Case study: A brief review of online visualisation tools that can help There is a growing range of online tools to help users their data. This brief review highlights four online visualisation tools that can help. The links page also links to lots more useful resources. Online tools that can help visualise data (these tools are free to use, but any data uploaded is typically then available on the system for other users) highlighted below include: On the resources and links page, we also link to free software applications and libraries for visualising data, and development languages for more sophisticated data visualisation.
Mondrian (software) Mondrian is a general-purpose statistical data-visualization system. It features outstanding visualization techniques for data of almost any kind, and has its particular strength compared to other tools when working with Categorical Data, Geographical Data and LARGE Data. All plots in Mondrian are fully linked, and offer various interactions and queries. Any case selected in a plot in Mondrian is highlighted in all other plots. Currently implemented plots comprise Mosaic Plot, Scatterplots and SPLOM, Maps, Barcharts, Histograms, Missing Value Plot, Parallel Coordinates/Boxplots and Boxplots y by x. Mondrian works with data in standard tab-delimited or comma-separated ASCII files and can load data from R workspaces.
5 of the Best Free and Open Source Data Mining Software The process of extracting patterns from data is called data mining. It is recognized as an essential tool by modern business since it is able to convert data into business intelligence thus giving an informational edge. At present, it is widely used in profiling practices, like surveillance, marketing, scientific discovery, and fraud detection. There are four kinds of tasks that are normally involve in Data mining: * Classification - the task of generalizing familiar structure to employ to new data* Clustering - the task of finding groups and structures in the data that are in some way or another the same, without using noted structures in the data.* Association rule learning - Looks for relationships between variables.* Regression - Aims to find a function that models the data with the slightest error.
Pavel Risenberg Nooblast Project inspired by the old days Noösphere concept. Visualization picks the real-time data from public APIs and calculates overall strength of signal (recent network buzz) for two given keywords. Some picked events have geolocation information, so they mapped on the globe in the exact points. The overall strength visualized around the globe as “noo”-cloud, the size of which reflects event streams and shaped by geotagged data, building light abstract visual structures-snapshots in space for each term. It explores abstract visual component of generated crowd sourced info streams as the visual connection attaching you to the pulse of planet.
gource visualisation tool Gource is a software version control visualization tool. See more of Gource in action on the Videos page. Introduction Software projects are displayed by Gource as an animated tree with the root directory of the project at its centre. Directories appear as branches with files as leaves. Developers can be seen working on the tree at the times they contributed to the project.
Gallery "Spike" map Interactive United States population density map. Average rating: 7.5 (23 votes) 2D histogram An extension of the concept of histogram to display the colour image content. Average rating: 4.8 (5 votes) claudio martella In the past, I’ve written about Google Pregel. At the time, as it was quite obvious, there was no implementation of anything like Pregel out there of any kind, not to mention Open Source. Now things have changed, so I’d like to give a quick list of the projects out there that might help you getting started with this technology, as I see that very often people ask what the difference is between all of them. I have direct experience only with the Java implementations, so I can talk about them a bit more extensively. As you remember from my last post, Pregel is a framework for large-scale graph processing that builds on top of the BSP computational model. It allows the developer to write a vertex-centric algorithm for graph processing (meaning you write a function that receives messages from vertices and sends messages to other vertices) and forget about things as distribution and fault-tolerance.
Data Mining Image: Detail of sliced visualization of thirty video samples of Downfall remixes. See actual visualization below. As part of my post doctoral research for The Department of Information Science and Media Studies at the University of Bergen, Norway, I am using cultural analytics techniques to analyze YouTube video remixes.
How to become a data visualization ninja with 3 free tools for non-programmers We noticed many times between the lines of this blog how data visualization is in the hype and how this trend is growing and growing. That’s good news guys! It’s fun and it’s … success! But as more and more people join this wild bunch we have to take care of those who are not as skilled as we are yet. There are many people out there who love data visualization but they think they are out of this business because they are not able to code.
75+ Tools for Visualizing your Data, CSS, Flash, jQuery, PHP Most people would agree that the old adage “A picture is worth a thousand words” is also true for web based solutions. There should be no discussion – Charts and Graphs are ideal to visualize data in order to quickly deliver an overview and communicate key messages. Whatever type of data presentation you prefer or suits you data (pie charts, bubble charts, bar graphs, network diagrams etc.), there are many different options but how do you get started and what is technologically possible? In this article tripwire magazine present more than 75 Tools for Visualizing your data on a website and most of the options available will be covered.
Open Source Text Analytics by Seth Grimes Open source is a great choice for many text analytics users, especially folks who have programming skills, who need custom capabilities or who are trying to get a feel for possibilities before committing themselves. Excellent options are available for all these users. Tools such as Gate, NLTK, R and RapidMiner share the low cost, power, flexibility and community that have driven adoptionof open-source software by individual users and enterprises alike. RapidMiner even combines text processing with business intelligence (BI) and visualization functions. This article will look at open source text analytics, focusing on those four tools.