Policy by the Numbers: Weekly Roundup

This Week in Data: 11/30/2012

Friday, November 30, 2012

A new report from Nesta, "Rise of the Datavores," looks at data-driven decisionmaking among a group of UK businesses. The paper "illustrates both the opportunities and challenges that online data presents for UK businesses."

An article in the Wall Street Journal on Thursday introduced us to Amanda Hubbard, who is about to lose access to data generated by the heart defibrillator implant in her chest because of regulations around health data. Hubbard currently gets information on the device via her doctor, but is on the verge of losing her insurance. However, the manufacturer of the implant, Medtronic, cannot provide data from the implant directly to Hubbard. From the article:

Medtronic says federal rules prohibit giving Ms. Hubbard's data to anyone but her doctor and hospital. "Our customers are physicians and hospitals," said Elizabeth Hoff, general manager of Medtronic's data business. Medtronic would need regulatory approval to give patients the data, she said. It hasn't sought approval because "we don't have this massive demand."

Over on Harvard Business Review blogs, NYU ITP professor and New York Times Data Artist in Residence Jeff Thorp turns a critical eye to the overused "data is the new oil" metaphor, and urges us re-frame data in a human context. Part of making data more human means engaging the artistic community in data-driven culture. "As we proceed towards profit and progress with data, let us encourage artists, novelists, performers and poets to take an active role in the conversation," he writes. "In doing so we may avoid some of the mistakes that we made with the old oil."

This Week in Data: 11/16/2012

Friday, November 16, 2012

Highlights of the week's stories about all things data.

In a piece on GigaOm, Ki Mae Heussner looks at tools that help normal people tap into the network of medical peer reviews—that is, find out what doctors come highly recommended by other doctors. Heussner writes, "By accessing information in government databases through FOIA (Freedom of Information Act) requests, healthcare innovators are now able to share connections between doctors that are based on millions of physician referrals—a valuable indicator of who doctors hold in esteem."

On Freedom to Tinker, UNC's Zeynep Tufekci reflects on her New York Times op-ed, "Beware the Smart Campaign." Tufekci's op-ed, and accompanying blog post, argues that the combination of data analytics and social science to assign numbers and corresponding messaging to voting groups threatens public discourse. But posits that data-driven campaigning isn't bad—it just requires transparency to keep public discourse open:

What is to be done? Campaigns should make public every outreach message so we at least know what they are saying. These messages can be placed in a public database like campaign contributions so the other side can be aware of, and have the right to respond to, false claims. Political access to proprietary databases should be regulated to provide an even playing field.

On Wired, Chartio's Dave Fowler urges entities trying to derive insight from data through analysis to forget "big data" and focus on their data. He pleads:

“Big data” is an impressive buzzword, but don’t get caught up in that. Let’s leave it to the journalists, researchers and marketing departments to tell us what the big data market is. Instead, focus on understanding your data. Your data is much more powerful than big data; in fact, it’s the only data you truly care about.

This Week in Data: 11/9/2012

Friday, November 9, 2012

Highlights from the week in data!

US Census Bureau's Acting Director Tom Mesenbourg wrote a great post yesterday about the things Census can tell us about communities impacted by Hurricane Sandy, featuring an interactive tool for crisis response called OnTheMap for Emergency Management. Tom writes:

This tool traced the path of Hurricane Sandy starting on October 22. As the predictions about the Storm’s path changed, data on potential impacts were automatically updated. This innovative tool provides information about the potentially affected population, the kinds of businesses impacted by a natural disaster, and the number and characteristics of workers, as well as where they live. You can use it to look at statistics for declared disaster areas and learn about things like the impacted industries, the ages of workers and workers’ earnings. These statistics can be used by communities to know not only how many people live in an area where there is a disaster but also how many people work in those areas.

Michael Scherer's Time piece on the data analysts working on Obama's campaign, "Inside the Secret World of the Data Crunchers Who Helped Obama Win," is worth highlighting because it is a great profile of data scientists and the use of data-mining for strategic campaign planning.

Boston.com's Michael Morisy reflects on Nate Silver, strategy, and the future societal benefits that we hope to enable via data-driven innovation. He writes, "To me, that’s the really exciting impact of big data: Not to determine whether you should end subject lines with more colons, but to determine how to transform medicine, cities, and societies."

This Week in Data: 11/2/2012

Friday, November 2, 2012

Happy Friday! A few highlights this week.

Derek Harris at GigaOm highlighted some of the ways companies used their tools to provide emergency information for people in areas impacted by Hurricane Sandy, including Google's crisis response map.

AdWeek's Christopher Heine takes a look at the term "big data" and its implications for businesses.

Health Policy Solutions, affiliated with Colorado University's School of Public Affairs, posted an opinion piece on the Colorado Health Institute's push for data-driven health policy. Michele Lueck covers five health care trends that are informed by data and aimed at transforming Colorado's health care system.

These Weeks in Data: 10/19/2012 & 10/26/2012

Friday, October 26, 2012

We didn't post a roundup last Friday due to mitigating circumstances (sorry!), so this week's roundup covers the last two weeks.

O'Reilly data guru Alex Howard writes about revisions to San Francisco's open data legislation aimed at putting more resources into the already vibrant innovation economy around the city's open data. The legislation would create a chief data officer in the mayor's office to facilitate data sharing and data-driven decisionmaking.

Thomas Davenport, Paul Barth and Randy Bean write for MIT Sloan Management review about how "big data" is different from traditional data processing and analytics in enterprise. Frankly, though, their argument only underscores a shift in the way we approach and derive insight from big data, not just its size—that is, the most disruptive aspect of "big data" is the innovation it drives in how we gather, analyze, and utilize data across domains and disciplines.

Google Research conducted an interview with Google statistician Rachel Schutt about data science inside and outside of Google. An excerpt:

R@G: What important problem would you like to see solved with data?
RS: I’d like my beautiful, smart, non-verbal, (severely) autistic brother, Alex, to be taken seriously as the intelligent human being he is and to be given the opportunity to speak. One day, Data Scientists could solve this. Generally I want to see data being used to solve problems of social value.

Writing for The Atlantic, Arizona State University student Jathan Sadowski makes a great case for the reinstatement of the Office of Technology Assessment, a Congressional agency defunded by Newt Gingrich in the 90s. Sathan writes:

The OTA holds an important place in history and as technology becomes increasingly complex, socially embedded, and wrapped up in policy we should look to it for lessons about how to apply these techniques in the present and future.

If you want to learn more about the OTA, Princeton maintains a fantastic OTA resource, with an electronic archive of the Office's publications. Also worth a read is Chris Mooney's article from the Bulletin for Atomic Scientists in 2005 that Sathan links to, "Requiem for an Office

This Week in Data: 10/12/2012

Friday, October 12, 2012

Last week, Code for America held its 2012 summit in San Francisco. Anthony Townsend, Research Director at Institute for the Future, delivered one of the Day 3 keynotes on the concept of "smart cities" and how technology is changing the urban landscape—and the importance of engaging the citizenry in effectively designing, selecting, and implementing technology in planning cities.

On ReadWriteWeb, Brian Proffitt writes about increasing demand across business sectors for professionals with data science skills. Explaining a flurry of job postings seeking MATLAB and business skills in one individual, Proffitt writes, "The meshing of technology and business skills is a big "get" for most businesses, as any geek who can speak numbers or any suit who can grok tech is highly sought candidates."

Over at The Atlantic, Betty Morais tells the story behind publishing start-up "Colliloquy," calling it a "choose-your-own-adventure model for the data-tracking age." The narrative in each book comes with multiple "pathways" for readers to make decisions about the direction of the plotline. Colliloquy records reader choices and provide that data to authors, who can make decisions about future installments of their book series based on reader feedback. Really interesting example of data-driven innovation in an industry where we don't often talk about data's potential!

This Week in Data: 10/5/2012

Friday, October 5, 2012

Here's our highlight of articles, reports, and more from the data-driven world!

In case you missed our post yesterday, the OECD released their 2012 Internet Economy Outlook—and the outlook is quite good.

Every hype cycle reaches a point where people start to forecast the death of said hyped item or term, and "Big Data" is no exception. Writing for Forbes this week, Michael Phelan argues that within a few years, "Big Data" will die and we'll realize it's all about "Any Data."

On Wednesday, TechAmerica Foundation's Big Data Commission released a new report, "Demystifying Big Data: A Practical Guide to Transforming the Business of Government" In light of Phelan's commentary, it may be useful to think about the Commission's research as work on data-driven policymaking and data-driven governance.

This Week in Data: 9/28/2012

Friday, September 28, 2012

In case you follow them, our apologies for not posting weekly highlights last Friday! Our blog editor was indisposed. But we're back this week with double the highlights to make up for it!

Bryce Maddock, CEO of TaskUs examines the human side of data analysis for Huffington Post—and does so quite persuasively, emphasizing the importance of data scientists, social scientists, and users in generating and making sense of data. It's easy to get swept up in talk of automation and supercomputing, and Maddock reminds us, "Humans are not an important part of utilizing new data, they are single most important part of the process."

Meanwhile, for a different take on the human side of data, check out the Sketchnotes Sacha Chua posted from the 2012 Quantified Self conference at Stanford, September 15-16: Opening plenary day 1, opening plenary day 2, day 1 and 2 ignite talks, and Kevin Kelly's closing plenary.

And one more human take on data-driven innovation, this one from Klint Finley at Wired: "Why Everyone (Not Just Geeks) Should Care About Big Data." Finley's piece is a nice preview of Rick Smolan's Human Face of Big Data project, which we included in our roundup two weeks ago.

InformationWeek editor-at-large Charles Babcock critiques a New York Times article that raises doubts about the eco-friendliness of data centers, thus casting a negative shadow on cloud computing in general. Babcocks unpacks and refutes many of the article's claims, like the Power Utility Efficiency ratios of modern data centers versus used for cloud computing versus those built long ago for enterprise purposes. Babcock's main criticism of the NYT piece is that it conflates these two kinds of data centers, which have wildly different composition and functions.

Finally, Derrick Harris at GigaOM writes about Disney's scrappy "big data" platform development, a great example of a Fortune 500 company harnessing data-driven innovation more like a startup.

This Week in Data: 9/14/2012

Friday, September 14, 2012

A couple months ago, Francisca Rojas from Harvard's Transparency Policy Project guest blogged about transit data. Last month, they released a study titled "Transit Transparency: Effective Disclosure Through Open Data," which "examines the process by which some transit agencies in the U.S. disclosed their operations data to the public and analyzes how constituencies for that data, particularly software developers and transit riders, used that information."

Photographer Rick Smolan, creator of the "Day in the Life" series, has set out to show how data-driven innovation is changing our world. From AllThingsD:

His new 7.5-pound book, “The Human Face of Big Data,” includes vignettes about wirelessly sensing disproportionate electricity and water consumption by individual home appliances, restoring human sight with a pair of computer eyeglasses that analyze light and other input in real-time, predicting repeat heart attacks by screening large samples of patients’ EKG data, and taking personal health tracking to the extreme. It will be released Nov. 20.

Not one for a single-media experience, Smolan has added a participatory angle via an app that collects information from users and their devices and compares them to other app users around the world, a sort of game of digital doppelganger. The app will be available September 25 through October 2.

If you want to get updates on new posts in your social media streams, follow us on Twitter @policybynumbers and Google+.

This Week in Data: 9/7/2012

Friday, September 7, 2012

Short week in the US means shortage of good news stories from the world of data. So in order to provide a list of interesting links, we've mined Google Scholar for a few scholarly pieces on data that have been published this year.

University of Pennsylvania Professor Francis Diebold has written a short paper claiming to be the first to use the term "Big Data" in an academic paper. The tone of the piece, "I Coined the Term 'Big Data'", is rather tongue-in-cheek at times, but the claim itself is (mostly) sincere. So in case you were wondering where the buzzword came from, here is an answer.

Late last year, Nokia Research Center Lausanne and partner academics in Switzerland teamed up to release data collected from 200 participants' cell phones over the course of more than a year. They couched the dataset release in a Mobile Data Challenge where registrants had the opportunity to use the data, and sponsored a subsequent workshop for the top submissions in June. Nokia Research has since published an overview of the project, "The Mobile Data Challenge: Big Data for Mobile Computing Research", that summarizes the project's goals and outcomes:

Already so far the Mobile Data Challenge has produced interesting ndings and multidisciplinary scienti c advances. The contributions to the MDC addressed various interesting angles from the perspective of mobile computing research, like investigations on predictability of human behavior patterns or opportunities to share/capture data based on human mobility, visualization techniques for complex data as well as correlation between human behavior and external environmental variables (like weather). The materials presented in the MDC workshop are available in [4]. Momentum around the interesting research resources described in this paper is expected to continue and expand also after the Mobile Data Challenge itself. Our intention is to maintain summary at least of the most important LDCC and MDC originated research outcomes in [4] also in the future.

[4] http://research.nokia.com/page/12000

This Week in Data: 8/31/2012

Friday, August 31, 2012

Ending August with a final look back at the week in data news.

Matt Fates of Ascent Venture Partners writing for the Boston Globe talks about how data-driven innovation can boost the economy of Massachusetts, especially given the governor's "Big Data Initiative." Fates explains, though, that extracting the benefits means more than just having "big data"—it's about the innovation and the insight that we derive from it:

In order for magic to happen, Big Data firms need to adopt a different mindset and step into the shoes of the organizations they sell to. They need to not only be able to provide or collect the data, they need to make it relevant to potential enterprise clients and explain why it all matters. They need to help retailers and banks, for example, understand how bits and bytes can make them more responsive to customers or help them adapt to market conditions in real time.

This necessary shift – from being able to develop technology to being able to convince corporations of its value – is essential and especially difficult for entrepreneurs who may have been trained as engineers. The technology is critical, but it must translate into complete solutions to gain adoption.

Forbes' Dave Einstein wrote about social networks' plans to use content posted by users to predict in real time the outcome of the 2012 US presidential election. But the author cautions that the portion of the electorate who uses social networks is not a representative sample of the electorate at large, likening the split to an example from American Presidential Elections past:

...Social networks tend to skew toward an upscale, younger demographic, and they skirt lower-class neighborhoods like tourists in Las Vegas who never leave the Strip. Put another way, the elderly women in Philadelphia who doesn’t have a photo ID also probably doesn’t tweet much or contribute to the 15 terabytes of new information on Facebook every day.

In fact, technology can be a two-edged sword. Remember the 1948 election, when the polls predicted a Dewey landslide over Truman? That election marked the first time pollsters relied on telephone surveys, giving them access to more voters—big data back then. It turned out that a lot of Truman supporters didn’t have phones. A parallel exists today: a growing number of U.S. households rely on cell phones instead of landlines, and pollsters don’t have access to most cell phone numbers.

Despite the drawbacks, it's certainly going to provide a really interesting perspective on at least how a subset of the US electorate thinks and feels about the election.

This Week in Data: 8/24/2012

Friday, August 24, 2012

Fresh Water, a Cleveland-based e-magazines that covers happenings in Northeast Ohio, highlighted a project at Case Western University's Center on Urban Poverty and Community Development called NEO CANDO.

NEO CANDO, a publicly accessible database, provides one-stop-shopping for anyone looking to research property information in their neighborhood. The site allows users to go beyond researching individual properties and look at snapshots of neighborhoods—including which properties are at risk of foreclosure and which have been condemned. The site also contains social, economic and census data.

The site is a resource for public officials, academics, and residents alike to understand trends in local communities.

On Computerworld, Sean Chai, Kaiser Permanente's director of innovation technology for the Innovation & Advanced Technology Team, discusses the social and data-driven direction for innovation in the healthcare sector. Social data is becoming an increasingly important source of information for patients and for professionals. He writes:

According to a recent Pricewaterhouse Coopers survey, about 33 percent of U.S. consumers use social media websites like Facebook and Twitter to obtain health information and track/share symptoms. Seventy-two percent of respondents said they would use social media sites for scheduling physician appointments, and 42 percent of respondents reported they have used social media to look up consumer reviews of health treatments or physicians.

This week, the White House announced its first group of Presidential Innovation Fellows. A subgroup of fellows will be working on the White House Open Data Initiatives, meant to "accelerate and expand Administration efforts to make government data more publicly accessible in 'computer-readable' form and spur the use of those data by entrepreneurs as fuel for the creation of new products, services, and jobs." Fellows will work within and across issue areas—health, education, energy, etc.—to make government data more usable by researchers, journalists, innovators, and the public at large. Video of the Fellowships ceremony below.

This Week in Data: 8/17/2012

Friday, August 17, 2012

In the Financial Post on Monday, IBM's Les Rechan argues that data-driven decision-making could alleviate if not solve many of Canada's productivity problems. He argues that "research shows analytically driven organizations outperform their competitors, delivering 49% higher revenue growth, 20 times more profit growth, and a 3% higher return on invested capital."

BankInfoSecurity.com posted an interview with Gartner analyst Neil MacDonald about the role of data analysis in cybersecurity. In the interview, MacDonald emphasizes the value of data in detecting and preventing threats:

Big data is being brought to solve the next generation of information security problems, but big data is being brought to solve the next generation of IT operations problems, things like application performance monitoring and root-cause analysis and behavioral monitoring of applications and behavioral learning. It's the same type of problem. Help me understand where anomalous behavior exists in my systems. Sometimes it's going to be security issues; sometimes it's going to be an operational issue, but the fact that it's anomalous behavior is of interest to both.

ZDNet published a podcast featuring a discussion with several key stakeholders in a massive undertaking to collect and analyze ocean and climate data, Ocean Observatories Initiative and the Cyberinfrastructure Program. The project is an amazing example of how different actors and interests can pool resources around massive amounts of data to do massive good.

This Week in Data: 8/10/2012

Friday, August 10, 2012

Today, IBM is hosting a research colloquium on data-driven innovation in the entertainment industry titled "Box Office to Front Office: Winning with Big Data." Watch the event's livestream here. IBM's Michelle Zhou, a participant in today's colloquium, guest blogged for Huffington Post earlier this week, writing about the four "V's" of data—velocity, volume, veracity, and variety—and the value of data to the end user.

Last month, Deloitte released "Data Nation 2012: Our Lives in Data," a report that "examines the UK public’s attitudes towards the collection and exploitation of their data by organisations in both the public and private sectors."

As election season heats up, Forbes reported on research findings from the Annenberg School for Communication at U Penn showing that Americans strongly dislike interest-based political advertising. Lisa Arthur writes, "Survey participants said their likelihood of voting for a candidate they support would decrease a lot (37 percent ) or at least somewhat (27 percent) if they learned a candidate’s campaign organization buys information about their online activities and their neighbor’s online activities—and then sends different political messages designed to appeal to them." Annenberg importantly makes a distinction between tailored ads and targeted ads. Arthur explains:

They described targeting advertising as the analysis of data about a population to determine who should receive a persuasive message, how, when and for what reasons. They described tailored advertising as shaping a persuasive message for a particular individual based on conclusions the targeting process generated about that person’s interests and values.

This Week in Data: 8/3/2012

Friday, August 3, 2012

Happy Friday! Here is this week's highlights of data stories on the web!

InformationWeek's "7 Deadly Sins Of Big Data Users" covers 7 categorizes of the common mistakes organizations make as they attempt to dive into the world of data. The list comes from Josh Williams, president and chief science officer of Kontagent. Particularly worth note:

6. Pride: Decision-Driven Data Making. Rather than running tests and using data to confirm or deny assumptions, this Deadly Sin is where you dig through data to confirm your preconceived notions. "We see this happen a lot throughout organizations, both at the executive level and within teams," Williams said. "People try to confirm what they believe; they dig through data to find it." But the best data-driven cultures have mantras like: "Data wins arguments," he said. Let the data speak the truth.

If you've been waiting for the ultimate infographic that visualizes just how much data is created every minute, this infographic on Domo's blog is for you.

The Information Security Forum released a report, "Data Analytics for Information Security" [report behind paywall for non-members], the potential for massive amounts of data to help us detect and reduce cybersecurity risks. As Computer Weekly reports, "...the importance of big data analytics has never been greater, with data volumes growing at around 2.5 million terabytes a day."

On The Information Daily (formerly eGov Monitor), Vicky Sargent muses on the complexities of public data initiatives, focusing on the UK. Despite the lack of immediate returns on investment in public data release, Vicky notes:

The open data agenda has raised awareness of the value of data and other information assets in making good decisions. Maps, visualisations and other tools built using the data ‘because it is there’, have created wider awareness of new technologies that make data easier to manipulate, present, share and communicate.

Interactive, web-based tools are starting to put data into the hands of ordinary managers and decision-makers. Where they once needed to wait for data from an analyst or GIS specialist managers are increasingly able to access and interrogate datasets on demand through shared online tools.

This Week in Data: 7/27/2012

Friday, July 27, 2012

Speaking of the Olympics, TechNewsWorld published a piece today about the lengths to which the organizers have gone to protect the infrastructure and secure the massive amounts of data generated at the Olympics safe from hackers.

In the most recent Beijing Olympics, it is estimated there were 12 million potential cybersecurity threats each day. The reality is the majority of these threats were easily mitigated -- routine cybersecurity attacks from automated tools and moderately skilled attackers. However, within those millions of benign threats, there were legitimate concerns as well. This presents a significant challenge: how to find the real threat within the noise.

For the upcoming London Olympic Games, organizers are doing their best to prepare for this challenge. State of the art systems have been implemented to monitor hardened networks and systems. Security Operation Centers (SOC) have been staffed to monitor threats 24 x 7. Ethical hackers have been employed to test the security and capability of systems and staff. The question is, will it be enough?

Over on IT World, Irfan Khan discusses several ways in which scientists are using harnessing satellite image data to build models of weather patterns that affect food supplies. Khan writes, "In Spain, for example, scientists are using such data to improve irrigation efficiency on farms, which is critical in a nation where 85% of the country’s water is consumed by agriculture."

InformationWeek's Kevin Fogarty's article on Wednesday, "Big Data Plus Police Work: Good Partners?", includes a great example of data-driven innovation in law enforcement:

For example, big data comprised of more than 1 million police emergency-call records helped redraw a central Texas city's police patrol-beat boundaries into fiefdoms far more easily patrolled than if the entire city were one big hot zone, according to Scott Dickson, a Texas crime analyst and consultant.

By pooling results of all those 911 calls, Dickson was able to assign specific types and levels of risk in different areas of town to decide how many patrols were needed in which areas, and for what type of crime. Frequent but low-intensity crimes such as vandalism or burglary require more day-to-day attention than murders, for example, because murder is comparatively rare.

Finally, on a similar subject, the Pew Public Safety Performance Project, which "works with states to advance data-driven, fiscally sound policies and practices in the criminal and juvenile justice systems that protect public safety, hold offenders accountable, and control corrections costs." Lots of interesting applications of data-driven policymaking around law enforcement and criminal justice to be found on the site.

This Week in Data: 7/20/2012

Friday, July 20, 2012

In Better medicine, brought to you by big data, Derrick Harris at GigaOM references an August 2011 GigaOM post about a company called Tableau that is helping staff at the Seattle Children's Hospital "draw inferences from the 10 terabytes of data locked up in his servers and warehousing appliances." The goal is to streamline processes, plan trials, and increase hospital efficiency.

Pew Internet & American Life Project released a report on big data this week: The Future of Big Data. The report is based on findings from a survey conducted with Elon University. Elon University has made both the credited and anonymous survey responses available on their website, which provides a glimpse into how people are thinking about the potential impact of data-driven everything.

Survey participants were asked, “What impact will Big Data have in 2020? What are the positives, negatives, and shades of grey in the likely future you anticipate? How will use of Big Data change analysis of the world, change the way business decisions are made, change the way that people are understood?”

A couple interesting answers:

“The more that data sets are open and accessible, entrepreneurial Web-savvy types will harness that raw material for different ends, and many times these may be philanthropic. We will see more visual representations of large data sets that will enable people to see the impacts of their activities as they play out in other parts of the world. Big Data will be used to forecast and predict, more simulations will be played out, and these simulations will help people to understand the complexity of our correlation to each other, as beings on this planet and beyond. People will try to ‘fix’ or ‘game’ scenarios based on simulations. We’ve already seen this in the past decade with the Wall Street crisis, but systems of this size and complexity are dynamic and self-regenerative. The realization of dynamic and emergent systems as a natural order will cause people to realize the foolishness of trying to game systems to the Nth degree. We will see the rise of more algorithmic thinking among average people, and the application of increasingly sophisticated algorithms to make sense of large-scale financial, environmental, epidemiological, and other forms of data. Innovations will be lauded as long as they register a blip in the range of large-scale emergent phenomena.”

“The data deluge is a good thing. Large datasets can be mined and visualized to elucidate patterns that have not been ever possible. The availability of large datasets is not the issue, but how people choose to use this information for policy decisions that benefit humanity (or not.) As an example of large datasets, scientists continue to collect voluminous data from imaging techniques from earthquake and ocean sensors, satellites, and space probes. The 2D and 3D visualizations are able to help scientists explain changes to our planet and predict future changes. Inferential software can be wrong, but I believe the developers of those tools will be making tools for the greater good, so better software will be developed when bugs are found.”

In "Why Big Is Bad When It Comes To Data," InformationWeek's Patrick Houston takes a look at the shortcomings of "big data" as a buzzphrase. He argues that "big" merely describes the amount and makes it sound "too benign" given the complicated landscape of policy issues relating in a data-driven world. He writes:

Data isn't static, like standing waters of a reservoir. It's increasingly dynamic, generated and collected in real time. Even transactional data is being captured at both ends--and at every point in between. Ergo, data gushes.

In "Time To Build Your Big-Data Muscles," Marcia Conner, a member of Fast Company's "expert contributor community," discusses the increasing demand for professionals with data analytics skills. Marcia argues that this isn't just for students getting ready to find jobs, either. Longtime professionals should start thinking about ways to brush up on their data analytics skills in order to remain competitive and relevant in the job market in any discipline, but especially in fields where business and IT come together. She writes, "Data will not answer questions by itself. People need to be able to communicate effectively about the findings, linking analytics to key decisions and the bottom line."

This Week in Data: 7/13/2012

Friday, July 13, 2012

A roundup this week's data coverage, events, papers, and more:

UK think tank Policy Exchange released a report on the value of data in the public sector titled "The Big Data Opportunity: Making government faster, smarter and more personal." In the report, author Chris Yiu argues that huge savings lie within massive amounts of data. He writes:

At a macro level, there is scope to improve the overall efficiency of government operations, to accelerate efforts to reduce fraud and error, and to make further inroads into the tax gap (the difference between actual tax collected and theoretical liabilities). We estimate that achieving cutting-edge performance could in time save the public sector up to £16 billion to £33 billion a year—equivalent to £250 to £500 per head of the population.

On Tuesday, Oracle released "Big data, Bigger opportunities" (account required for download), the first in a series of reports on the smart grid. Oracle's findings are based on a survey of "151 North American senior-level executives at utilities with smart meter programs in place." Findings show that "45 percent of utilities still struggle to report information to business managers as fast as they need it and 50 percent miss opportunities to deliver useful information to customers." [Forbes coverage here.]

The WorldBank Open Data Initiative teamed up with Data.gov and the Open Development Technology Alliance to host the second International Open Government Data Conference in Washington, DC. The event brought together 400 attendees from around the world to address the opportunities and challenges of opening public sector information. The WorldBank liveblogged the event's technical track and has already posted several keynotes to their site. Additional video from the conference will be available on Data.gov next week.

David McQueeney, IBM's head of Software Research, sat down with CNBC to discuss the untapped potential that lies within piles of unstructured data companies are gathering. Video posted about halfway down the page. Direct link to the video here.