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Predictions for the 2013-14 women's college basketball season
Before the season tips off Friday, espnW.com offers its predictions for conference champions, Final Four teams and who will be crowned national champion in Nashville, Tenn.Story | Conversation | November 08, 2013
2013 women's NCAA tournament -- UConn will have a height advantag...Kate Fagan
UConn will face Vanderbilt in the first game of eight Monday. It will be Stefanie Dolson's height against Tiffany Clarke's quickness.Story | Conversation | March 25, 2013
Women's Basketball: Sunday's Play 4Kay coverage maps
A look at the protected markets and ESPN3 links for Sunday's Play 4Kay on ESPN2, ESPNU, ESPN3 and WatchESPN.Story | Conversation | February 08, 2013
AP's Top 25 -- Baylor Lady Bears maintain hold as nation's No. 1 ...
Baylor remains No. 1 in The Associated Press women's basketball poll for a fifth straight week after cruising to two more Big 12 wins.Story | Conversation | February 04, 2013
Baylor Lady Bears stay at No. 1 in AP's Top 25 poll for fourth st...
Baylor remains No. 1 in The Associated Press women's basketball poll for a fourth straight week after two more Big 12 wins.Story | Conversation | January 28, 2013
Who are the toughest teams to figure out in Women's Bracketology?...Charlie Creme
Interpreting the resumes of Delaware, Green Bay, North Carolina, Texas, Kansas State and Oklahoma is the toughest part to Women's Bracketology this season.Story | Conversation | February 27, 2012
Kate Fagan -- Busting NCAA bracket selection mythsKate Fagan
The NCAA puts together a committee to pick its 64-team women's bracket. Kate Fagan became part of a mock committee and busted some bracket myths.Story | Conversation | February 17, 2012
Rebecca Lobo's Five QuestionsRebecca Lobo
Rebecca Lobo gets players and coaches to say and do the darndest things in her Five Questions feature.Story | Conversation | February 13, 2012
Women's NCAA tournament: Point guards stand tall for Sweet 16 tea...Graham Hays
When the Sweet 16 gets under way on Saturday afternoon, some of the biggest stars on the court will be the smallest players on the court, the point guards.Story | Conversation | March 24, 2011
Women's NCAA tournament: Sweet 16 breakdownGraham Hays and Mechelle Voepel
Mechelle Voepel and Graham Hays go region-by-region to preview this weekend's Sweet 16 contests, which begin Saturday at noon ET on ESPN.Story | Conversation | March 23, 2011
Women's college basketball: The week aheadGraham Hays
Monday Oral Roberts at Oakland: With a 76-74 win against IPFW on Saturday, Oral Roberts completed a season sweep of the third-place Mastodons and improved to 10-0 in the Summit League. That leaves Oakland as the biggest obstacle in the way of a c...Blog | Conversation | January 30, 2011
Games We're Watching: Hump day hoopsSarah Spain
Women's hoops fans rejoice! Three of the top five teams in the country are in action tonight, including the No. 1 Baylor Lady Bears and the No. 2 UConn Huskies. A big night of basketball will get you through hump day.Blog | Conversation | January 12, 2011
ESPN.com's Preseason All-Americans
UConn put two players on our preseason All-America teams. But Stanford cashed in with two Cardinal on the first team.Story | Conversation | November 11, 2010
Maya Moore of Connecticut Huskies a two-time unanimous preseason ...
Connecticut's Maya Moore is the second player to be a two-time unanimous choice on The Associated Press' women's basketball preseason All-America team.Story | Conversation | November 02, 2010
Charlie Creme's women's Bracketology video update
Florida State has moved past West Virginia and Xavier as the final No. 2 seed in Charlie Creme's women's Bracketology video update.Story | Conversation | March 04, 2010
Charlie Creme's women's Bracketology video update
All the recent upsets helped pave the way for Texas A&M to move up one spot to a No. 2 seed in Charlie Creme's women's Bracketology video update.Story | Conversation | February 05, 2010


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59 results for "one time"
NASCAR - Duels all about the desperate fewTerry Blount
There are 39 drivers for whom Thursday's Daytona qualifying Duel races hold no real drama. They are in Sunday's Daytona 500. For the 10 that remain, it's no holds barred.Story | Conversation | February 21, 2012
Time to scrap the abused past champion's provisional in NASCARTerry Blount
The past champion's provisional might have been a good idea at one time. Now it's just an abused rule to help struggling teams circumvent qualifying, and it's a loophole that should be closed, writes Terry Blount.Story | Conversation | May 20, 2008
NHRA - John and Courtney are Forces to be reckoned withTerry Blount
Courtney Force has her sights set on an NHRA Funny Car championship. Here's the intrigue: She'll likely have to go through her father, 15-time champ John Force, to get one.Story | Conversation | June 26, 2013
NASCAR - Jeff Gordon the fastest guy at DaytonaTerry Blount
Jeff Gordon is a three-time Daytona 500 champ and future Hall of Famer. How does he feel about sharing the front row with pole winner Danica Patrick? One word: Proud.Story | Conversation | February 17, 2013
NASCAR - new car will be star of Sprint UnlimitedTerry Blount
One lucky driver will win the Sprint Unlimited on Saturday night, but none of the 19 test pilots on the track will be the real star for this one. It's time to see how the new "Gen 6" car really races.Story | Conversation | February 15, 2013
NASCAR - For Danica Patrick, it's one goal at a timeTerry Blount
Danica Patrick isn't looking to set the NASCAR world on fire in her rookie season at the Cup level. "Small goals" is the buzz phrase coming out of the No. 10 Chevy camp.Story | Conversation | January 21, 2013
NASCAR - Clint Bowyer should help Texas be a thrill showTerry Blount
Sunday's Texas race has to be better than the one in April, which was one of the worst of the season. Why? Because drivers such as Clint Bowyer have nothing to lose.Story | Conversation | November 02, 2012
NASCAR - Monday Rundown - Remaining Chase tracks favor Jimmie Joh...Terry Blount
The good news: Brad Keselowski minimized the damage at one of Jimmie Johnson's best tracks, Martinsville. The bad news: The final three Chase tracks favor Five-Time in a big way.Story | Conversation | October 28, 2012
IndyCar - High anxiety at Texas Motor SpeedwayTerry Blount
The IndyCar Series hasn't raced on a high-banked oval since Dan Wheldon lost his life in a crash last fall at Vegas. No wonder emotions are sky-high at Texas Motor Speedway.Story | Conversation | June 07, 2012
NHRA - Robert Hight targets fifth straight Funny Car winTerry Blount
Robert Hight will join some elite company -- Don "The Snake" Prudhomme, John Force and Cruz Pedregon -- if he wins a fifth straight Funny Car event Sunday at Royal Purple Raceway.Story | Conversation | April 26, 2012
NASCAR - Kyle Busch looking for Texas redemptionTerry Blount
Kyle Busch reached a turning point in his Sprint Cup career after getting suspended last season at Texas Motor Speedway. Is he finally on the right track heading into Saturday's race?Story | Conversation | April 13, 2012
NHRA - Tony Schumacher wants canopies in Top FuelTerry Blount
Seven-time NHRA Top Fuel champ Tony Schumacher is on a mission: He is championing a move for enclosed canopies on dragsters -- a safety advancement that just could revolutionize the sport.Story | Conversation | February 07, 2012
NASCAR - Danica Patrick steals media tour spotlightTerry Blount
Day 1 of the NASCAR media tour offered few surprises. But it did confirm one thing: Danica Patrick's star is soaring higher than ever.Story | Conversation | January 23, 2012
Shawn Langdon will replace Larry Dixon at Al-Anabi RacingTerry Blount
Shawn Langdon will replace three-time NHRA champion Larry Dixon in a Top Fuel dragster for Al-Anabi Racing, team officials announced Tuesday.Story | Conversation | December 13, 2011
NASCAR - Auto racing's 10 burning questionsTerry Blount
From Tony Stewart's chances at a repeat to Danica Patrick's chances in a Cup car, Terry Blount answers the 10 burning questions in auto racing for 2012.Story | Conversation | December 12, 2011
AUTO RACING - Best and worst of 2011Terry Blount
From Tony Stewart's championship run in Sprint Cup to Dan Wheldon's tragic death in IndyCar, Terry Blount recaps the year's best and worst moments in motorsports.Story | Conversation | November 22, 2011

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it has been almost two years now and they are still saying they are waiting on blood work and his public defender still hasnt meet with him even though he has tryed to make appopinment after appointment. how long does it take for a blood test to come back and is it possible they have lost it and that it can get thrown out.
The past two years was the time during which the defense lawyer in a DUI case should be gathering facts and preparing the case. All lab work should have long been processed and available to everyone involved. Somethings, not right?
the statute of limitations in Georgia is 2 years from the date of the alleged act. Please don't hold it against the public defender he has tons of cases.
blood test results in Georgia can take up to 6 months to complete. Your husband can request an independent test if you want to know the reults now.
without the blood test your husband's odds at an acquittal significantly increase
There may be speedy trial statutes that are implicated along with statutes of limitations arguments to be made.
In most cases I have found that the best strategy is to let sleeping cases lie; if nothing is said, and the state forgets to prosecute in a timely manner, then the case would have to be dismissed with prejudice, regardless of the strength of evidence.
Be patient.
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Across the United States and around the world, law is a major instrument of public policy. Now, through Stanford's new interdisciplinary program in public policy, law students can gain the skills and knowledge to develop, advocate for, and implement policy that shapes the lives of people everywhere.
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- The Greening Of Barack Obama
November 18, 2014 Politico
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- Stanford Study: More Guns Means More Crime
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- Picking 'Three-Strikers' To Free Poses Complex Challenge
November 16, 2014 Los Angeles Times
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- Does Advice From Proxy Advisory Firms Really Help Shareholders?
November 15, 2014 Financial Post
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- More Guns, More Crime: New Research Debunks A Central Thesis Of The Gun Rights Movement
November 14, 2014 The Washington Post
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Corgi Loves Cabbage
Don't touch his lettuce, assholes.
Don't touch his lettuce, assholes.
Matt Stopera a year ago 44 responses
It looks good enough to eat. Thanks, Japan!
bobbyjrisms 2 years ago 59 responses
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StartUpHire is the place to find Field Applications Scientist jobs. Review the list of Field Applications Scientist career opportunities to the left. These Field Applications Scientist jobs represent some of the most rewarding careers available.
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Labcyte seeks an energetic scientist with automated liquid handling and automation experience and expertise in genomics, proteomics and/or drug discovery applications. This scientist will provide technical product demonstrations and customer support to drive sales and adoption10/11/2014 Sunnyvale, CA Save This Job
Labcyte seeks a creative and energetic Applications Scientist to play a key role in the success of our business through the development and implementation of laboratory automation solutions across a variety of workflows and scientific disciplines. This scientist will utilize10/11/2014 Sunnyvale, CA Save This Job
More information about this job: Fluidigm is seeking an established FAS/District Manager to support the Company?s primary product lines: Biomark, C1, Access Array, and EP1. The role is a blended position including West District Management support of field-based FAS within as10/28/2014 Houston, TX Save This Job
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Duties & Responsibilites - Develop advanced computer vision algorithms for intelligent video surveillance systems. - Design and develop custom video surveillance solutions. - Analyze and refine computer vision algorithms to support product launch. - Write10/15/2014 Reston, VA Save This Job
DEPARTMENT: Laboratory - 100 JOB CODE: DATE: 09/16/2014 REPORTS TO: Laboratory Manager GRADE: FLSA STATUS: Under general supervision of the Laboratory Manager, the Clinical Lab Scientist III performs all aspects of genetic testing such as array CGH/SNP, DNA extraction, DNA10/27/2014 Irvine, CA Save This Job
Job ID818695 LocationSan Francisco, CA 94102 Other LocationSan Ramon, Oakland, Walnut Creek, Pleasanton, Hayward, Fremont, San Jose, Silicon Valley Description Why Predixion? Predixion Software is a fast-growing, award-winning software company that is creating the future of10/6/2014 San Francisco, CA Save This Job
Requisition Number: SS3001 Job Purpose The purpose of this position is to drive the scientific management, planning, and execution of clinical research projects and to support the development and incorporation of new clinical biomarkers. Duties and Responsibilities Manages10/20/2014 Houston Save This Job
As a Data Scientist at Ayasdi, you will be solving some of the most complex problems with the most revolutionary analytical platform. Our applications, with your help, will fundamentally alter the way data is analyzed. Your technical and inquisitive aptitude will lead you to10/4/2014 Menlo Park, CA Save This Job
Working as part of a multidisciplinary drug-discovery team, the scientist is responsible for laboratory biological evaluation of compounds for animal health applications. Responsibilities include planning, development, execution, and coordination of in-house activities,11/13/2014 Research Triangle Park, NC Save This Job
We are seeking a Scientist to diversify our research and development efforts aimed at synthesis, characterization and scale-up of functional polymers and block copolymers for drug delivery applications. We are seeking candidates with a proven record of innovation and interested10/12/2014 Cambridge, MA Save This Job
Conviva continuously collects huge amount of online video data in real time from many different premium publishers, content providers and service providers. We have: ? 50 billion streams a year ? 2 Trillion events/year ? 1 billion devices ? 180+ countries More importantly we11/12/2014 San Mateo, CA Save This Job
The Informatics Team is the clinical development arm of Explorys. The Data Curation Team in Informatics is responsible for providing meaning to the data in our system and developing methods to leverage that data in our applications by standardizing and cleaning disparate data. We9/9/2014 Cleveland, OH Save This Job
Data Science North East, United States The role: Data Scientist for Ayasdi Government Services Location: Washington, DC Metro Area As a Data Scientist at Ayasdi, you will be solving some of the most complex problems with the most revolutionary analytical platform. Our10/4/2014 Washington, DC Save This Job
Does making a new discovery from analyzing large datasets sound like fun? Would you like to use your math and computing skills to help improve patient outcomes? Do you want to help create new ways to deliver actionable information for healthcare providers to use to improve the9/9/2014 Cleveland, OH Save This Job
SUMMARY/PURPOSE Explorys is searching for an innovative Data Scientist to help the Content team in Informatics develop creative solutions to the challenging problems and make a direct impact on the transformation of healthcare. As a Data Scientist on the Content Development8/10/2014 Cleveland, OH Save This Job
Market6 is looking for an experienced data scientist with big data skill and an analytics determination. Someone who is driven, self-directed, entreprenurial and focused on solving complex business problems though data, forecasting and predictive analytics. The candidate should10/26/2014 Deerfield, IL Save This Job
As a Senior Research Scientist within Sensory's Vision Technologies team, you will bring your intelligence and drive to our patented and award-winning speech and vision technologies. Sensory (www.sensoryinc.com) is a leader in providing speech recognition technologies for10/20/2014 Boulder, CO Save This Job
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|This tasty vegan slow cooker stew has ginger and coriander for extra flavor. (Photo from Cookin' Canuck.)
Submit Your Recipes: --If you're a food blogger with a good from-scratch slow cooker recipe you'd like to have featured on this site, here's how to submit it.
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The award was presented by the Menomonee Falls Chamber of Commerce. Read More »
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Five label printers are among 33 graphic arts companies that have captured annual human resources awards from the Printing Industries of America. Read More »
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The history of Zen Buddhism presents itself as a family saga. Each priest of the Sôtô school today belongs to an uninterrupted line which traces itself either to Gasan Jôseki Zenji (1276-1366) or to Meihô Sotetsu Zenji (1277-1350), two disciples of Keizan Zenji, all other Japanese lines having since become extinct. One is integrated into a lineage at the time of the ceremony of Transmission of the Dharma, by which the Master makes the Disciple his successor. Presented here is the chain of teachers that connects Eihei Dôgen Zenji to Gudo Nishijima Roshi, and in the 41st generation from Dogen, Jundo James Cohen of the Treeleaf Zendo. As well, its links are said to reach back in time through China and India, on to the historical Buddha, Śhākyamuni. The line is also closely associated, ever since the middle of the 15th century, with the temple Tôkei' in, located near to the Japanese town of Shizuoka. It is a long, yet continuing history. In an important sense, it is not to be limited to any place or nation, nor is it merely a timeline which flows from past to present: In Dogens teachings, past is present is future, while the future flows into the past as the past becomes the future. In this way, each teacher stands for all others, and all are with us now.
References: For a history of the development of Zen in Japan, please refer to William Bodiford, Sôtô Zen in Medieval Japan... read more
If however there is the tiniest gap, heaven and earth are far apart. If the least tendency arises to go against or conform, the mind is lost in confusion.
Cependant, sil existe le plus petit écart, ciel et terre se séparent. Que sélèvent la plus légère préférence ou le moindre rejet, lesprit se perd dans la confusion.


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This new book by Daniel J. Levitin explains how our brains have evolved to process information and he applies this knowledge to several of the most important realms of life: our homes, our social connections, our time, our businesses, our decisions, and the education of our children. Knowing how our minds manage attention and memory, especially their limitations and the ways that we can offload and organize information to work around these limitations, is essential for anyone who works with data.
This excerpt from the introduction will provides a sense of Levitin's intention:
We humans have a long history of pursuing neural enhancement—ways to improve the brains that evolution gave us. We train them to become more dependable and efficient allies in helping us to achieve our goals…Through the sheer force of human ingenuity, we have devised system to free our brains of clutter, to help us keep track of details that we can't trust ourselves to remember. All of these innovations are designed either to improve the brain we have, or to off-load some of its functions to external sources…It's helpful to understand that our modes of thinking and decision-making evolved over the tens of thousands of years that humans lived as hunter-gatherers. Our genes haven't fully caught up with the demands of modern civilization, but fortunately human knowledge has—we now better understand how to overcome evolutionary limitations. This is the story of how humans have coped with information and organization from the beginning of civilization. It's also the story of how the most successful members of society…have learned to maximize their creativity, and efficiency, by organizing their lives so that they spend less time on the mundane, and more time on the inspiring, comforting, and rewarding things in life.
Levitin describes the nature of our so-called information age, including the many ways that work done by information specialists in the past has been transferred to us (for example, making our own travel arrangements rather than relying on the services of a travel agent), resulting in overwhelming cognitive demands. He shows how the coping strategy of multi-tasking is in fact an inefficient form of serial tasking—attentional switching—that provides an illusory sense of productivity. Many of life's challenges require focus—extended periods of uninterrupted attention. We also need the replenishment of neural energy that the mind-wandering mode provides, where associations and insights can form while the mind soars freely.
How we sort through incoming data in rapid triage to separate urgent matters from others, how we categorize and store it for later retrieval, how we protect ourselves from the din of distracting noise, and how we assess facts when making decisions, are all skills that we can learn. Levitin's advice is practical, lucid, and firmly rooted in an understanding of the brain.
When organizations are chasing the latest so-called Big Data technologies, it's important to recognize that more and faster isn't necessarily better, and in fact, is often worse, because of the ways that our brains are designed. If you're involved in business intelligence, analytics, data visualization, data science, data storytelling, decision support, or whatever you choose the call the work of data sensemaking and communication, books like The Organized Mind are more useful to your success than a hundred books about specific software tools. Do yourself a favor and read this book.
Take care,
Stacey and I became fast friends several years ago during my first visit to Australia. Stacey is based in Brisbane. I turn to Stacey when I have questions about performance measurement and she turns to me when she has questions about data visualization. For years I've been encouraging Stacey to put her ideas in a book and I'm thrilled to announce that, after a long labor of love, she has done so. Within a couple of weeks her book Practical Performance Measurement will be available through booksellers such as Amazon.
I haven't received my copy yet, so I can't comment on the content, but I'm confident that it will be worthwhile. One way to determine this for yourself is to attend a free webinar that Stacey will be conducting to introduce some of the book's content. If you struggle with performance measurement, you should take advantage of this opportunity.
Take care,
Nick approached me a few months ago with a passion for data visualization, combined with a keen intellect, a fine pedigree of skills and experiences in decision support, and an insatiable curiosity. He's also an accomplished business leader, having founded or co-founded three companies.
Even though I had long ago decided that I would never hire someone to teach my courses, Nick eventually opened my mind to the possibility. Nick's addition to the team will solve a particular problem that many organizations have faced during the last few years since I began teaching public workshops: he will accept invitations to teach my courses privately. In recent years I've turned down many requests for private courses, preferring to use my limited time for teaching in public workshops where I can reach the broadest audience possible in the most efficient way. Nick is now available to teach Show Me the Numbers privately, and will soon offer my Information Dashboard Design and Now You See It courses as well. If your organization has at least 30 people that you'd like to have trained, email us at firstname.lastname@example.com or call us at (510) 558-7400 to discuss the possibility.
As some of you have already noticed, we've opened registration for two new advanced courses on our Workshops page. On January 13 and 14, 2015 I'll be teaching the two-day course Signal, which covers the content of my new book, in Berkeley, California. I'll also be teaching it in Utrecht in the Netherlands on May 18 and 19, 2015 and in Sydney, Australia on November 10 and 12, 2015. Here's an introduction to the content of Signal.
Many people assume that, if they know how to use data analysis software, this means that they are skilled data analysts. Knowledge of data analysis tools and possession of data analysis skills, however, are not the same. Even expert users of analytical tools frequently have little or no knowledge of fundamental yet powerful data analysis techniques.
Do you have the nagging sense that signals in your data—the things that matter most—might be slipping by unnoticed? Do you ever wonder if you're wasting time tracking the wrong metrics or tracking the right metrics in the wrong ways? The data analysis that takes place in most organizations produces only a small fraction of its potential for useful insights. This is because most of the people who do this work have never been trained in data exploration and analysis beyond the basics, if at all. When presented with a new data set, do you know how to get the lay of the land—the context that's necessary for analytical insights? Do you know how to separate signals from the noise?
At any given point in time, only a small portion of any organization's data is useful for decision making. The rest is noise. Increases in data volume, velocity, and variety are actually more a problem than a benefit unless you know how to find and decipher signals buried in that growing haystack.
In this advanced data exploration and analysis course, I'll take participants beyond the basic skills that are taught in my books Show Me the Numbers and Now You See It to the next level of statistical and data visualization skills that are required for signal detection. Only the signals matter.
The other new advanced course is Advanced Dashboard Design. I'll be teaching this three-day course for the first time on January 27-29, 2015 in Berkeley, California, and later in London on March 4-6, 2015 (now open for registration) and in Sydney, Australia on November 10-12, 2015. This course is limited to 20 participants. Here's a description:
Dashboards have now been a popular form of information display for over a decade, but relatively few of them live up to their potential. In my book Information Dashboard Design: Displaying Data for At-a-Glance Monitoring, Second Edition (2013), I introduce best practices for dashboard design that can be learned with relative ease. Competence, however, take more than reading a book; it takes experience that benefits from expert oversight and advice. This three-day course is specifically designed for dashboard designers who have already learned the basics and now want to extend and deepen their skills.
A series of short lectures and discussions cover advanced dashboard design topics, but most of the course involves hands-on dashboard design. Working in small groups of four, participants work collaboratively to fully design (but not develop) real dashboards of their choosing. Each participant brings a single set of dashboard requirements to the course and, with the assistance of fellow participants and myself, proceeds step-by-step through the design process from initial sketching to polished wireframes, which they present to the class on the last day for a final critique. Participants leave the course with a well-designed, real-world dashboard in hand and the skills to produce others, again and again.
This course is limited to 20 participants and is only for those who are already skilled dashboard designers.
If you have any questions about private training by Nick Desbarats or about either of the two advanced courses, you're welcome to post them here in this blog.
Take care,
Long before the term came into common usage around the year 2010, it began to pop up here and there in the late 1990s. It first appeared in the context of data visualization in 1997 at the IEEE 8th Conference on Visualization in a paper by Michael Cox and David Ellsworth titled "Application-controlled demand paging for out-of-core visualization." The article begins as follows:
Visualization provides an interesting challenge for computer systems: data sets are generally quite large, taxing the capacities of main memory, local disk, and even remote disk. We call this the problem of big data. When data sets do not fit in main memory (in core), or when they do not fit even on local disk, the most common solution is to acquire more resources.
Two years later at the 1999 IEEE Conference on Visualization a panel convened titled "Automation or interaction: what's best for big data?"
In February of 2001, Doug Laney, at the time an analyst with the Meta Group, now with Gartner, published a research note titled "3D Data Management: Controlling Data Volume, Velocity, and Variety." The term Big Data did not appear in the note, but a decade later, the "3Vs" of volume, velocity, and variety became the most common attributes that are used to define Big Data.
The first time that I ran across the term personally was in a 2005 email from the software company Insightful, the maker of S+, a derivative of the statistical analysis language R, in the title of a course "Working with Big Data."
By 2008 the term had become used enough in scientific circles to warrant a special issue of Nature magazine. It still didn't begin to be used more broadly until February, 2010 when Kenneth Cukier wrote a special report for The Economist titled "Data, Data Everywhere" in which he said:
…the world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly… The effect is being felt everywhere, from business to science, from governments to the arts. Scientists and computer engineers have coined a new term for the phenomenon: "big data."
It was around this time that the term was snatched from the world of academia to become the most successful information technology marketing campaign of the current decade. (I found most of the historical references to the term Big Data in the Forbes June 6, 2012 blog post by Gil Press titled "A Very Short History of Big Data.")
Because Big Data has no commonly accepted definition, discussions about it are rarely meaningful or useful. Not once have I encountered a definition of Big Data that actually identifies anything that is new about data or its use. Doug Laney's 3Vs, which describe exponential increases in data volume, velocity, and variety, have been happening since the advent of the computer many years ago. You might think that technological milestones such as the advent of the personal computer, Internet, or social networking have created exponential increases in data, but they have merely sustained exponential increases that were already happening. Had it not been for these technological advances, increases in data would have ceased to be exponential. Recently, definitions have emphasized the notion that Big Data is data that cannot be processed by conventional technologies. What constitutes conventional vs. unconventional technologies? My most recent encounter with this was the claim that Big Data is that which cannot be processed by a desktop computer. Based on this rather silly definition, Big Data has always existed, because personal computers have never been capable of processing many of the datasets that organizations collect.
So, if Big Data hasn't been defined in an agreed-upon manner and if none of the existing definitions identify anything about data or its use that is actually new, does the term really describe anything? I've thought about this a great deal and I've concluded that it describes one thing only that has actually occurred in recent years:
Big Data is a rapid increase in public awareness that data is a valuable resource for discovering useful and sometimes potentially harmful knowledge.
Even if Big Data is this and nothing more, you might think that I'd be grateful for it. I make my living helping people understand and communicate information derived from data, so Big Data has produced a greater appreciation for my work. Here's the rub: Big Data, as a term with no clear definition, which serves as a marketing campaign for technology vendors, encourages people to put their faith in technologies without first developing the skills that are needed to use those technologies. As a result, organizations waste their money and time chasing the latest so-called Big Data technologies—some useful, some not—to no effect because technologies can only augment the analytical abilities of humans; they cannot make up for our lack of skills or entirely replace our skills. Data is indeed a valuable resource, but only if we develop the skills to make sense of it and find within the vast and exponentially growing noise those relatively few signals that actually matter. Big Data doesn't do this, people do—people who have taken the time to learn.
Take care,
Don't confuse this with another fine book titled Made to Stick (2007) by brothers Chip and Dan Heath, which teaches how to get messages across in clear and compelling ways. Make It Stick presents in accessible terms the latest research findings regarding learning, both for people who want optimize their own learning efforts and for teachers who want to create successful learning experiences for their students.
By learning, the authors mean "acquiring knowledge and skills and having them readily available from memory so you can make sense of future problems and opportunities." They're not talking about simple recall. Learning involves memory, but extends beyond mere recall into the realm of application. Real learning is "effortful." For example, "When you're asked to struggle with solving a problem before being shown how to solve it, the subsequent solution is better learned and more durably remembered." Effort alone isn't enough, however. It has to be the right effort.
To apply knowledge and skills to new problems and opportunities when they arise, we must possess more than procedural familiarity; we must have a conceptual understanding that is generalizable. "People who learn to extract the key ideas from new material and organize them into a mental model and connect that model to prior knowledge show an advantage in learning complex mastery." We can all become better learners by developing better learning practices. One such practice is frequent testing. Whether you're studying on your own or in a structured learning setting, frequently testing your understanding and ability to apply what you're learning strengthens it and provides the feedback that you need to focus your efforts where they're most needed.
Many popular beliefs about learning, such as the benefits of cramming (a.k.a., massed practice) and rereading material over and over, are flawed. The ability to perform well on a multiple-choice test soon after cramming or rereading material is short-lived. Spaced practice, interleaved with other material, results in better learning than non-stop focus on a single topic or skill. Some of the best learning practices are counter-intuitive and don't necessarily feel like progress during the learning process itself, even though they dramatically outperform other practices that feel more productive. Some beliefs about learning that have garnered attention in recent years are downright wrong. One that I've encountered frequently in my own work is the notion that people learn best when they engage in the learning style that they prefer.
The popular notion that you learn better when you receive instruction in a form consistent with your preferred learning style, for example as an auditory or visual learner, is not supported by the empirical research. People do have multiple forms of intelligence to bring to bear on learning, and you learn better when you "go wide," drawing on all of your aptitudes and resourcefulness, than when you limit instruction or experience to the style you find most amenable.
Our brains are designed to think in several modes (e.g., verbally, numerically, and visually), which we should shift between fluidly, as needed, depending on the nature of the material and the perspective from which we wish to consider it.
Another popular but misguided notion is called student-directed learning. "This theory holds that students know best what they need to study to master a subject, and what pace and methods work best for them." While it's true that students should take more responsibility for their own learning, "most students will learn academics better under an instructor who knows where improvement is needed and structures the practice required to achieve it."
Fundamentally, the purpose for which we pursue the acquisition of information and skills has a significant effect on learning. There is a huge difference between focusing on performance versus focusing on learning.
In the first case, you're working to validate your ability. In the second, you're working to acquire new knowledge and skills. People with performance goals unconsciously limit their potential. If your focus is on validating or showing off your ability, you pick challenges you are confident you can meet…But if your goal is to increase your ability, you pick ever-increasing challenges, and you interpret setbacks as useful information that helps you sharpen your focus, get more creative, and work harder.
I could go on, but I won't, because I merely want to whet your appetite for more. This is an excellent book and one that is desperately needed. As the authors say, "No matter what you may set your sights on doing or becoming, if you want to be a contender, it's mastering the ability to learn that will get you in the game and keep you there."
Although I was already familiar with much of the material in this book, because of extensive reading about learning theory, 40 years of reflective teaching experience, and a lifelong love of learning, a great deal was new to me. Enough, in fact, that I will soon be redesigning my table and graph design course, Show Me the Numbers, to last two days rather than one so I can add frequent tests, additional discussions, and many more group exercises to guarantee that my students leave with a stronger foundation to build on. I've been teaching the concepts well, but not fully providing the learning experience that will make those concepts stick.
Take care,
Wanders work exhibits conscious, unapologetic self-expression—"Look at me!" One of the quotes writ large on the museum's wall expressed Wanders' belief that a designer's work should exhibit his personal signature. I disagree, as does Teague.
When speaking of the rightness of a design, Teague declares that all aspects "should derive their sanction from something more necessary than a designer's fancy." Design strives to solve a problem, to serve human needs, not to express the personality of the designer.
Wanders' notion of design is quite different.
It is our responsibility to be magicians, to be jesters, to be alchemists, to create hope where there is only illusion, to create reality where there are only dreams.
He shuns the formative principle of industrial design that "form follows function." His aspirations are those of an artist, not a designer. This perspective is reflected in his work.
No, this is not a toy, it is Wanders' full size, running "holiday car," its exterior covered with colored stones.
The designer's approach should be one of interaction, not imposition: interaction between human needs, the tools, techniques, and materials of construction, the environment, and the designer's skill and imagination. As designers, we use the best materials, tools, and techniques available to solve real problems in the context of our environment as well as possible. We are directed by human needs and the problems that must be solved to fulfill them, not a desire for self-expression. We are restricted objectively by our tools and materials and their impact on the world, not subjectively by the expanse of our egos. The product of our efforts should show no visible sign of ourselves, though it is born of our imagination. Perhaps this is a fundamental difference between art and design: the former an act of self-expression, often beautiful; the latter an act of integration and resolution, no less beautiful, but assessed differently. As designers, we speak in silence, but our voices, though anonymous whispers, are no less heard. Silently, we change the world.
Take care,
The three Vs are a perfect fit for the Big O, but not for data. More data coming at us faster from an ever-growing variety of sources offers few advantages and often distracts from the ultimate goal. Leanne doesn't understand why data geeks (her words, not mine) are spending so much time arguing about terminology and technology instead of focusing on content—what data has to say—and putting that content to good use. I couldn't agree more.
Take care,
Why was a contributor to Forbe's promoting the walking dead? Not because Kerschberg has expertly reviewed the product and found it worthy. Kerschberg is an attorney, with no expertise whatsoever in data visualization. It's clear from some of Kerschberg's statements that he was merely parroting promotional material that was provided by VisualCue. For instance, Kerschberg referred to "bar charts,…treemaps, Gannt charts, and scatter plots" as "subpar visualizations… that fail to serve their main purpose of communicating information." This language is reminiscent of statements previously made by the founder of FYI Visual. What is VisualCue's answer to these subpar visualizations? "Interactive Visualization," which Kerschberg says is a term that was coined by Gartner. First of all, Gartner did not coin this term. It has been in use since long before data visualization was on Gartner's radar. Anyone familiar with the field knows that interactive visualization has been around since the early days of computer graphics. Regarding interactive visualization, Kerschberg makes the following claim, no doubt lifted directly from VisualCue's absurd promotional content: "Interactive Visualization implies the use of heat maps, geographic maps, link charts, and a broad spectrum of special purpose visualizations that surround processes that are inextricably linked to an underlying analytics." Huh? Really? This is news to those of us who have worked in the field for many years. And what does VisualCue's version of interactive visualization look like? Now, for your viewing pleasure, I present and example of their amazing innovation:
One of these collections of icons (binoculars, clock, boat, etc.) is called a tile. You wouldn't ordinarily use a single tile, but an entire screen full of them, arranged as a mosaic, such as the following example:
A screen full of these cute icons would certainly serve as an effective substitute for "subpar" bar charts, tree maps, scatter plots, and the like, if you wanted to overwhelm viewers' senses with utter nonsense. Obviously, these heat map colored icons do not serve the same purpose as quantitative graphs such a bar charts and scatter plots. In fact, there is no purpose for which this display would provide a good solution.
FYI Visual, the predecessor of VisualCue, used the same basic approach except that its icons were all rectangles and an odd combination of colors and shapes served the purpose of the heatmap colors. What the new product calls tiles the old product called KEGS and what the new product calls a mosaic arrangement of tiles the original product called a KEGSET. Other than the names, which are now friendlier, it appears that little else has changed. If you're interested, you can read one of my reviews of the old product in the article "FYI Visual: The Story of a Product that was Built on a Fault."
If this zombie stumbles into your neighborhood, I think the best way to protect yourself against it is to laugh hysterically. If we start laughing now and refuse to cease, we'll chase this zombie back into the darkness from which it emerged before any organization wastes money purchasing it.
By promoting this software, Kerschberg is being irresponsible. By allowing people like Kerschberg to write about things they don't understand, Forbes is demonstrating a complete lack of respect for its readers. Shame on them.
Take care,
These three tasks are so fundamental to data visualization, I've long used them to define the term, as follows:
Data visualization is the use of visual representations to explore, make sense of, and communicate data.
But why is it that we must sometimes use graphical displays to perform these tasks rather than other forms of representation? Why not always express values as numbers in tables? Why express them visually rather than audibly? Essentially, there is only one good reason to express quantitative data visually: some features of quantitative data can be best perceived and understood, and some quantitative tasks can be best performed, when values are displayed graphically. This is so because of the ways our brains work. Vision is by far our dominant sense. We have evolved to perform many data sensing and processing tasks visually. This has been so since the days of our earliest ancestors who survived and learned to thrive on the African savannah. What visual perception evolved to do especially well, it can do faster and better than the conscious thinking parts of our brains. Data exploration, sensemaking, and communication should always involve an intimate collaboration between seeing and thinking (i.e., visual thinking).
Despite this essential reason for visualizing data, people often do it for reasons that are misguided. Let me dispel a few common myths about data visualization.
Myth #1: We visualize data because some people are visual learners.
While it is true that some people have greater visual thinking abilities than others and that some people have a greater interest in images than others, all people with normal perceptual abilities are predominantly visual. Everyone benefits from data visualization, whether they consider themselves visual learners or not, including those who prefer numbers.
Myth #2: We visualize data for people who have difficulty understanding numbers.
While it is true that some people are more comfortable with quantitative concepts and mathematics than others, even the brightest mathematicians benefit from seeing quantitative information displayed visually. Data visualization is not a dumbed-down expression of quantitative concepts.
Myth #3: We visualize data to grab people's attention with eye-catching but inevitably less informative displays.
Visualizations don't need to be dumbed down to be engaging. It isn't necessary to sacrifice content in lieu of appearance. Data can always be displayed in ways that are optimally informative, pleasing to the eye, and engaging. To engage with a data display without being well informed of something useful is a waste.
Myth #4: The best data visualizers are those who have been trained in graphic arts.
While training in graphic arts can be useful, it is much more important to understand the data and be trained in visual thinking and communication. Graphic arts training that focuses on marketing (i.e., persuading people to buy or do something through manipulation) and artistry rather than communication can actually get in the way of effective data visualization.
Myth #5: Graphics provide the best means of telling stories contained in data.
While it is true that graphics are often useful and sometimes even essential for data-based storytelling, it isn't storytelling itself that demands graphics. Much of storytelling is best expressed in words and numbers rather than images. Graphics are useful for storytelling because some features of data are best understood by our brains when they're presented visually.
We visualize data because the human brain can perceive particular quantitative features and perform particular quantitative tasks most effectively when the data is expressed graphically. Visual data processing provides optimal support for the following:
1. Seeing the big picture
Graphs reveal the big picture: an overview of a data set. An overview summarizes the data's essential characteristics, from which we can discern what's routine vs. exceptional.
The series of three bar graphs below provides an overview of the opinions that 15 countries had about America in 2004, not long after the events of 9/11 and the military campaigns that followed.
I first discovered this information in the following form on the website of PBS:
Based on this table of numbers, I had to read each value one at a time and, because working memory is limited to three or four simultaneous chunks of information at a time, I couldn't use this display to construct and hold an overview of these countries' opinions in my head. To solve this problem, I redisplayed this information as the three bar graphs shown above, which provided the overview that I wanted. I was able to use it to quickly get a sense of these countries' opinions overall and in comparison to one another.
2. Easily and rapidly comparing values
Try to quickly compare the magnitudes of values using a table of numbers, such as the one shown above. You can't, because numbers must be read one at a time and only two numbers can be compared at a time. Graphs, however, such as the bar graphs above, make it possible to see all of the values at once and to easily and rapidly compare them.
3. Seeing patterns among values
Many quantitative messages are revealed in patterns formed by sets of values. These patterns describe the nature of change through time, how values are distributed, and correlations, to name a few.
Try to construct the pattern of monthly change in either domestic or international sales for the entire year using the table below.
Difficult, isn't it? The line graph below, however, presents the patterns of change in a way that can be perceived immediately, without conscious effort.
You can thank processes that take place in your visual cortex for this. The visual cortex perceives patterns and then the conscious thinking parts of our brains make sense of them.
4. Comparing patterns
Visual representations of patterns are easy to compare. Not only can the independent patterns of domestic and international sales be easily perceived by viewing the graph above, but they can also be compared to one another to determine how they are similar and different.
These four quantitative features and activities require visual displays. This is why we visualize quantitative data.
Take care,
I expressed my concerns to Dr. Hidalgo by posting the following comments in response to his article:
Dr. Hidalgo,
I'm one of the naysayers in response to the claims of so-called Big Data. I'm concerned primarily with the hype that leads organizations to waste money chasing new technologies rather than developing the skills that are needed to glean value from data. One of the fundamental problems with Big Data is the fact that no two people define it in the same way, so it is difficult to discuss it intelligently. In this article, you praised the benefits of Big Data, but did not define it. What do you mean by Big Data? How is Big Data different from other data? When did data become big? Are the means of gleaning value from so-called Big Data different from the means of gleaning value from data in general?
Stephen Few
He was kind enough to respond with the following.
Dear Stephen Few,
These are all very good questions.
First, regarding the definition of big data:
As you probably know well, the term big data is used colloquially to refer mostly to digital traces of human activities. These include cell phone data, credit card records and social media activity. Big data is also used occasionally to refer to data generated by some scientific experiments (like CERN or genomic data), although this is not the most common use of the phrase so I will stick to the "digital traces of human activity" definition for now.
Beyond the colloquial definition, I have a working definition of big data that I use on occasion. To keep things simple I say that big data needs to be three times big, meaning that it needs to be big in size, resolution and scope. The size dimension is relatively obvious (data on 20 or 30 individuals is not the same as data on hundreds of thousands of them). The resolution dimension is better explained by an example. Consider having credit card data on a million people. A low resolution version of this dataset would consist only on the total yearly expenditure of each individual. A high resolution version, would include information on when and where the purchases where made. In this example, it is the resolution of the data what allows us to use it to study, for instance, the mobility of this particular group of people (notice that I am not generalizing to the general population, since this subpopulation might be worthy of study on its own). Finally, I require data to be big in scope. By this, I require data to be useful for applications other than the ones for which it was originally collected. For instance, mobile phone records are used by operators for billing purposes, but could be used to forecast traffic or to identify the location of mobile phone users prior to a natural disaster (and use this information to help speed up search and rescue operations). When data is big in size, resolution and scope, I am comfortable saying that it is big.
Second: Your question about when big data become big?
This is an interesting question because it points to the evolution of language. During the last decade the word data has begot at least two children: "metadata" and "big data". The word metadata grew in popularity in the wake of the NSA scandal, as people needed to differentiate between the content of messages and their metadata. Big data, on the other hand, emerged as people searched for a short way to refer to the digital traces of human activity that were collected for operational purposes by service providers serving large populations, and that could be used for purposes that were beyond those for which the data was originally collected. Certainly, the phrase "big data" provides an economy of language, and as someone that enjoys writing I always appreciate that.
Regarding the time at which this transition happen, I remember that when I started working with mobile phone data (in 2004) people were not using the word big data. As more people entered the field, the word begun to gain force (around 2008). With the financial crisis, the hype of big data entered full swing, as many framed big data as a the new asset, or technology, that could save the economy. I guess at that time, everyone wanted to believe them :-).
Third and Final: You ask whether the means of gleaning value from big data include the methods used to glean value from data in general.
In short, the answer is yes (it is data after all). Multivariate regressions in all of its forms and specifications are still useful and welcome (I use them often). Yet, these new datasets have also stimulated the proliferation of some additional techniques. For instance, visualizations have progressed enormously during recent years since exploring these datasets is not easy, and large datasets involve more exploration. As an example, check dataviva.info . This site makes available more than 100 million visualizations to help people explore Brazil's formal sector economy. By taking different combinations of visualizations it is possible to weave stories about industries and locations. An example of these stories for a related project, The Observatory of Economic Complexity (atlas.media.mit.edu), can be seen in this video (http://vimeo.com/40565955). Here you will be able to see how these visualization techniques allow people to quickly compose stories about a topic.
Finally, it is worth noting that different people might mean different things when they refer to gleaning value from data. For some people, this might involve explaining the mechanisms that gave rise to the observed patterns, or use the data to learn about an aspect of the world. This is a common approach on the social sciences. For other people value might emerge from predictions that are not cognitively penetrable but nevertheless accurate, such as the ones people obtain with different machine learning techniques, such as neural networks or those based on abstract features. The latter of these approaches, which is often used by computer scientists, can be very useful for sites that require accurate predictions, such as Netflix or Amazon. Here, the value is certainly more commercial, but is also a valid answer to the question.
I hope these answer help clarify your questions.
All the best
I wanted to respond in kind, but for some unknown reason the Scientific American website is rejecting my comments, so I'll continue the discussion here in my own blog.
Dr. Hidalgo,
Your response regarding the definition of Big Data demonstrates the problem that I'm trying to expose: Big Data has not been defined in a manner that lends itself to intelligent discussion. Your definition does not at all represent a generally accepted definition of Big Data. It is possible that the naysayers with whom you disagree define Big Data differently than you do. I've observed a great many false promises and much wasted effort in the name of Big Data. Unless you're involved with a broad audience of people who work with data in organizations of all sorts (not just academia), you might not be aware of some of the problems that exist with Big Data.
Your working definition of Big Data is somewhat similar to the popular definition involving the 3 Vs (volume, velocity, and variety) that is often cited. The problem with the 3 Vs and your "size, resolution, and scope" definition is that they define Big Data in a way that could be applied to the data that I worked with when I began my career 30 years ago. Back then I routinely worked with data that was big in size (a.k.a., volume), detailed in resolution, and useful for purposes other than that for which it was originally generated. By defining Big Data as you have, you are supporting the case that I've been making for years that Big Data has always existed and therefore doesn't deserve a new name.
I don't agree that the term Big Data emerged as a "way to refer to digital traces of human activity that were collected for operational purposes by service providers serving large populations, and that could be used for purposes that were beyond those for which the data was originally collected." What you've described has been going on for many years. In the past we called it data, with no need for the new term "Big Data." What I've observed is that the term Big Data emerged as a marketing campaign by technology vendors and those who support them (e.g., large analyst firms such as Gartner) to promote sales. Every few years vendors come up with a new name for the same thing. Thirty years ago, we called it decision support. Not long after that we called it data warehousing. Later, the term business intelligence came into vogue. Since then we've been subjected to marketing campaigns associated with analytics and data science. These campaigns keep organizations chasing the latest technologies, believing that they're new and necessary, which is rarely the case. All the while, they never slow down long enough to develop the basic skills of data sensemaking.
When you talk about data visualization, you're venturing into territory that I know well. It is definitely not true that data visualization has "progressed enormously during recent years." As a leading practitioner in the field, I am painfully aware that progress in data visualization has been slow and, in actual practice, is taking two steps backwards, repeating past mistakes, for every useful step forwards.
What various people and organizations value from data certainly differs, as you've said. The question that I asked, however, is whether or not the means of gleaning value from data, regardless of what we deem valuable, are significantly different from the past. I believe that the answer is "No." While it is true that we are always making gradual progress in the development of analytical techniques and technologies, what we do today is largely the same as what we did when I first began my work in the field 30 years ago. Little has changed, and what has changed is an extension of the past, not a revolutionary or qualitative departure.
I hope that Dr. Hidalgo will continue our discussion here and that many of you will contribute as well.
Take care,


text:
Speer Empty Shot Capsules 38 Special Box of 50
Product #: 313962 Speer Bullets #: 8780 UPC #: 076683087805
Product Information
Speer Bullets has been known as a leader in innovative bullet technology since Vernon Speer started making bullets in 1943. Speer Empty Shot Capsules are one of those innovative products that Speer is known for. These capsules allow the reloader to create custom shot cartridges to shoot out of their revolver. Simply fill the capsule with your favorite size shot, snap in the base wad and load like a conventional bullet. These capsules are intended for short-range pest and varmint control and not recommended for self-defense. These capsules are not for use in firearms having ported recoil compensators or lever action rifles. Shot not included.
Technical Information
Material: Plastic
These capsules are designed to be filled with small diameter birdshot which will act like a "mini-shotgun" for close range varmint and pest control
Intended for revolvers, not lever action rifles
Shot not included
Load data available from the Speer Reloading Manual
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Material: Plastic
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text:
March 10, 1999 - Industry News
A 17-truck Pennsylvania fleet with the worst safety record in the state has been indicted for encouraging its drivers to exceed federal hours-of-service limits and keep false logbooks
Tags: Safety
Members of the Texas House Transportation Committee are in no hurry to consider a bill calling for uniform speed limits for cars and trucks on many Texas highways, according to the Owner-Operator Independent Drivers Assn
March 8, 1999 - Industry News
The International Motor Carrier Audit Commission sounds like a new government agency about to hassle carriers, but it isn't — at least it isn't a government agency. But that doesn't mean it won't be hassling carriers; it's still too early to tell
March 5, 1999 - Industry News
Bills introduced in both the Ohio House of Representatives and Senate address the issue of uniform speed limits for cars and trucks on the state's highways
March 4, 1999 - Industry News
A panel created by the Louisiana state Legislature voted to recommend slower speed limits for trucks on four-lane highways – but it was far from a unanimous vote
March 3, 1999 - Industry News
Transportation Secretary Rodney Slater is going all-out to focus the nation's attention on transportation safety
The man in the truck safety hot seat at the Department of Transportation advises patience and careful study of the facts before anything is done to the Office of Motor Carriers
February 26, 1999 - Industry News
Turnout was quite low Friday morning for the opening of Parents Against Tired Truckers' first symposium on driver fatigue in San Diego
A log truck driver is being credited with preventing an even worse accident by flipping his truck when a car ahead of him suddenly stopped on a Mississippi highway
February 24, 1999 - Industry News
A bill giving Montana auto drivers a daytime speed limit for the first time since 1995 is expected to be signed by the governor. The measure specifies lower limits for trucks than for other vehicles
The Department of Transportation has announced a two-day national transportation safety conference to take place in Washington, D.C., beginning March 2
The Occupational Safety and Health Administration has issued what amounts to a test balloon for its ergonomics standards.
February 23, 1999 - Industry News
The Office of Motor Carriers got knocked around on Capitol Hill yesterday as Rep. Frank Wolf and others took the agency to task for shortcomings in its enforcement of truck safety rules
February 19, 1999 - Industry News
New Jersey Sen. Frank Lautenberg has spent his 16 years in the Senate plugging away on transportation and other issues. The 75-year-old Democrat has announced he will not run again
February 18, 1999 - Industry News
Secretary of Transportation Rodney Slater has enlisted a respected Washington veteran to help lower the heat in the congressional dispute over truck and bus safety enforcement
Who should be responsible for the maintenance and safety of intermodal equipment – carriers or equipment owners? That's the basic question now being asked by the Federal Highway Administration.
Container chassis and intermodal trailers are often owned
February 17, 1999 - Industry News
Montana moved one step closer Monday to putting up new speed limit signs on its highways, with lopsided House approval of a bill that calls for lower truck limits than the version passed by the Senate
February 16, 1999 - Industry News
If President Clinton has his way, fuel taxes that are supposed to pay for improving the nation's roadways could be put to other uses. Clinton's budget for next year calls for diverting billions of dollars in fuel tax revenue from the highway trust fund to a variety of other transportation programs
February 11, 1999 - Industry News
Debate on the future of the Office of Motor Carriers opened yesterday with hearings before the House Committee on Transportation and Infrastructure.
The status of OMC, the office in the Federal Highway Administration that enforces truck safety rules, is part of a general examination of trucking safety that will unfold in congressional hearings and federal investigations in the coming months
Congress begins taking a closer look at trucking today with the first of several hearings scheduled to look at truck safety and hours of service rules. Also on the agenda of the House Ground Transportation Subcommittee is a discussion to possibly move the Office of Motor Carriers
February 9, 1999 - Industry News
Nearly 7,000 Freightliner Century Class trucks with model years from 1996-1998 have been recalled for windshield wiper problems
February 8, 1999 - Industry News
Rep. Frank Wolf, R-VA, has once again introduced legislation to move the Office of Motor Carriers from the Federal Highway Administration to the National Highway Traffic Safety Administration
The Montana Motor Carriers Assn. opposes the state Legislature's proposed 10-mph increase in speed limit for trucks on Interstate highways
February 4, 1999 - Industry News
The Montana House is holding a hearing today on a bill setting new speed limits
February 3, 1999 - Industry News
Government and safety representatives are willing to look at bigger and heavier trucks if the industry can prove they're safer and easier on the roads, said Freightliner President and CEO Jim Hebe Tuesday at a press conference at the company's Portland, OR, headquarters
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John Fritz MOREAU Twitter Statistics
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Twitter Counter is the #1 Twitter stats site powered by Twitter. It all started in June 12, 2008 and we grew rather rapidly because of our Twitter Counter badge. The button is a nice small image that shows your visitors how many followers you have on Twitter. Within a year the button was on many many blogs around the world and we displayed more than 100 million buttons in one month. We track follower stats for over 94 million users now.
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This blog covers a technique for automatic property validation while using KVC in iOS. The default validation for KVC requires you to implement a method for every property you want to validate. It also requires you to manually call the validation method. This blog post provides a way to make this all happen automatically.
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Zombie Plowboy
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Thursday, August 1st, 2013 at 8:00pm
All Ages
Zombie Plowboy at the stunning Musiquarium Lounge Seattle, home to 1900 fish swimming around. Show starts at 9 pm
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How This Table Art Created a Dialogue About Our Food System
How, as social designers, can we best communicate pressing issues and engage others in a healthy dialogue?
One way is to put on a gallery show. And that's just what our class at DSI did.
Teamed up with the renowned Kevin O'Callagan and his supportive team, we expressed and exhibited 24 different views of the global food system by 'Putting It All On The Table' at the SVA Gramercy Gallery.
The catch? We each had to present an issue using a simple IKEA table and chair.
Caught In A Maize by Gina Kim
We dove deep into the global food system. The topics embraced a diverse range of issues including the US Farm Bill, GMOs, food security, waste, environmental impacts, public health, and corruption. At every level of every community, food is essential to our lives.
The beauty of the exhibition room was not only how each table told a different story, but also how they all tied into a larger narrative. Donella Meadows, a pioneer of systems-thinking, describes this well, '"We can't impose our will on a system. We can listen to what the system tells us, and discover how its properties and our values can work together to bring forth something much better than could ever be produced by our will alone."A system is dependent on all of its parts.
Our food system is broken, and so are many other systems.
Our goal was to create an experience that opened peoples' eyes to the realities on their dinner plates. As social designers, we want to understand not only where they're twisted, but why they're twisted, and by whom. If the elements of a system aren't in sync, it risks being thrown off balance and compromising its beautiful complex resilience.


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Lismore Workers Sports Club, Goonellabah
Solo Guitar & Vocalist more
DAN HANNAFORD Saturday, November 29 2014, 6.30pm. Free Live Entertainment. more
Regular performers at the Lismore Workers' Club. more
Cherry Street Sports, Ballina Dc
A blues & jazz group from Byron Bay more
Trombone Kellie and The Muddy Roaders putting the swing back into each & every performance! Gaining a following of eager supporters wherever they perform. more
Headliners Chorus - Vocal Production Course Monday, October 20 2014, 6.30pm more
Thursday, December 04 2014, Doors open 7.45pm, Show starts 8.30pm more
Regular performer at the Workers' Club with a loyal following. Playing the music you grew up with. more
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The best part of one's life is the working part, the creative part. Believe me, I love to succeed... However, the real spiritual and emotional excitement is in the doing.Garson Kanin
I've spent most of my life walking under that hovering cloud, jealousy, whose acid raindrops blurred my vision and burned holes in my heart.Astrid Alauda
All our work, our whole life is a matter of semantics, because words are the tools with which we work, the material out of which laws are made, out of which the Constitution was written. Everything depends on our understanding of them.Felix Frankfurter
There is no end. There is no beginning. There is only the passion of life.Federico Fellini
Life is all about timing... the unreachable becomes reachable, the unavailable become available, the unattainable... attainable. Have the patience, wait it out It's all about timing.Stacey Charter
Life is God's novel. Let him write it.Isaac Bashevis Singer
Live your life and forget your age.Norman Vincent Peale
There are two ways to slide easily through life: to believe everything or to doubt everything; both ways save us from thinking.Theodore Rubin
Side effect of overemphasizing the importance of personal security in your life is that it can cause you to live reactively.Steve Pavlina
The greatest discovery of my generation is that a human being can alter his life by altering his attitudes of mind.William James 1842
A true man does not need to romance a different girl every night, a true man romances the same girl for the rest of her lifeAna Alas
Humility is the only true wisdom by which we prepare our minds for all the possible changes of life.George Arliss
The most wonderful of all things in life, I believe, is the discovery of another human being with whom one's relationship has a glowing depth, beauty, and joy as the years increase. This inner progressiveness of love between two human beings is a most marvelous thing, it cannot be found by looking for it or by passionately wishing for it. It is a sort of Divine accident.Sir Hugh Walpoe
Throughout life people will make you mad, disrespect you and treat you bad. Let God deal with the things they do,cause hate in your heart will consume you too.Will Smith
Life is an adventure in forgiveness.Norman Cousins
My faith has been the driving thing of my life. I think it is important that people who are perceived as liberals not be afraid of talking about moral and community values.Marian Wright Edelman
There can be no vulnerability without risk; there can be no community without vulnerability; there can be no peace, and ultimately no life, without community.M. Scott Peck
Sleep that knits up the ravelled sleave of care The death of each day's life, sore labour's bath Balm of hurt minds, great nature's second course, Chief nourisher in life's feast.William Shakespeare
Life is something that happens when you can't get to sleep.Fran Lebowitz
Living to a ripe old age may not be one of humanity's great blessings, but to live with gusto at a ripe old age is to discover not only what life is about, but what it's always been about.Joe Klock