Silk

Get a free Silk site to share reports and other data, and create interactive visualizations

Silk is a platform where you can make websites with structured data and visualizations.

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Silk
 

Full Description

A Silk site consists of normal web pages that have a special place to enter structured data. This data can be used for interactive graphs, maps and tables. Ideal for transparent sharing of NGO reports or data analysis. Create a site from scratch, or use the spreadsheet importer. The convenience of a database powered site, without technical experience required.

PRICE / FEE

Free


SOCIAL FEEDS:


LATEST BLOG POSTS FROM Silk

  • Major League Free Agents: Pitchers and Pandas
    Posted 20 December 2014 | 4:54 am
    For the past few weeks in the United States, sports fans have watched closely as teams have snapped up many of the various free agents on the market in Major League Baseball (MLB). It was a particularly notable winter signing season largely due to the lack of top quality free agents on the market in various positions. The playoff dash last year also resulted in numerous starting pitchers in the last year of their contracts going to contending teams like the Oakland A’s and the San Francisco Giants. The teams that traded those players got farm prospects in exchange for more horses down the stretch. Many of those hurlers went back on the market immediately to get a better offer. Pitching is always at a premium in MLB. Data from mlb-signings.silk.co The biggest free agent story for Silk, due to our San Francisco employees, was the sad departure of Pablo Sandoval (aka Panda). A stalwart on the Giants during all three World Series title runs (2010, 2012, 2014), Panda elected to go to Boston and play with the Red Sox. Bummer. We’ll be doing some additional salary analysis shortly and we are praying the Giants will pull through with a decent third-baseman. (Update: The Giants just traded for Florida Marlin’s hot-corner vet Casey McGehee, says Yahoo! Sports). Here’s a Silk of 2014 MLB free agent data that lets anyone analyze the MLB free agent signings using data from ESPN. Our MLB Signings Silk allows baseball fans to analyze the economics of the market in various dimensions, and with visualizations. ESPN is one of the best places online to pull in sports stats. You can see how Silk brings that data to life with some cool charts and a nice card gallery. Please play with the data in our Silk, build your own visualizations, and let us know what you think. Contact us @Silkdotco or @SilkJournalism on Twitter.
    > Read more


  • Weekly New Silk Update: STEM Toys at Xmas, Kickstarter and More
    Posted 18 December 2014 | 7:20 pm
    Note: This is a weekly email we send out to journalists with our latest visualizations. We’ll be posting these in our blog, as well, to let people see what we’ve been working on. Enjoy! We’re getting up on the Christmas madness. Adding to our Black Friday Death and Mayhem Analysis from last issue, we’re piling on the holiday data and some more serious Silks, as well. Here’s this week’s crop: Data from interpol-most-wanted.silk.co Interpol’s Most Wanted: Original Data Collection by Silk’s Data Journalists to Map the 95 Most Dangerous Criminals - interpol-most-wanted.silk.co (See the map above for a taste of this Silk). XMAS - Science Toys That Rock: STEM Toy Recommendations, Top-Rated Stem Toys, and the Most Affordable Stem Toys - stem-christmas-toys.silk.co XMAS SILK - Champagnes and Sparklers: Bubbly Data from Veneto to the Napa Valley - champagnes-and-sparkling-wines.silk.co U.S. Police Misconduct Data Visualized and Mapped: Data Collected by the Cato Institute. Sex Offenses Are One-Quarter of the Total, Just 10% Result in a Conviction of Any Sort - police-misconduct-data.silk.co Gender Gap Comparisons Around the World: The Data from WEF on How Women Stack Up In Country to Country Comparisons. (Hint: The U.S. is not even in the Top 10) - global-gender-gap-index.silk.co NBA Player Salaries Analysis: Is Pay Correlated to Weight, Age, or Height? What Colleges Have the Highest Paid Alums in the NBA? And we know why Kobe is paid so much but Joe Johnson? - nba-player-salaries.silk.co More Silks coming next week. Until then, Happy Silking and send us any questions (we’re on Twitter @Silkdotco or @SilkJournalism Pro Tip: Want to place the visualizations you see above in a story? Any visualization you see or create can be embedded on your site using the embed code found in the “Share and Embed” tab. Embeds are also mobile-friendly in “responsive” mode. And they look great!
    > Read more


  • Pin a widget on all pages in a collection
    Posted 17 December 2014 | 3:10 pm
    A lot of Silk creators have asked us for a way to add text and widgets to all pages in a collection. We’re pleased to say that this is now possible via pinning. Any widget or text block in a Silk can be pinned to a page to make it reappear on all other pages in that collection. To do this, edit a page and simply click the pin icon next to a widget. Pinning can be helpful for adding copyright notices, navigation blocks, logos, sources, and other repeating blocks of text or images to your pages. We used it to add a link to NASA and Wikipedia on all planet pages on solarsystem.silk.co, for example. … but there’s more: pinned widgets can make use of the value of a tag, dynamically altering a widget’s behavior in relationship to that particular page. That makes these dynamic pins very powerful. For example, we have used dynamic pins to show a different video for each page of a collection, to show a map that plots a specific team member’s location, and much more. In the video below, I pin a block of text to my page on the Cocoon Demo Silk. I also embed and pin a Twitter timeline on the page, using ~Twitter Username as a value to make it dynamic. When I reload another page (oh hi Adam!), you can see the pinned widgets magically appear there as well. For more information check out our help article on pinning. Happy Silking!
    > Read more


  • The Great California Storm: Tweet Analysis and Visualization with CrowdFlower
    Posted 16 December 2014 | 4:20 am
    It was a rainy Friday afternoon when the email came from our friends at CrowdFlower. “Hey, we collected and analyzed 10,000 Tweets about the big story that just hit. Can you give us some visualizations?” We said “No problem!” and a few minutes later our California Storm Tweets Analysis Silk was born. As Silks go, it’s a simple one - only a few visualizations, not a lot of data on the pages. But what CrowdFlower liked was our ability to turn around a live interactive visualization in minutes. So we helped them put together a blog post and visualize the data. Data from california-storm-tweets-2014.silk.co Here’s a bit of context. On December 10, a huge storm hit just North of the Bay Area. This “Pineapple Express” weather event flooded homes and businesses, closed schools, plunged over 100,000 Bay Area residences into darkness, raised waves of nearly 30 feet, and delivered pounding rainfall of over 6 inches in 24 hours for some locations. CrowdFlower took the opportunity to harvest sentiment from Twitter and find out the most prevalent sentiments expressed about the #BayAreaStorm. To do this categorization CrowdFlower used it’s distributed workforce of remote workers, assigning them small online tasks to analyze the sentiment of tweets the CrowdFlower data science team had collected. The crowd was asked to categorize the sentiment in the tweet (e.g. power outage, humor, etc) as well as to capture the number of retweets. (Note: This is a great use case for CrowdFlower: a number of large advertising agencies and PR agencies use CrowdFlower specifically for this purpose.) The Silk Data Journalism team took the data, scrubbed it for dupes, and reduced it down to 9300 relevant tweets and then published the data on Silk for quick visual analysis and to build visualizations. The findings? In typical laid back NorCal fashion, Bay Area residents were more amused by the storm, than they were concerned about road closures or power outages. (See the above donut chart for the precise breakdown). Data from california-storm-tweets-2014.silk.co The most popular tweet came from the social media team at NetFlix: “@netflix: Netflix Recommends: Working From Home tomorrow. #NetflixWeather #BayAreaStorm” got a whopping 514 retweets. Very clever. Check out the visualizations and sift through the text of the tweets by hovering over the lines on the bar chart to get a taste of what tweets garnered the most interest.
    > Read more



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