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European Union regulators filed antitrust charges Tuesday against Amazon, accusing the e-commerce giant of using its access to data from companies that sell products on its platform to gain an unfair advantage over them.The charges, filed two years after the bloc’s antitrust enforcer began looking into the company, are the latest effort by European regulators to curb the power of big technology companies. Margrethe Vestager, the EU commissioner in charge of competition issues, has slapped Google with antitrust fines totaling nearly $10 billion and opened twin antitrust investigations this summer into Apple. The EU’s executive Commission also opened a second investigation Tuesday into whether Amazon favors product offers and merchants that use its own logistics and delivery system.

The EU investigation found that Amazon is accessing and analyzing real-time data from other vendors that sell goods on its platform to help it decide which new products of its own to launch and how to price and market them. That “appears to distort genuine competition,” Vestager said.Investigators focused on that practice in France and Germany, the company’s two biggest markets in the EU, but Vestager didn’t give specific examples of merchants affected by Amazon’s behavior.The stakes have risen for retailers as many European countries have shut nonessential shops temporarily to try to contain the coronavirus pandemic, pushing more shopping online, where Amazon is a major presence. Advertising Skip AdSkip AdSkip Ad Amazon faces a possible fine of up to 10% of its annual worldwide revenue. That could amount to as much as $28 billion, based on its 2019 earnings. The Seattle-based company rejected the accusations.

This forecast is part of the Cisco® Visual Networking Index (VNI), an ongoing initiative to track and forecast the impact of visual networking applications. This document presents the details of the Cisco VNI global IP traffic forecast and the methodology behind it.

Therein lies one of the biggest problems with traditional RSVP. Each time you see text that is not centered properly on the ORP position, your eyes naturally will look for the ORP to process the word and understand its meaning. This requisite eye movement creates a “saccade”, a physical eye movement caused by your eyes taking a split second to find the proper ORP for a word. Every saccade has a penalty in both time and comprehension, especially when you start to speed up reading. Some saccades are considered by your brain to be “normal” during reading, such as when you move your eye from left to right to go from one ORP position to the next ORP position while reading a book. Other saccades are not normal to your brain during reading, such as when you move your eyes right to left to spot an ORP. This eye movement is akin to trying to read a line of text backwards. In normal reading, you normally won’t saccade right-to-left unless you encounter a word that your brain doesn’t already know and you go back for another look; those saccades will increase based on the difficulty of the text being read and the percentage of words within it that you already know. And the math doesn’t look good, either. If you determined the length of all the words in a given paragraph, you would see that, depending on the language you’re reading, there is a low (less than 15%) probability of two adjacent words being the same length and not requiring a saccade when they are shown to you one at a time. This means you move your eyes on a regular basis with traditional RSVP! In fact, you still move them with almost every word. In general, left-to-right saccades contribute to slower reading due to the increased travel time for the eyeballs, while right-to-left saccades are discombobulating for many people, especially at speed. It’s like reading a lot of text that contains words you don’t understand only you DO understand the words! The experience is frustrating to say the least.

Then we put the data up, but the problem with Solr was it didn’t have a user interface, so we used Project Blacklight, which is open source software normally used by librarians. We used it for the journalists. It’s simple because it allows you to do faceted search—so, for example, you can facet by the folder structure of the leak, by years, by type of file. There were more complex things—it supports queries in regular expressions, so the more advanced users were able to search for documents with a certain pattern of numbers that, for example, passports use. You could also preview and download the documents. ICIJ open-sourced the code of our document processing chain, created by our web developer Matthew Caruana Galizia. We also developed a batch-searching feature. So say you were looking for politicians in your country—you just run it through the system, and you upload your list to Blacklight and you would get a CSV back saying yes, there are matches for these names—not only exact matches, but also matches based on proximity. So you would say “I want Mar Cabra proximity 2” and that would give you “Mar Cabra,” “Mar whatever Cabra,” “Cabra, Mar,”—so that was good, because very quickly journalists were able to see… I have this list of politicians and they are in the data!

Last Sunday, April 3, the first stories emerging from the leaked dataset known as the Panama Papers were published by a global partnership of news organizations working in coordination with the International Consortium of Investigative Journalists, or ICIJ. As we begin the second week of reporting on the leak, Iceland’s Prime Minister has been forced to resign, Germany has announced plans to end anonymous corporate ownership, governments around the world launched investigations into wealthy citizens’ participation in tax havens, the Russian government announced that the investigation was an anti-Putin propaganda operation, and the Chinese government banned mentions of the leak in Chinese media. As the ICIJ-led consortium prepares for its second major wave of reporting on the Panama Papers, we spoke with Mar Cabra, editor of ICIJ’s Data & Research unit and lead coordinator of the data analysis and infrastructure work behind the leak. In our conversation, Cabra reveals ICIJ’s years-long effort to build a series of secure communication and analysis platforms in support of genuinely global investigative reporting collaborations.

For communication, we have the Global I-Hub, which is a platform based on open source software called Oxwall. Oxwall is a social network, like Facebook, which has a wall when you log in with the latest in your network—it has forum topics, links, you can share files, and you can chat with people in real time.

About Transparency Toolkit We need information about governments, companies, and other institutions to uncover corruption, human rights abuses, and civil liberties violations. Unfortunately, the information provided by most transparency initiatives today is difficult to understand and incomplete. Transparency Toolkit is an open source web application where journalists, activists, or anyone can chain together tools to rapidly collect, combine, visualize, and analyze documents and data. For example, Transparency Toolkit can be used to get data on all of a legislator’s actions in congress (votes, bills sponsored, etc.), get data on the fundraising parties a legislator attends, combine that data, and show it on a timeline to find correlations between actions in congress and parties attended. It could also be used to extract all locations from a document and plot them on a map where each point is linked to where the location was mentioned in the document.

Analysis Platform On the analysis platform, users can add steps to the analysis process. These steps chain together the tools, so someone could scrape data, upload a document, crossreference that with the scraped data, and then visualize the result all in less than a minute with little technical knowledge. Some of the tools allow users to specify input, but when this is not the case the output of the last step is the input of the next. Tools Existing and planned Transparency Toolkit tools include include scrapers and APIs for accessing data, format converters, extraction tools (for dates, names, locations, numbers), tools for crossreferencing and merging data, visualizations (maps, timelines, network graphs, maps), and pattern and trend detecting tools. These tools are designed to work in many cases rather than a single specific situation. The tools can be linked together on Transparency Toolkit, but they are also available individually. Where possible, we build our tools off of existing open source software. Road Map You can see the plans for future development of Transparency Toolkit here.