The Internet Defense League - Protecting the Free Internet since 2012. 26 :: K.I.S.S. (Keep It Simple Stupid) Het tijdperk van toeters en bellen loopt ten einde. De bloeiperiode van simpleware is aangebroken. ‘Complexiteit is vaak een kwestie van verkeerde keuzes.’ De function creep noemde Maurice Wessling van voormalig privacywaakhond Bits of Freedom het eens. Wessling zag de function creep als een van de grootste gevaren voor de huidige samenleving. Waar systemen zuchten onder de function creep, zijn het producten die struikelen over de feature creep. Maar het is niet alleen marketingopportunisme en ‘het kan dus we doen het’ die gadgets en hun bediening steeds complexer maakt. Master & slavePsycholoog Leonard Verhoef heeft er z’n vak van gemaakt. Verhoef was eerder betrokken bij de ontwikkeling van kaartautomaten van de NS, ontwierp het reistijdenbord voor de vertrekhal van stations en de bedieningspanelen van de HSL-lijn. De oproep tot eenvoud en begrijpelijkheid van psycholoog Verhoef lijkt gehoor te vinden. Meer megapixels! De consument leert niet alleen zelf maar ook van anderen.
byjess.net ekonlab.com Alain Garcia Homepage uvLayer - web d3.js Waskman Diseño bost.ocks.org Please find my recent work on Observable. Past Work April 28, 2017A Better Way to Code December 9, 2016Command-Line Cartography March 9, 2016What Makes Software Good? December 28, 2015Introducing d3-scale December 3, 2015Introducing d3-shape November 23, 2015Let’s Make a (D3) Plugin December 27, 2014Mapping Every Path to the N.F.L. December 20, 2014How Each Team Can Make the N.F.L. November 5, 2014The Most Detailed Maps You’ll See From the Midterm Elections November 3, 2014How To Scroll September 19, 2014‘Stop-and-Frisk’ Is All but Gone From New York July 26, 2014Mapping the Spread of Drought Across the U.S. June 26, 2014Visualizing Algorithms June 15, 2014Three Little Circles May 22, 2014Is It Better to Rent or Buy? May 6, 2014Let’s Make a Bubble Map April 22, 2014Who Will Win The Senate? March 7, 2014Let’s Make a Block Feburary 14, 2014Front Row to Fashion Week February 14, 2014Sochi 2014: Interactive Stories January 11, 2014Taking the Battle to the States November 5, 2013Let’s Make a Bar Chart #Examples
KA_LEN_DIAR | Originální diáře 2014 Cube Time Series Data Collection & Analysis Cube is a system for collecting timestamped events and deriving metrics. By collecting events rather than metrics, Cube lets you compute aggregate statistics post hoc. It also enables richer analysis, such as quantiles and histograms of arbitrary event sets. Collecting Data An event in Cube is simply a JSON object with a type, time, and arbitrary data. Cube’s collector receives events and saves them to MongoDB. Querying Events Cube defines a simple language for querying events. You can intersect filters and customize which event fields are returned. request(browser).gt(duration, 250).lt(duration, 500) Cube supports both HTTP GET and WebSockets for retrieving events. Querying Metrics You can also use Cube to group events by time, map to derived values, and reduce to aggregate metrics. The first few results of which appear as: Or, to count requests to the path "/search", change the expression: sum(request.eq(path, "/search")) sum(request(duration))
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