IB, a quarterly journal, is dedicated to the latest advancement of Internet and Business, and the intersection of Economics with business applications. The goal of this journal is to publish cutting edge research and promote the research work in these fast moving areas. All manuscripts submitted to IB must be previously unpublished and may not be considered for publication elsewhere at any time during IB's review period.
This course is about scalable approaches to processing large amounts of information (terabytes and even petabytes). We focus mostly on MapReduce, which is presently the most accessible and practical means of computing at this scale, but will discuss other approaches as well.
Founded in 2004 we're a not-for-profit organization promoting open knowledge: that's any kind of information – sonnets to statistics, genes to geodata – that can be freely used, reused, and redistributed.
In the book The Art of War for Executives, Donald G. Krause interprets the following: “Sun Tsu notes, superior commanders succeed in situations where ordinary people fail because they obtain more timely information and use it more quickly.” For metadata professionals, this observation is increasingly relevant as more and more of the business seeks integration and federation, alignment with business goals and strategies, and agility - the ability to respond both quickly and accurately to change. Industry analysts and IT professionals are less focused on solutions to problems where metadata management plays a role but rather look more to metadata management as an overall strategy for the benefits it provides to multiple aspects of the whole organization.
Data presentation can be beautiful, elegant and descriptive. There is a variety of conventional ways to visualize data - tables, histograms, pie charts and bar graphs are being used every day, in every project and on every possible occasion. However, to convey a message to your readers effectively, sometimes you need more than just a simple pie chart of your results. In fact, there are much better, profound, creative and absolutely fascinating ways to visualize data. Many of them might become ubiquitous in the next few years.
We are an information science research group developing software and methodologies to exploit Internet-based data sources for social sciences research, in addition to scientometrics, link analysis, cybermetrics and webometrics.
The Open Knowledge Definition (OKD) sets out principles to define the 'open' in open knowledge. The term knowledge is used broadly and it includes all forms of data, content such as music, films or books as well any other type of information.
In the simplest form the definition can be summed up in the statement that "A piece of knowledge is open if you are free to use, reuse, and redistribute it".
Infoenthusiasts may exult in the sheer volume of raw data, & just as industrial revolution society learned how to process a glut of "atoms," we must now learn how to process this glut of "information."
What makes something “Information Visualization?” Is it just visual titillation? Or is it a tool that interprets, analyzes, and facilitates deeper understanding of data?
Open source graph visualization software. Takes descriptions of graphs in a simple text language, makes diagrams formatted as images, SVG for web, PS for PDF, GXL (XML dialect), and more.
Exemplary sites covered here include: WikiViz, FreeMind, Visualizious, Tree Radial Balloon Layout, Comment Flow, OneWord, Del.icio.us Network Explorer, Bubbl.us, ClusterBall, and data visualization of a social network.
This diagram depicts a spectrum of information sharing capabilities. Moving from lower right to upper left of the diagram, we see that more expressive forms of metadata and semantic modeling encompass the simpler forms, and extend their capabilities. From
This diagram depicts a spectrum of information sharing capabilities. Moving from lower right to upper left of the diagram, we see that more expressive forms of metadata and semantic modeling encompass the simpler forms, and extend their capabilities. From
G. Stumme, und K. Wolff. Proc. Intl. Symposium on Knowledge Retrieval, Use, and Storage for Efficiency, Seite 206-219. Vancouver, Canada, (August 1997)
