Jeff Bezos Should Put His Billions Into Libraries | WIRED
The Importance of Access to Technology in the Public Library System
Pizza Post — Nicholas A. Rossi
Python web scraping selenium
Buyers Guides | MultiView
selling to associations
Putting the science back in data science - O'Reilly Media
Reproducibility, scripts
The Equality of Opportunity Project
Great examples irf data documentation
IT Upgrade Policy Review (2001 - State of Washington)
Desktop software is produced or upgraded on an 18-month cycle. One software upgrade can usually be skipped without suffering productivity or support issues. But by the end of the third year, the software must be upgraded to keep up with vendor support, and compatibility within and among agencies and other partners. It is frequently impossible to continue using an older version, because incompatibility with other systems eventually forces an upgrade. Once one workgroup upgrades, everyone in the agency needs to upgrade to maintain compatibility, or else document compatibility and information- sharing issues become prominent, and support costs increase with the complexity of multiple versions. The software then drives the hardware needs by requiring more memory, storage capacity, and faster processing speeds. Likewise, when a central service agency, such as the Office of Financial Management, upgrades or requires a specific version of a program for use with central systems, all agencies using that system must upgrade as well.
Donald Trump nominations list
Great data access and presentation from WaPo, with partnership for public service. appointments and confirmations.
CIA Simple Sabotage Field Manual - for organizations
Thought you all would enjoy this. In 1944 the OSS ( predecessor agency to the CIA) developed the "Simple Sabotage Field Manual" - a pamphlet for German nationals who worked in the Nazi bureaucracy but were Allied Forces sympathizers. There were simple but effective ways to much up the Nazi machinery (both literal and figurative). Skip past the sections on sabotaging buildings, water sources, manufacturing centers, railways, and telegraphs. The really good reading starts on page 28: General Interference with Organizations and Production. I think a lot of it will resonate with you. Without further adieu, I give you, the Simple Sabotage Field Manual.
great viz: % of America Chose Trump and Clinton as the Nominees - The New York Times
Inside the Obama Tech Surge as it Hacks the Pentagon and VA — Backchannel
(Fligstein) Why the Federal Reserve Failed to See...
Theory of sense making
Get the Report : Financial Crisis Inquiry Commission (nopost)
Public Domain & Open Source (nopost)
What Gartner’s Bimodal IT Model Means to Enterprise CIOs | CIO
The Pitch Meeting for Animaniacs - The Toast - The Toast
EXEC #2: You’re saying that ten years from now, a young person will watch The Godfather or read Freud for the first time and realize that the Viennese shrink archetype in their minds was actually from Animaniacs all along? And the mumbling mafia don and the plot of Les Miserables and the fall of the Tsars? That the show will act as a sort of contextual membrane through which kids absorb quintessential images that will one day render direct source material more accessible, and that the cultural déjà vu they experience when they encounter said material will recur throughout their adult lives?
Monegraph: News
The Procrastination Matrix - Wait But Why
The matrix was popularized in Stephen Covey’s famous book, The Seven Habits of Highly Effective People and is named after President Dwight Eisenhower. Eisenhower was well-known for being tremendously productive, which Covey credits to his “first things first” attitude on how to spend your time. And to Eisenhower, the “first things” were always the important ones. He believed you should spend nearly all of your time in Quadrants 1 and 2, and he accomplished this with a simple D-word for each quadrant: Eisenhower Matrix Actions And that’s fantastic for Dwight fucking Eisenhower. But you know what Dwight clearly didn’t have in his bald head? An all-powerful Instant Gratification Monkey. If he had, he’d know that a procrastinator’s matrix looks like this: Procrastinator's Matrix
Star Wars: The Force Accounted
Feels rich despite simple data.
What Drives Gun Sales: Terrorism, Obama and Calls for Restrictions - The New York Times
Seasonal adjustment and d3
Cities and Towns in Europe over 1000 Inhabitants [2059x1779]
This link is a useful illustration of the effect of criteria definition on a visualization
Are Polls Ruining Democracy? - The New Yorker
Gallup had always wanted to be a newspaper editor, but after graduating from the University of Iowa, in 1923, he entered a Ph.D. program in applied psychology. In 1928, in a dissertation called “An Objective Method for Determining Reader Interest in the Content of a Newspaper,” Gallup argued that “at one time the press was depended upon as the chief agency for instructing and informing the mass of people” but that newspapers no longer filled that role and instead ought to meet “a greater need for entertainment.” He therefore devised a method: he’d watch readers go through a newspaper column by column and mark up the parts they liked, so that he could advise an editor which parts of the paper to keep printing and which parts to scrap. Burdick’s dystopianism is vintage Cold War: the Strangelovian fear of the machine. (Burdick also co-wrote “Fail Safe,” in which a computer error triggers a nuclear war.) But after 1960 the D.N.C. essentially abandoned computer simulation. One reason may have been that L.B.J. wasn’t as interested in the work of M.I.T. scientists as Kennedy had been. For decades, Republicans were far more likely than Democrats to use computer-based polling. In 1977, the R.N.C. acquired a mainframe computer, while the D.N.C. got its own mainframe in the eighties. The political scientist Kenneth Janda speculates that the technological advantage of the Republican Party during these years stemmed from its ties to big business. Democratic technological advances awaited the personal computer; the R.N.C. is to I.B.M. as the D.N.C. is to Apple. Then came the Internet, which, beginning with the so-called MoveOn effect, favored Democrats but, as Matthew Hindman argued in “The Myth of Digital Democracy,” has not favored democracy.
District Data Labs - How to Transition from Excel to R
Why the D.C. area risks losing its allure to millennials - The Washington Post
Roadmap for the Washington Region’s Economic Future. “The Washington region really needs to up its game.” The study, based partly on 35 in-depth interviews with chief executives and other leaders of local companies, also identified other barriers to economic growth in the region, including inequalities and competition among jurisdictions and Washington’s reputation for political gridlock and inefficiency. The survey was commissioned by the Roadmap group. It is seeking an ambitious, area-wide response to the historic slowdown in federal spending. [Here’s how D.C. business thinks region should react to painful sequestration] Founded by the 2030 Group, a business organization, the Roadmap has 12 other sponsors, including the Greater Washington Board of Trade, Federal City Council, Fairfax and Montgomery chambers of commerce, Metropolitan Washington Council of Governments and the Washington Regional Association of Grantmakers.
Higher Ed's Moneyball? : NPR Ed : NPR
all it higher ed's version of Moneyball. Only the goal isn't a World Series ring; it's to help more students stick with college, improve academically and graduate. Fast analysis of disparate data streams, including your daily Web surfing, helps corporate America market its goods, chart growth and follow you across the Internet with annoying ads. Innovative predictive analytics are essential for businesses, especially tech companies. They've got annual conferences on the stuff.
Tracking Boston’s Progress With Just One Number -
“It’s a way for the mayor to say, in a given day, how well are we doing to meet our targets, or how much improvement do we need to meet our targets?”
The influence of elites, interest groups and average voters on American politics - Journalist's Resource Journalist's Resource
Amazon Jobs | Our Leadership Principles
Worldwide cybersecurity market continues its upward trend | CSO Online
Saturday Morning Breakfast Cereal
Investors pour billions in to cybersecurity firms | CSO Online
Ann's Blog | Avoiding diagonal text in your charts, and other shameful mistakes I made before I knew better
1980s computer controls GRPS heat and AC |
Putting the Service-Profit Chain to Work - HBR
Performance Curve Database
Getting started with visualization after getting started with visualization
When Maps Shouldn’t Be Maps | Matthew Ericson -
Stephen Few: Show Me The Numbers | Michael Sandberg's Data Visualization Blog
Anscombe’s quartet
why do data visualization. same mean. same median.
Joshua Tauberer’s Curriculum Vitae
FITARA – Big Deal or Big Snooze? |
OMB clearly was determined to implement FITARA in a new and far more effective manner. OMB’s initial draft of FITARA guidance survived the interagency review process remarkably intact. The version that is out for comments now is in many respects a model for how policy guidance should be developed. OMB Deputy Director for Management Beth Cobert, CIO Tony Scott, and E-Government chief Lisa Schlosser should be commended for producing a public policy document that will make a difference rather than just answering the mail.
Nate Silver's big-data insights -- FCW
If big data is to become a standard tool by which the government operates, aging legacy IT systems will have to modernize. This is no small feat, given that 70 percent of the federal government's $79 billion IT budget in 2011 was spent on maintaining existing systems. Many federal systems still run Common Business-Oriented Language (COBOL), a programming language developed in 1959, ten years before NASA put a man on the moon. But perhaps the biggest obstacle required before big data becomes a big staple in the government's IT arsenal is peoples' "goals and attitudes," Silver said. Old-hat policies need to change – Silver later told feds at the conference that "bureaucracy is the enemy of imagination," to smiles and knowing glances around the room. Changing policies means changing people's beliefs about what big data is and what it might do. Big data is not a cure-all, and it is inherently filled with noise and uncertainty, but it does have tremendous potential if people approach if the right way. "The world is not lacking for techniques, it's more about the right goals and right attitudes," Silver said. In November, NOAA's big-data based supercomputers took in data from polar-orbiting satellites, weather buoys and Gulfstream-IV and P-3 jets to churn out high-resolution computer models of Hurricane Sandy's path every six hours for several days before the storm landed. Residents in the storm's path had ample warning, and though more than 100 people died, without big data the net loss of life would have been far higher. Even in its infancy, big data is changing the way agencies perform. The Department of Health and Human Services is changing the way it responds to disasters and the Department of Defense's global shared service center has implemented a big-dated based business activity monitoring software tool that has so far detected $4 billion in improper payments. "One thing data doesn't do is tell you what your goals ought to be," Silver said. "You still have to think about what to accomplish. Data is not a substitute for judgments you have to make."
The ‘Moneyball’ effect on K Street: The influence game gets scientific - The Washington Post
'Northern American Megalopolises': An Objective Response to 'The Emerging Megaregions' [OC] [2000x997] : MapPorn
What happened with the GSA in Vegas stymies federal workers - The Washington Post
You have an outrageous case and all of a sudden you have a blanket law,”
free-programming-books/ at master · vhf/free-programming-books
Monegraph Uses Bitcoin Tech So Internet Artists Can Establish “Original” Copies Of Their Work | TechCrunch
(Conceptual) Art, Cryptocurrency and Beyond |
Ten Secret Truths About Government Incompetence by Donald F. Kettl | The Washington Monthly
Donald F. Kettl is a nonresident senior fellow at the Volcker Alliance and the Brookings Institution and a professor in the University of Maryland School of Public Policy, where he served as dean from 2009 to 2014.
Union Square Ventures' Serial Investor, Joel Monegro: Blockchain Tech Will Disrupt Traditional Business Models
Many of the Ways that Tyler Clippard Is Unusual | FanGraphs Baseball
Inside Obama's effort to use science — and find policies that actually work - Vox
A couple of years ago, former Obama and Bush officials estimated that only 1 percent of government spending is backed by any evidence at all. 1 percent. Perhaps unsurprisingly, then, evaluations of government-sponsored social programs have found that some three-quarters of them have no effect on the people they were designed to help.
Top Navy official asks Congress to strip out acquisition regulations -- FCW
The statement reflects growing agreement between Capitol Hill, the Defense Department and industry players that the acquisition process has grown intolerably complex and is undercutting the Pentagon's technological competitiveness with adversaries.
The Urban Institute | Challenges and Choices for the New Mayor
map of colonial south america (8544×10404)
18F — FOIA Modernization
(5) FOIA scrum board | Trello
Tangled Up in FOIA Requests, Agencies Turn to Technology -
How one company is trying to tackle Big Data’s big problem - The Washington Post
Joining the dots | Civil Service Quarterly
he trouble with data However, much of that data is still locked-away in separate silos, created for a time when a dataset served a single human need. We tend to release our data in separate files or documents, the result being hundreds or thousands of spreadsheets on various websites, even if they are all brought together through the government’s data portal ( Publishing in this disconnected, piecemeal way can create significant overheads. Spreadsheets are hard to find and difficult to use when the user only requires certain columns from a particular file. The result is a user community that spends significant time and effort copying, pasting and reformatting data before they can use it. These problems are exacerbated when users combine DCLG data with other third-party sources. For instance, imagine you are a homelessness advisor wanting to link together separate spreadsheets from DCLG, Ministry of Justice and Local Authority data on, say, homelessness and housing in Cornwall. How has each data publisher defined Cornwall in its own spreadsheet? Have they used names or codes, and are these consistent across all sources? We invariably find a lack of commonality or standards here, which again translates into unnecessary time and effort to prepare data for re-use.
A Collection of Uncommon Points of View on Startups
Tweet from Dataviz & AI (@DataVizAI)
Bowser official says open gov improvements are in the works - DC
Our Favorite Talks from The Lean Startup Conference: Day 1 | The How
A Dozen Things I’ve Learned from Eric Ries about Lean Startups (“Lattice of Mental Models” in VC) | 25iq
Lean startup
Top Political Campaign Software | 2014 Reviews of the Best Systems
Beginner's guide to X-Wing and TIE Fighter: joystick issues, controls, and picking a version | PCGamesN
The cancer of bureaucracy: how it will destroy science, medicine, e... - PubMed - NCBI
Dubious analysis inspires a closer look?
mbostock/us-rivers · GitHub
This is a great project.
The Art of Not Working at Work - Atlantic Mobile
Bob Behn on PerformanceStat
, Senior Lecturer, Harvard Kennedy School of Government Tuesday - 11/4/2014, 4:10pm EST Bob Behn The Office of Management and Budget says "stat" sessions -- Portofolio Stat, Tech Stat, etc. -- have saved the government millions of dollars. Agencies are developing their own approaches to the Stat model. Bob Behn is Senior Lecturer in Public Policy at the Kennedy School of Government at Harvard University. He publishes the Performance Leadership Report, and his latest book is The PerformanceStat Potential: A Leadership Strategy for Producing Results. On In Depthwith Francis Rose, Bob said one big problem with implementing Stat sessions is convincing people they won't be bashing sessions.
DataKind | Director of Programs
Every ColorBrewer Scale
Introducing: Flickr PARK or BIRD |
The Real Revolution in Online Education Isn't MOOCs - Michelle Weise - Harvard Business Review
Something is clearly wrong when only 11% of business leaders — compared to 96% of chief academic officers — believe that graduates have the requisite skills for the workforce.
Obama to name longtime political aide as 'Ebola czar,' bypassing senior health official | Fox News
Balance between WH and agencies.
Your E-Book Is Reading You - WSJ
DC Free Law Innovation Fellowship - Civic Hacking on the D.C. Council - Screendoor
DC’s open data directive adopts the mistakes made by the White House Joshua Tauberer’s Blog
Why Governments Don’t Know Bridges Are Deteriorating
Why not? For one thing, preparers have pushed back against such disclosures as overly time consuming and expensive. 
Make Cities Explode in Size With These Interactive Maps | Science | Smithsonian
Data mining your children
Data Science Toolkit
What the data world can learn from the fashion industry - O'Reilly Radar
Don't infer, ask! We are beguiled by a key concept from this report: fashion innovators spend time listening to their customers and turning what they hear into data. The result is data that is critical to understanding what fashion consumers are interested in, how they are engaged, and what motivates them.
Breaking down the White House big data and privacy report
Ten years ago, many large companies knew next to nothing about their customers. At Burger King, for example, “You’d hand over your $2, you’d get your Whopper, and that was it,” Kirk Nahra, a partner with Wiley Rein, says.
Full Stack Development - fetching data, visualizing with D3, and deploying with Dokku - Real Python
Why I regret being a nice boss: Setting boundaries with employees.
Almost every “person problem” is really a structure problem—a crack in the system where the rule-makers have failed to effectively communicate with the rule-followers. Back when I ran Yola, a quotation attributed to George Patton often came into my head: “Never tell people how to do things. Tell them what to do, and they will surprise you with their ingenuity.” Personal ingenuity flourishes when there is a strong structural foundation in place—when people know exactly what is expected of them. 
Government as a Platform-- Open Government - O'Reilly
Hey Uncle Sam, Eat Your Own Dogfood — Medium
However, we appear to have stalled out a bit in our progress towards government as platform. It’s incredibly difficult to ingest the data for successful commercial products. The kaleidoscope of data formats in open data portals like might politely be called ‘obscure’, and perhaps more accurately, ‘perversely unusable’. Some of the data hasn’t been updated since first publication, and is quite positively too stale to use. If documentation exists, most of the time it’s incomprehensible.
(Data) Warehouse for Laymen — Medium
Citizen Onboard
Citizen Onboard is a national project to understand how our own government services work and don't work. We tear down so we can build up. Learn how to contribute!
District studies roots of dropout crisis and promises it will work to fix it - The Washington Post
new York urban density
Jobs Charted by State and Salary
The chart below shows what people do and what they get paid. These vary depending on where you live. Select a state in the drop-down menu, and use the slider to adjust the median annual salary. treemap
Visualization: Salaries by Occupation and Industry
Sometimes the amount you get paid can vary a lot for the same job across industries. Browse salary ranges for over 800 occupations, across 100 industries and 20 sectors. Estimates are for 2013 from the Bureau of Labor Statistics. Read more →
Americans don’t care for Washington. New research suggests the feeling is mutual. - The Washington Post
"The most disturbing finding was that members of Washington policy community have a jaundiced view of ordinary Americans, and they didn’t know very much about ordinary Americans either," Ginsberg said. When asked how much they thought the average American knew about a variety of policy debates, like raising taxes on the rich, warrantless wiretapping, and government's role in healthcare, policymakers most frequently said "very little."
Transparency, Open Government and Open Data Directive | DC
2014-15 News Releases / 20140910_Big Data Winner
The Decalogue of Policy Making 2.0: Results from Analysis of Case Studies on the Impact of ICT for Governance and Policy Modelling - Springer
1776 - The Innovation Police: When It Comes to Code Academies, Where Is the Crisis?
Why Putin’s Russia is weaker than the USSR, in one chart - Vox
The new hero of big data and analytics: The Chief Data Officer
Muriel for Mayor » Issues
using Google Maps for non-geographic representations | diana maps
Browse Maps - Places & Spaces: Mapping Science
Infosthetics: the beauty of data visualization | PingMag : Art, Design, Life – from Japan
Interesting example trying to explore large topics
PIOs stretched too thin, lack authority to affect change
Why H.U.D. Ran From Grace - New York Times
In examples too numerous to mention - from cash management and debt collection, to H.U.D.'s giant, complex organization, to the incredible lack of modern accounting and financial management systems, to an almost total breakdown in management planning and evaluation, to the absence of managerial accountability - the Grace commission had H.U.D. pretty well pegged.
New Yorker online free for three months. What should you read?
DVDC Strategy and Visualization
D3 forced direction diagram of comments Interactive art data sculptures Local newsroom turning news into visualizations Engage
Data Blueprint - Unlocking Business Value through Data Management
Whitemarsh Information Systems Corporation - WisWeb Homepage
Is this homepage an image map? In 2014?
Big Data, Chief Data Officers and the Promise of Performance
NYC Digital - Digital RoadMap
Includes original 2011 and updated 2013.
The Man Who Put the 'M' in OMB
Sir Robert Peel’s Nine Principles of Policing -
Effectiveness Versus Efficiency:Operations Research in a New Light - Springer
Operations researchers have traditionally been concerned with well-structured problems which have one best solution or a range of acceptable solutions. Social scientists, on the other hand, deal with hard-to-structure problems in which it is very difficult to define what “best” means let alone find the best solution. Stated differently, operations research attempts to find the most efficient means of reaching a goal given a particular problem formulation. In contrast, social sciences tend to question the validity of the goal itself by treating the problem formulation not as a given but as open to challenge and revision.
The "-Stat" Movement Turns Twenty | IBM Center for the Business of Government
Compstat performancestat
eRegulations Insights: Overview | Splunk
How to Get City Governments to Sell What They Don’t Even Know They Own – Next City
Parsing Politicization: Presidents, Responsiveness, and the Office of Management and Budget authored by Rudalevige, Andrew. and Dickinson, Matthew.
Two days before submitting the plan, the Council decided to change the proposed name to the Office of Management and Budget to appease congressional leaders and others who in consultations had opposed the dropping of “Budget.”
Full text of "Development of the management function in the Office of Management and Budget."
The Emergence of Government Innovation Teams | Brookings Institution
Visual Business Intelligence - Why Do We Visualize Quantitative Data?
The Social Responsibility of Business is to Increase its Profits, by Milton Friedman
The paper.
Mahler: Where to Start | Classic FM
GAO: Data Transparency:: Oversight Needed to Address Underreporting and Inconsistencies on Federal Award Website
Couldn't find agency records to compare most data elements so concluded they were inaccurate?
How to Harness the Wisdom of Crowds in Public Services
Marketing Emails, and Why Data Science Is Like a Good Jockstrap
Part I: Deciding on a graduate program in statistics | StatsbyLopez
equal population eu states map (2000×1987)
Would be cool to do for federal government
Google Play Music Timeline Visualization
Making News at The New York Times
The Dissolution of an Analytics Team
In the fullness of time, this CAO moved on, and the BA group merged with its sister group. The "replacement CAO" -- an experienced general business manager with no BA experience -- insisted on reviewing all findings before passing them on to the business units. This CAO insisted that findings matched business opinions and projected desired perceptions; anything inconsistent was discarded. Because the CAO didn't support lieutenants as they dealt with opinion-based clients, these clients felt free to push harder to make results fit their opinions and to make their performance look good.
Amazon Customer Service and Jeff Bezos' Emails
Assessing Product Opportunities
1. Exactly what problem will this solve? (value proposition) 2. For whom do we solve that problem? (target market) 3. How big is the opportunity? (market size) 4. What alternatives are out there? (competitive landscape) 5. Why are we best suited to pursue this? (our differentiator) 6. Why now? (market window) 7. How will we get this product to market? (go-to-market strategy) 8. How will we measure success/make money from this product? (metrics/revenue strategy) 9. What factors are critical to success? (solution requirements) 10. Given the above, what’s the recommendation? (go or no-go)
Product Discovery
I really like this
Why government data sites are so hard to use
Audience shift
works cup allegiances via Facebook
What if everything we know about poor countries' economies is totally wrong? - Vox
facebook Case: A Glimpse Into a Toy Department
 I've noticed an undercurrent where individuals or teams too often think of corporate rules, best practices, guidelines, and even laws as being impediments to their ability to do their jobs. It's an attitude of intellectual superiority and privilege.
How to Win at Monopoly ® - a Surefire Strategy
Dropping Loot –
What's A Vice President of Product Management? | Rich Mironov's Product Bytes
The Art and Science of Data-driven Journalism | Why Data Journalism Matters | Tow Center for Digital Journalism
Obama’s management problem - Vox
What went wrong at the VA? - The VA scandal, explained - Vox
VA officials could have, of course, reported those long wait times to the federal government, but that could have meant losing out on pay bonuses hospitals receive for keeping wait times short. What's scandalous about the behavior at the Phoenix VA hospital is that, instead of making the long wait times public in hopes of fixing the problem, administrators tried to make it look like the issues didn't exist at all.
What are you going to do with that degree?
Jobs by college major This is a quick Sankey visualization of how college majors relate to professions, based on data from the American Community survey. On the left are the larget college majors; to the right are the most common professions. To see broad fields like "Sciences" and "Humanities", see the edited version of this page. 
Episode 536: The Future Of Work Looks Like A UPS Truck : Planet Money : NPR
UPS analytics
What broke Washington - The Washington Post
Human responsibility should be restored as the operating philosophy for democracy. Only real people, not bureaucratic rules, can make adjustments to balance a budget, or be fair, or change priorities. Democracy cannot function unless identifiable people can make public choices and be accountable for the results.
Who’s Afraid of Data-Driven Management? - Jeff Bladt and Bob Filbin - Harvard Business Review
What are the most overrated films? | Benomics
The FCC’s net neutrality Twitter chat was actually useful - The Washington Post
Not terrible public comment.
What the hell is happening at the VA? - Vox
Besides the secret list, the Phoenix VA hospital already provided a different, official wait list to DC that allowed VA higher-ups to verify that patients are being treated in a timely manner (within 14 to 30 days). But Phoenix's secret wait list supposedly avoided federal oversight with an elaborate scheme in which officials shredded evidence that some patients were taking months to be seen. What's worse, if someone died while waiting for an appointment due to the secret wait list, Phoenix officials would allegedly discard the name as if the fatal error never happened.
Piketty's Inequality Story in Six Charts : The New Yorker
Fairness vs. Freedom: Is Politics Going Back to the 1970s? | FiveThirtyEight
Example of easy analysis alternative to surveys or structure Data etc over decades. Keyword search of party platforms.
The Education of a Public Man -
When Congress fails - The Washington Post
Why ‘trust and safety’ are no longer free on UberX and Lyft
Perils of innovation. There is a reason why taxis are expensive. Your "tech" solution is valuable because it cuts out protections, not because it is a slam dunk mobile innovation.
AllAnalytics - Beth Schultz - IT & Marketing Meet at the Digital Business
the SAS Global Forum Executive Conference earlier this week. Starbucks and its digital agenda first came up in casual conversation with Wilson Raj, global marketing director of customer intelligence at SAS. I bumped into Raj on Monday morning, just as the conference was getting underway for its first full day. We talked about the conference size -- at 1,500 executive attendees, a sure sign that interest in data-driven decision making had captured corporate leadership's attention. 
College Basketball Data Aplenty for Those Who Can Afford It -
The U.S. government owns thousands of unused buildings it doesn’t know what to do with
Transforming data into smart business analytics -
In the studio today is David Rubal, Public Sector Pre-Sales Consulting Manager with Tableau Software. Tableau makes it easy for people to rapidly transform data into smart business analytics. Their self-service analytics tool helps federal agencies perform fast, ad hoc analysis on data of any size and format without special coding or scripting. This solves a key problem federal information professionals have - they are bombarded with massive data sets and are striving to get a handle on what that "big data" means. During the interview, Rubal discusses big data in government and how Tableau Software helps Federal agencies see and understand data through native connectors to 40 spreadsheet, data warehouse, cube, database and big data sources. Not just big data, but garden variety data as well. Rubal explains how to use Tableau with traditional data sources to create interactive financial, operational and mission-critical visualizations, views and dashboards. For more face-to-face information, Tableau is sponsoring their first Government Executive Forum in DC in November.
How Google Is Using People Analytics to Completely Reinvent HR
30 thought leaders in Data Visualization « Big Data Made Simple
Don't Measure Customer Satisfaction – Ask For Actionable Feedback Instead | SurveyGizmo
Since when is being “satisfied” a good thing? It’s a mediocre achievement. I want ecstatically happy customers, evangelists and zealots that tell me everything they love and hate about our product. I want passion – not satisfaction. As a company that relies 100% on word of mouth marketing — I don’t want “satisfied” customers.
Avoiding the Weaknesses of Traditional Assessments of Customer Satisfaction | Marketing Research Association
According to an explanation of customer satisfaction developed by the author, customer satisfaction is at risk every time a prospect or customer comes into contact with any aspect of a supplier company. Each contact, or moment of truth, is an opportunity to strengthen or weaken customer satisfaction. Level of customer satisfaction/dissatisfaction with a supplier is the result of a customer’s cumulative total experience with these moments of truth. Prospects and customers have six points of contact with a supplier: the supplier’s core products or services (e.g., cleaning and polishing chemicals, motor vehicle parts, contract security services, banking services); policies (e.g., credit and warranty policies); procedures (e.g., ordering and returned goods procedures); non-core business functions (e.g., billing); properties (e.g., vehicle fleet, Web site, voice mail system); and personnel (e.g., switchboard operator, service technician, customer service rep, sales staff). A company’s market research and management practices determine customers’ experiences at these six points of contact. To ensure customers consistently have experiences that give them reasons to keep coming back, a company’s managers require timely and complete information about customers’ standards for the company’s core products or services, procedures, policies, properties, personnel and non-core business functions
The 10 Commandments of Product Marketing
Fostering Innovation, Creating Jobs, Driving Better Decisions: The Value of Government Data
A Guide to the National Income and Product Accounts of the United States
Lawmakers Want Agencies to Share Information on Job Applicants - Management -
Why Philadelphia's first Chief Data Officer quit - Philly
The new clearance system is “superior” to a property-tax balance API, Tolson said. Headd disagrees. “A self-certifying website is a 20th century answer to the problem of tax deadbeats,” he wrote in an email. “An open data API is a 21st century answer to the problem. And that was my single biggest frustration during my time at the city — we were constantly using 20th century answers to problems that required a 21st century solution.”
Catalist | Product
The History of BI: The 1980's and 90's - - Dataconomy
Make a random Pleasing color.
Lionel Messi Is Impossible | FiveThirtyEight
This kind of investigation is what collecting huge amounts of granular data in standardized formats allows.
Visualizing Algorithms
Mike Bostock: Algorithms are a fascinating use case for visualization. To visualize an algorithm, we don’t merely fit data to a chart; there is no primary dataset. Instead there are logical rules that describe behavior. This may be why algorithm visualizations are so unusual, as designers experiment with novel forms to better communicate. This is reason enough to study them. But algorithms are also a reminder that visualization is more than a tool for finding patterns in data. Visualization leverages the human visual system to augment human intellect: we can use it to better understand these important abstract processes, and perhaps other things, too.
Downloading Your Email Metadata
On N.C.’s Outer Banks, scary climate-change predictions prompt a change of forecast - The Washington Post
Even with an eight-inch forecast, 414 Dare County properties worth $70 million would be marked for inundation. If the state ever activates the Web site that lets potential investors search by address, Kelly said, “all of a sudden, those properties would be worthless.”
Lean manufacturing - Wikipedia, the free encyclopedia
Lean manufacturing, lean enterprise, or lean production, often simply, "lean", is a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful, and thus a target for elimination. Working from the perspective of the customer who consumes a product or service, "value" is defined as any action or process that a customer would be willing to pay for. Essentially, lean is centered on preserving value with less work. Lean manufacturing is a management philosophy derived mostly from the Toyota Production System (TPS) (hence the term Toyotism is also prevalent) and identified as "lean" only in the 1990s.[1][2] TPS is renowned for its focus on reduction of the original Toyota seven wastes to improve overall customer value, but there are varying perspectives on how this is best achieved. The steady growth of Toyota, from a small company to the world's largest automaker,[3] has focused attention on how it has achieved this success.
Creating And Deploying Small-Scale Projects | NPR Visuals
In addition to big, long-term projects, the NPR Visuals team also produces short-turnaround charts and tables for daily stories. Our dailygraphics rig, newly open-sourced, offers a workflow and some automated machinery for creating, deploying and embedding these mini-projects, including: Version control (with GitHub) One command to deploy to Amazon S3 A mini-CMS for each project (with Google Spreadsheets) Management of binary assets (like photos or audio files) outside of GitHub Credit goes to Jeremy Bowers, Tyler Fisher and Christopher Groskopf for developing this system.
ZMap · The Internet Scanner
ZMap is an open-source network scanner that enables researchers to easily perform Internet-wide network studies. With a single machine and a well provisioned network uplink, ZMap is capable of performing a complete scan of the IPv4 address space in under 45 minutes, approaching the theoretical limit of gigabit Ethernet. ZMap can be used to study protocol adoption over time, monitor service availability, and help us better understand large systems distributed across the Internet. Check out our Getting Started Guide, read our Research Paper, or go and Download ZMap yourself.
Density Design | Minerva – Data visualization to support the interpretation of Kant’s work
distinct streamgraphs (steamgraph) like flow or alluvial diagrams using minerva
Citeology - Projects - Autodesk Research
Learning - Projects - Autodesk Research
Learning The Learning project aims to investigate advanced techniques for assisting users in learning complicated applications. We are interested in a range of investigations from the scientific study of the human learning process to prototyping novel interaction techniques for improving the general learning mechanisms that can be applied to all applications. One of our main observations is that the fundamental application provided learning mechanism, the "help system", has not changed much in the last 10 years or so. However, our computing environment has undergone significant changes such as: Widespread Internet usage Google searching (and indexing of vast quantities of information) Cheap video streaming (e.g., YouTube) Larger and higher resolution displays CPU/GPU speed improvements Online communities The Learning project will focus on a variety of research questions such as: Can we improve the way people learn complicated applications? Can we provide ways of capturing expert workflows and share them with colleagues by visualizing the workflows within an application? Are there ways of intelligently recommending contextually-based learning material to users based on analyzing CIP data (time-stamped command histories) reported by thousands of users and comparing that to a user's own command history? Can we visualize and detect patterns of command usage and command sequencing to help inform interface design?
How a Small Group of Entrepreneurs Transformed Government Services -
From Aneesh Chopra.
Study Report: Study Pursuant to Section 108(d) of the Sarbanes-Oxley Act of 2002 on the Adoption by the United States Financial Reporting System of a Principles-Based Accounting System
SEC Requests Financial Firms' Security Details
What's especially notable about the SEC's announcement is that the examination isn't predicated on telling businesses what to do or presenting them with a checklist. Instead, it says that maintaining correct risk-based controls is the responsibility of any individual business, and that those controls will be unique to the business. For now, the SEC wants details about what businesses are doing and why they're doing it.
Robert Haas: Why The Clock is Ticking for MongoDB
How can we improve the use of past performance in contracting? -- FCW
Managing the Digital Enterprise ® | Professor Michael Rappa
Federal Government and agency performance plans | 31 U.S. Code § 1115 -
(1) establish Federal Government performance goals to define the level of performance to be achieved during the year in which the plan is submitted and the next fiscal year for each of the Federal Government priority goals required under section 1120 (a) of this title; (2) identify the agencies, organizations, program activities, regulations, tax expenditures, policies, and other activities contributing to each Federal Government performance goal during the current fiscal year; (3) for each Federal Government performance goal, identify a lead Government official who shall be responsible for coordinating the efforts to achieve the goal; (4) establish common Federal Government performance indicators with quarterly targets to be used in measuring or assessing— (A) overall progress toward each Federal Government performance goal; and (B) the individual contribution of each agency, organization, program activity, regulation, tax expenditure, policy, and other activity identified under paragraph (2); (5) establish clearly defined quarterly milestones; and (6) identify major management challenges that are Governmentwide or crosscutting in nature and describe plans to address such challenges, including relevant performance goals, performance indicators, and milestones.
Articles * Center for Evidence Based Management
List of dozens of Evidence Based Management articles.
Envisioning Evidence-Based Management. Rousseau D.M.
Evidence-Based Management (EBMgt) is an evolution in the practice of management. It is a knowledge-intensive, capacity-building way to think, act, organize and lead. Its practice incorporates 1) use of scientific principles in decisions and management processes, 2) systematic attention to organizational facts, 3) advancements in practitioner judgment through critical thinking and decision aids that reduce bias and enable fuller use of information and 4) ethical considerations including effects on stakeholders. It is a no-fad, no-fluff approach to developing better managers and leading effective and adaptive organizations. EBMgt is a product of the distinct yet interdependent activities of practitioners, educators and scholars. This chapter discusses how each contribute to the advancement and use of EBMgt.
Evidence-Based Management in “Macro” Areas: The Case of Strategic Management
Despite its intuitive appeal, evidence-based management (EBMgt) faces unique challenges in “macro” areas such as Organization Theory and Strategy Management, which emphasize actions by organizations, and business and corporate leaders. The inherent focus on complex, multi-level and unique problems present serious challenges. EBMgt will nurture the establishment of a new model of research that is not only cumulative in its knowledge-building but also promotes engaged scholarship. Further, the uncertainty and conflict that characterize “macro” decision contexts heighten the need for EBMgt. We put forward four recommendations to advance EBMgt: (1) using more sophisticated meta-analyses; (2) providing syntheses that go beyond quantitative summaries; (3) engaging in a disciplined conversation about our implicit “levels of evidence” frameworks; and (4) developing decision supports.
Information Geographies
really neat site full of maps of information stuff
FiveThirtyEight | What the Fox Knows
Indeed, as more human behaviors are being measured, the line between the quantitative and the qualitative has blurred. I admire Brian Burke, who led the U.S. men’s hockey team on an Olympic run in 2010 and who has been an outspoken advocate for gay-rights causes in sports. But Burke said something on the hockey analytics panel at the MIT Sloan Sports Analytics Conference last month that I took issue with. He expressed concern that statistics couldn’t measure a hockey player’s perseverance. For instance, he asked, would one of his forwards retain control of the puck when Zdeno Chara, the Boston Bruins’ intimidating 6’9″ defenseman, was bearing down on him? The thing is, this is something you could measure. You could watch video of all Bruins games and record how often different forwards kept control of the puck. Soon, the NHL may install motion-tracking cameras in its arenas, as other sports leagues have done, creating a record of each player’s x- and y-coordinates throughout the game and making this data collection process much easier. I would ask a lot of questions of this data if I had it. For instance: Is it smart for a player to keep control of the puck when Chara (or a similarly gifted defensemen) has him in his sights? Might the player yield fewer turnovers if he passed the puck instead? Would measuring a player’s perseverance give us meaningful information beyond what is reflected in “box score” statistics, such as goals, assists and plus-minus? Do players who persevere under threat match those who are regarded as “tough” or as having lot of “heart” by coaches, scouts and commentators? If not, is the metric flawed, or are the coaches biased? The quality of hockey statistics is fairly poor compared to those for baseball or basketball, so I can understand Burke’s skepticism. But often, general managers and CEOs and op-ed columnists use the lack of data as an excuse to avoid having to examine their premises.
Behind the Scenes: Mountains of the Olympics - Washington Post Information Graphics
AllAnalytics - Meta S. Brown - Building a Business Case for Text Analytics
Instead of merely looking for insights, we need to identify specific business problems and use text analytics to address them. The more we know about the value of solving the problem, the better we’ll be able to define the expected benefits, and the more convincing the business case becomes. Hard benefits can come from cost savings or revenue increases. Those are the only two options.
Reddit's empire no longer founded on a flawed algorithm
"When squirrels attack! There's a medical code for that." -
Basketball analytics
Research: 2014 Analytics, BI, and Information Management Survey - InformationWeek Reports
67% are interested in using advanced analytics to improve business operations. Other data points: > 59% say data quality problems are the biggest barrier to successful analytics or BI initiatives > 35% have standardized on one or a few analytics and BI products deployed throughout the company > 44% say "predicting customer behavior" is the biggest factor driving interest in big data analysis > 47% list "expertise being scarce and expensive" as the primary concern about using big data software > 58% list "accessing relevant, timely or reliable data" as their organization's biggest impediment to success regarding information management
New Charts, Features Join the Google Visualization API
How Will Ezra Klein's 'Project X' Add Context to News? - Conor Friedersdorf - The Atlantic
Here's Jay Rosen once more (my emphasis): I noticed something in the weeks after I first listened to “The Giant Pool of Money.” I became a customer for ongoing news about the mortgage mess and the credit crisis that developed from it... ‘Twas a successful act of explanation that put me in the market for information. Before that moment I had ignored hundreds of news reports... In the normal hierarchy of journalistic achievement the most “basic” acts are reporting today’s news and providing current information, as with prices, weather reports and ball scores. We think of “analysis,” “interpretation,” and also “explanation” as higher order acts. They come after the news has been reported...
SQL Joins Explained
NY Times Taps Prof. Wiggins as Chief Data Scientist | The Fu Foundation School of Engineering & Applied Science - Columbia University
“The New York Times is creating a machine learning group to help learn from data about the content it produces and the way readers consume and navigate that content,” says Wiggins, who is also a member of Columbia’s Institute for Data Sciences and Engineering, a founding member of the University’s Center for Computational Biology and Bioinformatics (C2B2), and co-founder of hackNY. ”As a highly trafficked site with a broad diversity of typical user patterns, the New York Times has a tremendous opportunity to listen to its readers at web scale.” "Data science in general and machine learning in particular are becoming central to the way we understand our customers and improve our products," adds Marc Frons, chief information officer of The New York Times. "We're thrilled to have Chris leading that effort."
Dataset: Ten Years of NFL Plays Analyzed, Visualized, Quizzified (Downloadable) - Statwing Blog
George Mason University Updates Master’s Program for Data Science
Today's Big Data is Not Yesterday's Big Data – AnalyticBridge
todays Big data refers to "everything, quantified and tracked"
OCW Bookshelf | Open Matters
Free textbooks!
Federal senior executives growing weary and risk averse, says employee association - The Washington Post
Beth Cobert, deputy director for management at the Office of Management and Budget, said the SES “is key to our success, and [we] are actively exploring ways to best attract, develop and retain their talents. We are also exploring, as we always do, changes that can make them even more effective going forward.”
Play Anywhere® Access – Catch Media, Inc.
Osha - Charles Jeffress | A Dangerous Business | FRONTLINE | PBS
Charles Jeffress served as assistant secretary of labor for occupational safety and health during the late 1990s. In this interview, Jeffress argues that federal workplace safety laws are weak, pointing out that "to willfully violate the law and kill someone is a misdemeanor under the OSHA Act." He also explains how the theory behind the 1970 Occupational Safety and Health Act was to be preventive and assess penalties for existing hazards. However, he warns that in practice the OSHA law "has inadequate teeth" for the federal government to rein in a rogue company. This is an edited transcript of his interview with FRONTLINE, conducted on Sept. 30, 2002. OPPORTUNITY FOR DATA ANALYTICS: So if you go to OSHA's central file system in Washington and typed in Tyler Pipe, you wouldn't necessarily come up with connections to all the other plants that are related to it? No. The OSHA investigator, when they're making a determination of what penalty to issue, researches the corporate history of the company, tries to research the corporate ties of the company. If there are two different sites under different names but owned by same management, it is possible to tie the two together, which might have the impact of increasing the penalty. But in this day and age of companies operating under lots of different names and difficult to track down, we don't always tie together two subsidiaries to the same holding company. FAMILIAR TO INFORMATION TECHNOLOGY You say that, for most companies, it's good business to comply, to take care of their workers. What we've discovered, at least in one case, is that a company has all the right paperwork. They post all the signs, have the manuals, but really doesn't instruct its workers or have group meetings. Safety is considered a cost of doing business, and it's better business, apparently, to ignore it, in reality. There are companies with good programs on paper, written by some consultant some place, but never applied in the workplace. Then it's easy to tell when you walk into a workplace; within 30 minutes, you can tell whether there's attention being paid to the details that are necessary to keep people safe or not. ... But in terms of safety being a good policy or good program or safety pays -- if you account for the costs of an accident, not just the hurt to the individual, not just the payment to that family and the medical bills, but if you look at training the new workers to take its place; you look at the down time that occurs when a serious accident occurs; you look at the damage to the equipment; you look at all the time that the corporation and officers of the corporation spend reviewing the accident, trying to correct that problem -- for a good company that takes its job seriously and safety, the cost of an accident is probably 10 times the actual dollar outlay for the injured worker. There are many, many hidden aspects of an accident that a company that's doing its job pays. So when we say safety pays, when we say an investment in safety pays off, you avoid not only the cost to the individual, but you avoid all those indirect costs. Does the OSHA law adequately protect workers in the United States? No. OSHA law cannot adequately protect workers in the United States [for] a couple of reasons. One, OSHA can't be everywhere. The protection of an individual worker starts at that plant level -- that worker looking out for himself or looking out for his or her fellow employees. That's the most important thing anybody can do to running safe on the job -- have a conscious program of looking after each other. OSHA can't be everywhere any time. OSHA has to be able to give support to those employees who don't get support from their employers. When there are employers that are careless or overlook or don't give any priority to safety and health, OSHA has to be available to come in and help those employees get the employer's attention, if you will, and force action. But on a daily basis, there's no way OSHA's going to be in every workplace. ...
Moral & Political Chart of the Inhabited World (1837) (4050×2250)
historical visualization of "civilizedness" and civilization, redone with modern methods. This is awesome.
Improving the Citizen Experience: Q&A with Gail Roper - Socrata, Inc.
In a Socrata Webinar, Gail Roper, Chief Innovation Officer of Raleigh, North Carolina, shared how to leverage open data to improve citizen experience. Watch the webinar recording and read the follow-up blog to learn how your government can improve citizen experience in the coming year.
Joel Klein vs. New York City teachers : The New Yorker
She declined to say what the charges against her were or to allow her name to be used, but told me that she was there “because I’m a smart black woman.” I asked the woman for her reaction to the following statement: “If a teacher is given a chance or two chances or three chances to improve but still does not improve, there’s no excuse for that person to continue teaching. I reject a system that rewards failure and protects a person from its consequences.” “That sounds like Klein and his accountability bullshit,” she responded. “We can tell if we’re doing our jobs. We love these children.” After I told her that this was taken from a speech that President Obama made last March, she replied, “Obama wouldn’t say that if he knew the real story.”
Schumpeter: Measuring management | The Economist
Diane Rehm, 2006: Discussion of Robert Gates nomination to secdef
CIA veteran, CQ journalist, and State policy planning director They just attribute his nomination to Bush 41 trying to get things back on track, which gates rejects in "Duty"
How (Not) to Run the Pentagon - Gates, 2006
Robert Gates: A man still at war - The Washington Post
Tech Policy Is Not A Religion - InformationWeek
AllAnalytics - Meta S. Brown - Text & the City: Municipalities Discover Text Analytics
Identifying root causes is a unique value proposition for text analytics in government. It's one thing to know something happened -- a crime, a missed garbage collection, a school expulsion -- and another to understand where the problem started. Conventional data often lacks clues about causes, but text reveals a lot.
Meet the former Microsoft employee who wants to liberate liberal data - The Washington Post
"We've never had someone like Josh. He's like, in love with standards in a really bizarre way," joked Seth Bannon, the chief executive of Amicus and an OSDI partner.
Why no one uses your government data » Ben Balter
In this case, listing ID’s is just scratching the surface of what a developer might expect from the private sector. Is the API responsive? Does it return data in a usable format? Are related queries properly linked? The list goes on.
Chroma.js Color Scale Helper
A watchdog grows up: The inside story of the Consumer Financial Protection Bureau - The Washington Post
An Error Message for the Poor -
More failures in citizen services
The Information Oriented Architecture | Data Integration Blog
Analytics/Research and Data - MediaWiki
Research methods. We use a variety of methods (both quantitative and qualitative strategies, exploratory analyses, controlled experimentation, and statistical modeling) to answer research questions. Collaboration. We mostly work by embedding ourselves in the teams that we support. We believe that we work best with customers when we participate in the design process from a very early stage to identify research questions that new products or programs are designed to answer. We also support the teams we work with by advising towards best practices on instrumentation, data modeling, data visualization and the definition of key performance metrics. To determine the best approach and prioritize research questions we typically consult with program and product owners on a quarterly basis, or on a per-project basis as needed. Transparency. We strive to make the process and output of our work as transparent as possible, by publicly sharing the research reports (see the Research:Index), visualizations, code (see FIXME) and datasets (see our group) that we produce. When we publish our work in academic outlets, we make sure that the results are openly accessible to the community. Product development. We also work with the Analytics Development and the Wikimedia product and engineering teams to identify and prototype new analytics product ideas or ways to use data to improve user experience on Wikimedia sites. Outreach. We work with community members and academic researchers to spearhead Wikimedia/Wikipedia research and to evangelize open research tools and data sources. We regularly hang out on IRC in the #wikimedia-researchconnect and #wikimedia-analyticsconnect channel, where you can reach us to ask us anything about our work. We are also familiar with the scholarly literature on Wikipedia and online collaboration in general and we strive to bridge the gap between the Foundation, our editor community and the research community by participating in various outreach initiatives. Grantmaking. We support Wikimedia movement affiliates in making research-driven decisions about how to further our mission and strategic goals through grant funded projects, and how to demonstrate the impact of those projects.
Federal services: People, Not Data — Medium
Observations of why federal services need to be rethought.
Beyond Open Data: The Data-Driven City
those events are so rare, even in a city as large as New York, that it can be difficult to accurately measure the performance improvement from such a small dataset. Instead, we had to think about the leading indicators of outcomes. When we increase the speed of finding the worst of the worst by prioritizing the complaint list, we are reducing our time to respond to the most dangerous places, and we are in effect reducing the number of days that residents are living at risk. We calculated that as a reduction in fire-risk days.
How Netflix Reverse Engineered Hollywood - Alexis C. Madrigal - The Atlantic
Economic Value Added - Wikipedia, the free encyclopedia
Cool concept
K-means Clustering 86 Single Malt Scotch Whiskies
alluvial diagram - Google Search
Sankey Diagram in d3.js
Spaghetti diagrams, part 1 « Energy Literacy
Visio | Sankey Diagrams
How Y’all, Youse and You Guys Talk - Interactive Graphic -
My notes go here
Big Data excerpt: How Mike Flowers revolutionized New York’s building inspections.
Flowers was named to a special task force assigned to crunch the numbers that might unmask the villains of the subprime mortgage scandal in 2009. The unit was so successful that a year later Mayor Bloomberg asked it to expand its scope. Flowers became the city’s first “director of analytics.” His mission: to build a team of the best data scientists he could find and harness the city’s untapped troves of information to reap efficiencies covering everything and anything. Prior to the big-data analysis, inspectors followed up the complaints they deemed most dire, but only in 13 percent of cases did they find conditions severe enough to warrant a vacate order. Now they were issuing vacate orders on more than 70 percent of the buildings they inspected. Yet the most important reason for the program’s success was that it dispensed with a reliance on causation in favor of correlation. “I am not interested in causation except as it speaks to action,” explains Flowers. “Causation is for other people, and frankly it is very dicey when you start talking about causation. I don’t think there is any cause whatsoever between the day that someone files a foreclosure proceeding against a property and whether or not that place has a historic risk for a structural fire. I think it would be obtuse to think so. And nobody would actually come out and say that. They’d think, no, it’s the underlying factors. But I don’t want to even get into that. I need a specific data point that I have access to, and tell me its significance. If it’s significant, then we’ll act on it. If not, then we won’t. You know, we have real problems to solve. I can’t dick around, frankly, thinking about other things like causation right now.”
Michael flowers | The White House
Sapping Attention: Reading digital sources: a case study in ship's logs
Dutch East India Company - Wikipedia, the free encyclopedia
By 1669, the VOC was the richest private company the world had ever seen, with over 150 merchant ships, 40 warships, 50,000 employees, a private army of 10,000 soldiers, and a dividend payment of 40% on the original investment.
Political polarization of the U.S. Senate: Is the data fooling us? | Randal S. Olson
This explores critical analysis of data visualizations and identifies cautionaries warnings about cherry picking and distortions.
Military Innovation and Carrier Aviation
Big Data: New Tricks for Econometrics
by Hal Varian
Ekisto: motivation, goals, algorithmic and design challenges - Ekisto: motivation, goals, algorithmic and design challenges - processq
description of the github and stackoverflow "as cities" visualization
Mayor Bloomberg’s Geek Squad -
Do You Need a Data Scientist?
Do you need a data scientist? - Strata
The Pyramid of Data Science - Data Community DC
Speaker Slides and Video: Strata 2013 - O'Reilly Conferences, February 26 - 28, 2013, Santa Clara, CA
How the Obama campaign won the race for voter data
One of the hallmarks of Obama’s 2012 campaign was its prodigious appetite for research. The trio at the top — Messina, senior strategist David Axelrod and White House senior adviser David Plouffe — were enthusiastic consumers of research. Though different in their approaches to politics — Axelrod operated intuitively, Plouffe’s watchwords were “Prove it” and Messina wanted to be able to measure everything — they all pushed the campaign for more research, testing, analysis and innovation. We did a very detailed postmortem where we looked at all kinds of numbers, looking at the general stuff like the number of door knocks we made, phone calls we made, number of voters that we registered,” said Mitch Stewart, who would direct the campaign’s 2012 effort in battleground states. “But then we broke it down by field organizer, we broke it down then by volunteer. We looked at the best way or the best examples in states of what their volunteer organization looked like
10 Things You Can Learn From the New York Times’ Data Visualizations | Blog
Adapting To A Responsive Design (Case Study) | Smashing Mobile
nForm / Trading Cards / Customer Research, Information Architecture, Interaction Design, Usability, User Experience
User experience trading cards. Created for the IA Summit in 2007, 2008 and 2009.
The Anatomy of an Experience Map - Adaptive Path
The experience map highlighted above was part of an overall initiative for Rail Europe, Inc., a US distributor that offers North American travelers a single place to book rail tickets and passes throughout Europe, instead of going to numerous websites. They already had a good website and an award-winning contact center, but they wanted to get a better handle on their customers’ journeys across all touchpoints, which would allow them to more fully understand where they should focus their budget, design and technology resources. Derived from this overall “diagnostic” evaluation, of which the map was just one part, were a number of recommendations for focused initiatives. The experience map helped create a shared empathic understanding of the customers' interactions with the Rail Europe touchpoints over time and space. I almost always apply five critical components that make an experience map useful. And when I say useful, I'm thinking of two key criteria: First, it can stand on its own, meaning it can be circulated across an organization and doesn't need to be explained, framed or qualified. Like others, we make our experience maps large, often greater than five feet long. They're meant to engender a shared reference of the experience, consensus of the good and the bad. Second, it's clearly a means to something actionable—ideally something to design around—and not an end in and of itself. A good experience map feels like a catalyst, not a conclusion.
IT dashboards: Picture perfect? -- FCW
Analytics Blog: Universal Analytics Business Applications
Analytics (still limited to customer domain) Our team designed an experiment to dive into Universal Analytics by creating interactive scenarios inside ourour Google Analytics dashboard We integrated sensors and RFID readers to capture data about coffee and tea making behaviour in our office. We also measured each time the fridge was opened, when one of our team updated a support ticket, client hours were logged, code was committed, administrative tasks, and viewing of
I Got 200 Million Problems, But Multicollinearity Ain't One
A Cloudless Atlas — How MapBox Aims to Make the World's 'Most Beautiful Map' | Wired Design |
Data “When it comes to open government, there’s all this talk of APIs. What wereally need is government infrastructure for bulk download.”
MIT Data Warehouse
Reports with the symbol (standard reports) have been tested by a group of central and departmental users who have checked that the numbers in the report reliably tie out to SAP. Reports without a symbol (user reports) have been reviewed by the Data Warehouse team and approved for posting on the web, but have not been through a formal testing process.
LESSON - Data Warehouse Alternatives: Seven Data Integration Options for BI Solutions -- TDWI -The Data Warehousing Institute
. Enterprise Information Integration (EI ) Enterprise information integration (EII) refers to the real-time aggregation of data across multiple data sources. EII solutions present distributed data as if it exists in a single location. This distinguishes EII from other types of data access technologies, since data is not permanently moved or replicated into a new location or database. The source data remains intact.
Ten Questions That USASpending.Gov Can’t Answer
Recurring Developments
“Designing for Behavior Change” – New O’Reilly Title Coming from Local Data Community Member
Data Community Member* http:// <><> /k/12rVg5K <> Analytics design *This guest post is by **Steve *<> *Wendel* <>*,*<> * “a behavioral social scientist and simulation modeling expert” at ** HelloWallet** who has been a strong supporter of Data Community DC since the beginning.* I’m happy to announce that O’Reilly Media will be publishing a new book I’m writing called *Designing for Behavior Change*. The book gives step-by-step guidance on how to design, build, and test products that help people change their daily behavior and routines. The goal is to help people take actions that they want to take, but have struggled with in the past: from exercising more (FitBit, Fuelband), to spending less on utilities (Opower, Nest), to taking control of their finances (HelloWallet). It’s a practical how-to book, aimed at designers, product folks, data scientists, entrepreneurs and others who are thinking about and building these products. It includes: Insight into how the mind makes decisions, and what that means for changing behavior. Step-by-step instructions on how to select a behavioral change strategy, and convert that strategy into a real product. Techniques and software tools for evaluating the concrete impact of a product on user behavior, and for discovering the factors that block users from changing their behavior. Lots of practical, concrete examples. For those of you who have been reading my blog for a while, it covers some of the same topics (how to sustain engagement with a product, how to overcome existing habits, etc), but in much greater depth, and with an overall framework to make sense of the product development process. The book draws from our experiences here at HelloWallet over the last four years, and well as from the dozens of companies I’ve had the joy of talking with through the Action Design DC Meetup<>, and mentoring companies at The Fort<>and 1776 DC <>. *If **you’d** like a free copy of the draft **eBook*, just sign up for my email newsletter here <> (http://<> <>/ <>tJfgz<>). I’ll send out draft chapters as they become ready, and blog posts on related topics. I look forward to your feedback! I’d also love to hear about interesting case studies and examples of companies doing this work. -Steve <> The post “Designing for Behavior Change” – New <>O’Reilly<>Title Coming from Local Data Community Member<>appeared first on Data Community DC <>.
Moving Beyond Basecamp: Managing Company Growing Pains - DROdio
Asana: How will Asana's main product be different than Basecamp? - Quora
Asana - Dan DeMeyere
Re: Fwd: How to Tell a Story with Data
Should Martin O’Malley Be President?
What we need in the next president, in other words, is not just creative policy-making and politicking, but a willingness to drive the bureaucracy to perform. He or she must have a passion for managing the government itself. It’s a tough order to fill. Considering the growing complexity and size of both the federal government and the challenges it has been asked to address, many would characterize it as Sisyphean. But fortunately, over the last couple of decades, through trial and error, new systems of goal setting, data gathering, and accountability have been developed in the public sector that attempt to give elected officials some of the same tools corporate leaders use to demand bottom-line results from their organizations. These new accountability systems are hardly panaceas; in fact, they have disappointed more often than they have succeeded. But it just so happens that the politician who is most broadly recognized to have made them work the best is none other than Maryland Governor Martin O’Malley.
The tradeoffs of simplicity, Obamacare edition
The government is spending way more on disaster relief than anybody thought
No one even knew, not FEMA, not OMB
From big data to better decisions -- FCW
Census: Data Visualization Gallery
Open Data Has Little Value If People Can't Use It - Craig Hammer - Harvard Business Review
Mayor Bloomberg’s Geek Squad -
List of HTML5 Charts by sunilurs - Kippt
VIsual Guide to the Federal Reserve
Teaching Smart People How to Learn
on the knowledge worker, 1991
Next Generation of API Driven Analytics and Visualizations
Rackspace Slashes Prices, Taunts Amazon | Wired Enterprise |
Knight Foundation gives $985K grant to TED
Over-the-top quantified self
automatic logging of outlook and google calendar
N.Y.U. Center Develops a ‘Science of Cities’ -
Managing cities like SimCity
A brief history of the Chinese growth model
» The Great Shift in Japanese Pop Culture – Part One:: Néojaponisme » Blog Archive
Bitter Pill: Why Medical Bills Are Killing Us |
ITIM: A Framework for Assessing and Improving Process Maturity
GAO report from 2004 on maturity models
Stakeholder-facing analytics | DBMS 2
Stakeholder-facing analytics
NYT: The Philosophy of Data
Open Programming: Free coding books
data products
Will the Chief Innovation Officer Transform Government?
d3.js bibliography & tutorials
Learning PHP, MySQL, JavaScript, and CSS, 2nd Edition - O'Reilly Media
HTML5 and JavaScript Web Apps - O'Reilly Media
UX/UI Bibliography - O'Reilly Media
NYT: Fred Kaplan&apos;s &apos;Insurgents,&apos; on
Nathan Heller: The Twentysomethings Are All Right : The New Yorker
Wonkblog's books of 2012
“Buying Our Boys Back”: The Mass Foundations of Fiscal Citizenship in World War II | ResearchGate
POQ idealism and war bonds
We don’t need more data scientists — just make big data easier to use — Tech News and Analysis
Kludgeocracy: The American Way of Policy
Stevey's Google Platforms Rant -
Includes story of Jeff Bezos services-first policy at Amazon
A Baseline for Front-End Developers - Adventures in JavaScript Development
Ontology Tutorial
The Entebbe Option - By Mark Perry | Foreign Policy
Gartner: Do you have a Chief Digital Officer? You’re gonna need one
The Rise of the Chief Digital Officer | Russell Reynolds Associates
Fantastic Information Architecture and Data Visualization Resources - noupe
Analytics - What's On Your Dashboard? -- FCW
FCW review of IT Dashboard, PortfolioStat, and Evidence Based Management.
Big Data Tradeoffs: What Agencies Need To Know - NIST's Peter Mell
What did the study of the Soviet economy contribute to mainstream economics?
From Data to Decisions II: Building an Analytics Culture
Memos to National Leaders | Memos to National Leaders
Strengthening the Federal Budget Process Rationalizing the Inter-Governmental System Administrative Leadership Strengthening the Federal Workforce Reorganization of Government Information and Transparency Managing Big Initiatives Next Steps in Improving Performance Managing Large Task Public-Private Partnerships
who stole the American dream
Overview | Pew Internet & American Life Project
Facilitating Decision Choices with Cascading Consequences in Interdependent Networks
The Influence of Organizational Structure On Software Quality: An Empirical Case Study - Microsoft Research
The Mystery of Werner Herzog: Two Video Essays and One Text Essay | Press Play
Interview: NFL Replacement Referee Jerry Frump on Refs and the Lockout | Keeping Score |
The Five Competitive Forces That Shape Strategy - Harvard Business Review
is there room to make a five-forces model for government organizations behavior?
Table of contents - Harvard Business Review
Can You Live Without a Data Scientist? - Tom Davenport - Harvard Business Review
Data Scientist: The Sexiest Job of the 21st Century - Harvard Business Review
Hafslund SESAM - Semantic integration in practice
Measuring and Improving the Readability of Network Visualizations
A Very Short History of Big Data | What's The Big Data?
Deloitte Review | A Delicate Balance | Organizational barriers to evidence-based management | James Guszcza | John Lucker
MIT lecture notes: 15-320-strategic-organizational-design: what is changing
MIT OpenCourseWare | Civil and Environmental Engineering | 1.040 Project Management, Spring 2009 | Readings
Readings on project management.
Frontinus—A project manager from the Roman Empire era - Walker - 2011 - Project Management Journal - Wiley Online Library
The Early Middle Ages, 284--1000 with Paul Freedman - YouTube
Building data science teams - O'Reilly Radar
Consider downloading the whole report.
NoSQL & Big Data Analytics: History, Hype, Opportunities
Data Scientist Summit 2011 | Greenplum
Posted lectures from 2011 event.
Analytics and Data Mining Industry Overview
Greenplum: Data Science Summit (Las Vegas)
Six Keywords in the History of Analytics
December 2010
Big Data Initiative Or Big Government Boondoggle? - Software - Information Management - Informationweek
Criticism of White House big data initiative
Big Data is a Big Deal | The White House
See also: Factsheet: Press Release:
data science an action plan (2001)
How to harness big data for improving public health | Government Health IT
U.S. charges more than 100 for Medicare fraud schemes : The Fiscal Times
Splunk: Big Data Machine for Operational Intelligence | SmartData Collective
An Analytics Story Problem: When will two trains collide? | SmartData Collective
Make Data Work Throughout Your Organization - Thomas C. Redman and David Walker - Harvard Business Review
Build "data to discovery to dollars" processes
Building Data Discovery into Your Organization - Thomas C. Redman - Harvard Business Review
the non-tablet that changed the world
A Very Short History of Data Science | What's The Big Data?
The Future of BI in Two Words | SmartData Collective
Six degrees of aggregation : CJR
Example of Huffington Post as a concrete result of analytically thinking through an abstract opportunity environment. So eager was AOL to boost its content-driven traffic that in late 2010 it devised a strategy, The AOL Way. Management set markers: Monthly story production rate was to rise from 33,000 to 55,000, video from 4 percent of the content to 70 percent. All staffers were to write between five and 10 stories a day. To help them make those numbers, AOL produced a 60-page handbook filled with graphs, content flow charts, and such exhortations as “Each article should be profitable and generate at least 7k PVs/story.” Editors were to “Identify High-Demand Topics”; guidelines were provided to “breaking, seasonal, and evergreen.” Editors were commanded to calculate a story’s “profitability consideration.” “Site leaders” were expected to have on hand no less than eight packages that could produce $1 million in revenue. One employee anonymously told Business Insider, which broke the story, “AOL is the most fucked-up, bullshit company on earth.” The AOL Way was, with apologies to Maimondes, “a guide for the perplexed.” In 2010, HuffPost decided to reward its most engaged readers with three “badges” that signify the extent of that engagement: “networkers,” who draw fans and followers; “superusers,” who share often on Facebook and Twitter and who also comment frequently; and “moderators” who, in recognition of their keen eye and absorption of the site’s ethos, are trusted with deleting comments they judge inappropriate.
Assessment & Accountability -- THE Journal
The rest of the THE Journal looks like an industry trade magazine about devices. This topic area (Assessment & Accountability) focuses on articles of more interest to my area.
TIES 2011 EdTech Conference: Schedule
Education technology: school data-driven decision-making resources
List of links from Minnesota TIES, including Federally-funding centers.
Manage Your Human Sigma - Harvard Business Review
The core message: There is a big difference in behavior between customers that are "rationally" satisfied with a company and those that are "emotionally" satisfied--and those differences in behavior translate into huge differences in loyalty and profitability.
Getting on the Same Page: Dashboard Development from Planning to Implementation | Cutter Consortium
2006. Distinction between automobile dashboard versus aircraft navigation system. Emphasizes predictive and "where you are going" aspects of successful dashboards. They proceeded to show us a number of reports from the current "dashboard," which essentially reported on project status for ongoing projects. While the graphs, widgets, and colored diagrams were impressive to look at, closer examination revealed that all of the data consisted of "lagging indicators." Many of the critical items that we had explored in our planning were not included at all. Beyond the missing leading indicators, how would this dashboard report on the progress toward their goals? Where was the critical item of "value"? Where did key compliance issues (e.g., Sarbanes-Oxley, CMM®, various quality initiatives) fit in, since these weren't really projects? We also knew that certain key items (e.g., project charters, specifications) were going to be most indicative of success or failure. Yet these were at best binary measures -- they were complete or not. In fact, a project didn't hit the "radar" until the charter was completed, so this critical step might not even be reflected in their existing dashboard. In the simulation, we had painstakingly mapped a number of assumptions and external factors. A key one was how fast they could acquire, train, and deploy additional resources. Was the resource factor included in the dashboard? Not really -- it showed nothing beyond the amount of these resources that had been consumed at a given point. We believe that most often questions about data accuracy, data completeness, or historical data are red herrings. When we start arguing about the precision of metrics, we frequently find we have the wrong measures or the wrong presentation, or we are dealing with resistance that has nothing to do with the accuracy of the numbers. Measurement is supposed to make you uncomfortable. Questioning the accuracy of the numbers is how some people vent that discomfort. Remember the IT department client we mentioned above? When we began replacing their plethora of spreadsheets with a version of the planning module we outlined earlier, we cautioned the consultant who was working on the model to remain calm when (not if) the accuracy of the data was attacked. Very early into a meeting on the new model, one of the participants began vigorously comparing our data to her spreadsheet and pointing out a series of minor discrepancies. The behavior was disruptive, but because we were prepared for this resistance, we stayed calm and didn't get into a defensive position or an argument. We quietly pointed out that the discrepancies were there because we were all working from a number of unrelated spreadsheets. Prepare for arguments about data. Agree on the margin of error and what you will do about inaccuracies. Do this before you show your data or the results. Even then, beware the smokescreen and anticipate resistance. Metrics hold up a mirror, and the picture we see isn't always flattering. It can get emotional. Remember, if your metrics aren't making someone uncomfortable, they probably aren't the right metrics. On the other hand, beware the homegrown Excel wizard. We've seen some systems built with a proliferation of spreadsheets, and while they appeared to be "money savers" at first, they ultimately cost more than the value they delivered. Often they were delivered quickly, but many were built on a house of cards -- undocumented macros that delivered results no one could justify. Even if you found the error, the safest presumption was that you'd never be able to fix it without rewriting the whole spreadsheet. That may sound extreme, but it's far more common than you might think.
Thomas Goetz: It's time to redesign medical data | Video on
Google Research: Excellent Papers for 2011 | Research Blog Technology Context Reviews Evals and Assessments
Government Data and the Invisible Hand by David Robinson, Harlan Yu, William Zeller, Edward Felten :: SSRN
Innovation for the People, by the People
Big data: The next frontier for innovation, competition, and productivity | McKinsey Global Institute | Technology & Innovation | McKinsey & Company
Matching Text with ngramms
tf*idf - Wikipedia, the free encyclopedia
Corpus Resources
Links to English corpus and corpera
LIWC: Linguistic Inquiry and Word Count
dictionary of sentiment categories for computational linguistics
Big Data, Big Impact: New Possibilities for International Development | World Economic Forum-Big Data, Big Impact: New Possibilities for International Development
Big Data’s Impact in the World -
n+1: White Oak Denim, Greensboro
The Greatest Books of All Time, as Voted by 125 Famous Authors - Maria Popova - Entertainment - The Atlantic
McKinsey Classics: Corporate strategy for turbulent times
Five low-profile startups that could change the face of big data — Cloud Computing News
Peter Robinett - Quantifiying productivity on Vimeo
MIT: Building a Well-Networked Organization
Leading from the Middle: The Power and Influence of Middle Leaders
The 'Trophy Kids' Go to Work -
Leading Change: Why Transformation Efforts Fail
John Kotter.
15.320 Strategic Organizational Design
15.317 Organizational Leadership and Change
Radian6 - text analysis service
Anderson Analytics OdinText - text analysis
The Affordable Care Act - Implementation Timeline | The White House
Federal_Health_Information_Technology_Strategic_Plan_2011-2015.pdf (application/pdf Object)
Predicting the Present with Google Trends
Revealed Preference and its Applications
Hal Varian on how the Web challenges managers (free)
The Middle Aging of New Public Management: Into the Age of Paradox?
Connecting the Dots in Public Management: Political Environment, Organizational Goal Ambiguity, and the Public Manager's Role Ambiguity
Goal Ambiguity in U.S. Federal Agencies
Is Hierarchical Governance in Decline? Evidence from Empirical Research
Third-Party Governance under No Child Left Behind: Accountability and Performance Management Challenges
CS 7450 - Information Visualization - Syllabus
Georgia Tech information visualization course.
Jnl. of Public Admin. Research and Theory | JPART Reader
Highlighted articles over the last 15 years for free.
The Economics of Internet Markets
The Impact of Information Technology on Consumer Lending
What is middle class about the middle classes around the world?
Incentives Work: Getting Teachers to Come to School
The miracle of micro…nance? Evidence from a randomized evaluation
The Evolution of Top Incomes: A Historical and International Perspective
Inequality at Work: The E ect of Peer Salaries on Job Satisfaction
The World Top Incomes Database - G-MonD, PSE-Paris School of Economics
Single crossing properties and the existence of pure strategy equilibria in games of incomplete information
How Large Are Human-Capital Externalities? Evidence from Compulsory Schooling Laws
The labor market and corporate structure
The Rise of Europe: Atlantic Trade, Institutional Change and Economic Growth
Central government and frontline performance improvement: The case of "targets" in the UK