the same line, the Gephi software, created in 2008, brought a powerful open source tool to many researchers in the field of Social Network Analysis. After Pajek, other solutions were released, such as NetMiner in 2001, a commercial software for exploratory analysis and visualization of large networks data. As we mentioned earlier, the first off-the-shelf solutions spawn from the work of network theory researchers. These solutions are either, Saas, or on-premise software and web applications. There are other solutions which do not require any development. ![]() Most of the tools we are about to present can be plugged directly to database and analytics systems to further the analysis of graph data. You need to quickly assess the fraudulence of flagged transactions? You guessed it, graph visualization. You need to understand the human dynamic between criminal networks? Graph data visualization. You need to identify shady financial schemes in terabytes of data? Graph data visualization. And graph visualization tools are useful in many scenarios. Once data is stored and calculations are done, end-users need an intelligible way to process and make sense of the data. It is also the reason graph visualization solutions are complementary to the graph analytics and graph databases tools we discussed in the previous articles. And in addition, it will be easier to share and explain your findings through a visual medium.Ĭombined with the capabilities brought by computer machines, these advantages opened new doors for analysts seeking information in large volumes of data.You will compare situations or scenarios more easily.You can digest larger amounts of data more easily.You have a greater ability to recognize trends & patterns.When you apply visualization methods to data analysis, you are more likely to cut the time spent looking for information because: ![]() As we previously wrote, graph visualization is critical for the analysis of graph dat. There is a reason researchers started to develop these tools. Even though these applications have long been confined to the field of research, it was the birth of computer tools for graph visualization. In the field of graph theory and network science, researchers started to imagine graph analysis and visualization tools as early as 1996 with the Pajek project. Graph visualization tools turn connected data into graphical network representations that takes advantage of the human brain proficiency to recognize visual patterns and more pattern variations. Representing connected data in tables is not intuitive and often hides the connections in which lies the value. While it’s easy to read and comprehend non-graph data in a tabular format such as a spreadsheet, you will probably miss valuable information if you try to analyze connected data the same way. It helps surface information and insights leading to the understanding of a situation, or the solving of a problem. Visualization tools represent an important bridge between graph data and analysts. For decades, visual representations have helped researchers, analysts and enterprises derive insights from their data. The visualization of information has been the support of many types of analysis, including Social Network Analysis. The third layer of graph technology that we discuss in this article is the front-end layer, the graph visualization one.
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