He started in the right place with a ringing endorsement of the progressive use of big data as a tool for economic and social improvement.  He referred favorably to “breakthroughs in medical research from aggregated health care records that can produce information far more robust than the limited populations of medical trials,” and cited a recent example:    

“The drug Herceptin was developed through identification of the HER-2 oncogene from records of 9,000 breast cancer patients. IBM is working with hospitals and the IBM-WATSON natural language system to collect anonymized medical records in ways that protect privacy and analyze unstructured data applying the power of new analytic technologies across many different text-based medical records previously unintelligible to computers.”

As SIIA noted in a recent whitepaper, the seamless flow of data across borders is important to the growth of data-driven innovation and the global economy. Kerry underscored the economic importance of cross-border data flow:

 “Trans-border trade – and especially transatlantic trade – now relies on the continued open flow of data, and cutting off these flows would cause significant and immediate economic damage. Moreover, it would lead to loss of competitiveness on both sides as other economies around the world that embrace open Internet architectures and freedom to experiment with data analytics offer havens for innovators. Our economic future is at stake in our international engagement.”

Then he noted the importance to transatlantic trade of the Safe Harbor arrangement that has governed transfers of information from the European Union to the United States for well over a decade. He warned of the dangers a weakening of this framework would pose to transatlantic trade:

“Today, more than 4,000 companies have subscribed to the Safe Harbor Framework. Many of these are U.S. subsidiaries of EU companies that also rely on the framework…Safe Harbor is a fundamental building block of the trade relationship between the United States and Europe…Any step back from Safe Harbor would send the trading relationship between the U.S. and the EU backward.”

This worry about a threat to the Safe Harbor Framework is not idle. On July 19, 2013 Viviane Reding, European Commission Vice President, issued a statement  saying, “The Safe Harbour agreement may not be so safe after all.” On July 24, 2013, a statement from the Conference of German Data Protection Commissioners indicated that it would examine whether transatlantic data transfers “should be suspended on the basis of the Safe Harbour framework.” 

The basis for this threat to the Safe Harbor in both cases is the NSA revelations regarding government surveillance–but this is mixing up apples and oranges.

The EU Data Protection Directive and the Safe Harbor both provide an exception for national security purposes.  In the US and EU regime, the law, regulation, and policy considerations that relate to protecting consumer privacy in a commercial context are completely different from the law and policy and constitutional considerations that govern government surveillance. 

Moreover, putting onerous burdens on the commercial transfer of information as a backdoor way to control government surveillance is self-defeating and counterproductive.  It distracts from real measures that might protect citizens from overly intrusive government surveillance and it puts an unnecessary burden on commerce that is not justified by the need to preserve and protect consumer privacy in a commercial context.

Kerry’s remarks yesterday show he grasps these issues clearly.  It might have been his last public statement before leaving his current post at the Commerce Department, but it sets a promising roadmap for Obama administration policy in this area.

Mark MacCarthy, Vice President, Public Policy at SIIA, directs SIIA’s public policy initiatives in the areas of intellectual property enforcement, information privacy, cybersecurity, cloud computing and the promotion of educational technology. Follow the SIIA Public Policy team on Twitter at @Mark_MacCarthy

Last Thursday, the Obama Administration released its Intellectual Property (IP) Enforcement Strategy, which addresses a wide range of IP enforcement issues, offering numerous specific actions by federal agencies aimed at helping to protect and advance creativity and innovation. In response, SIIA praised the Plan’s call for software compliance throughout the federal government, while expressing our disappointment that it does not address digital content compliance, which is an equal challenge for SIIA members. SIIA also welcomed greater involvement by the Administration in the expansion of domain names by ICANN, which will have far reaching implications for businesses, brands and consumers. Read more on SIIA’s Digital Discourse Blog.

Mobile Privacy Code of Conduct Could Be Finalized Soon

Just around the corner after the July 4th break, the Department of Commerce (DOC) is hopeful to conclude the year-long process to develop a voluntary code of conduct for mobile app privacy. The effort is the first of the multistakeholder initiatives launched by the DOC in 2012 as a major component of a new effort to develop a flexible privacy regime. SIIA is very supportive of the voluntary, multistakeholder approach to privacy because it is more nimble and less prescriptive than a legislative or regulatory approach. To that end, we have been leading participants in the multistakeholder discussions and are hopeful to reach a final code that will serve as an effective model for companies that provide consumer apps to develop “short form” privacy notices for users. Stay tuned!

SIIA Cautions about Scope of New Cybercrime Legislation

Last week, legislation was introduced in the House and Senate that would weaken the Computer Fraud and Abuse Act (CFAA), a long standing law that is critical to software and digital content companies to protect their networks and the intellectual property in their products and services. While the bill is well intended and seeks to address real concerns, SIIA reiterated our concerns with CFAA reform proposals that the proper fix is to clarify the prosecutorial guidelines, not a wholesale rewriting and weakening of the underlying statute. SIIA believes that the better way forward for Congress is to wait a Supreme Court clarification and then see if further legislative revisions are necessary. In the meantime, the Justice Department can address any concerns about prosecutorial overreach through improved guidelines. Read more on SIIA’s Digital Discourse Blog.

FTC Joins the Fight against Patent Trolls as Lawsuits Expand Beyond Tech

Also last week, FTC Chairwoman Edith Ramirez declared in a speech that, “PAE lawsuits are no longer filed primarily against IT firms. Retailers and financial services providers that incorporate software into their products and services are now common targets.” Ramirez went on to explain that the FTC is “on the watch for PAEs that target small businesses with false claims made to induce the payment of illegitimate licensing fees. This would include telling a small business that it owes money to a PAE for a patent license when the PAE has no ownership interest in, or standing to assert, any patent rights; has only an expired patent; or makes false threats of litigation.” The Chairwoman’s remarks are a welcome sign that the FTC remains committed to the battle against patent trolls, and this is a valuable reminder that they have an integral role to play.

David LeDuc is Senior Director, Public Policy at SIIA. He focuses on e-commerce, privacy, cyber security, cloud computing, open standards, e-government and information policy. Follow the SIIA public policy team on Twitter at @SIIAPubPolicy.

Over the past decade you have seen sports such as baseball and the success of “Moneyball” where teams used large amounts of data to find undervalued players and sign them in order to compete more successfully against teams with more money.  Over this time many professional sports leagues have used types of data analytics to increase and maintain fan support of the league by making their sport more exciting and interactive to fans because they are now able to explain the why of how a specific team or player is better and not just the what using math and patterns.  Now the Association of Tennis Professionals (ATP) Tour is getting in on the action by partnering with IBM at their Grand Slam tournaments. 

The ATP and IBM are doing this by creating an analytics tool called SlamTracker, which allows for 8 years of data and 41million data points per match to be used and analyzed.  This information is available for players, coaches, broadcasters, and fans to use to help them figure out where they need to improve their game, what are the most important things to determining who will win a match, or why a specific player is better and not just that they are.  According to the data SlamTracker has collected the reason Rafael Nadal is so dominant on clay is because his serve to the ad side on that surface is the single hardest shot to hit (based on the math) in all of tennis due to the small window there is for an opponent to return it.  At the same time the reason Novak Djokovic had the best possible chance at beating Nadal of the entire field is because he is the best at hitting a high bouncing back hand return.  Look for SlamTracker to again be used during Wimbledon later this month.  By using SlamTracker and all of the data that is accumulated during matches the ATP is able to enhance the experience of the sport for both the players and fans and is an excellent example of the real world uses of Data Driven Innovation (DDI).

Denys Emmert is the Public Policy intern at SIIA. He has a degree in marketing and political science from Florida State University.

Running a small business is a lonely job at times. Key business decisions are too often made in a vacuum, without access to pertinent data. In this new era of big data, Intuit is working to give small businesses powerful, data-driven insights once only available to much larger businesses.

The Trends feature in Intuit’s QuickBooksOnline empowers small businesses to benefit from the power of their own data as well as the collective wisdom of fellow Intuit customers. Trends anonymously aggregates customer data, allowing small businesses to see how their income and expenses stack up against similar businesses. For example, a roofer in Philadelphia grossing $250,000 a year can compare results with other roofers in the area or across the country. Is that revenue good or bad? Is five percent growth normal or better than companies in your area like you? With Intuit Trends, small businesses can now answer those questions in seconds.

An Intuit customer in Illinois uses Trends to see how his consulting firm’s expenses compare to others in his industry. The business can easily recognize if it needs to continue to increase its profit margins and reduce costs to stay competitive. Trends make it easy for them to stay aware of what is going on in the industry and make key business decisions.

The rapid advance of medical monitoring technology has done wonders to improve patient outcomes. Today, patients are routinely connected to equipment that continuously monitors vital signs such as blood pressure, heart rate and temperature. The equipment issues an alert when any vital sign goes out of the normal range, prompting hospital staff to take action immediately, but many life-threatening conditions do not reach critical level right away. Often, signs that something is wrong begin to appear long before the situation becomes serious, and even a skilled and experienced nurse or physician might not be able to spot and interpret these trends in time to avoid serious complications.

Project Artemis, part of IBM’s First-of-a-Kind pro-gram which pairs IBM’s scientists with clients to explore how emerging technologies, can solve real-world business problems. The system captured the data stream from bedside monitors and processed it using algorithms designed to spot the telltale signs of nosocomial infection. The truly significant aspect of the Project Artemis approach is how it brings human knowledge and expertise together with device-generated data to produce a better result. The system’s outputs are based on algorithms developed as collaboration between the clinicians themselves and programmers. The algorithm concept is the essential difference between the Artemis system and the existing alarms built into bedside monitors.

The flexibility of the platform means that in the future, any condition that can be detected through subtle changes in the underlying data streams can be the target of the system’s early-warning capabilities. Also, since it depends only on the availability of a data stream, it holds the potential for use outside the ICU and even outside the hospital. For example, the use of remote sensors and wireless connectivity would allow the system to monitor patients wherever they are, while still pro-viding life-saving alerts in near-real time.

Scripps Health, a nonprofit community health system, innovative and patient-focused process that has virtually eliminated wait times and has changed the way the hospital delivers care to patients seeking treatment in the emergency department at multiple campuses. Scripps is changing its culture from one in which quality is measured almost entirely by the performance of physicians, to one in which quality is measured by the performance of the processes, systems and teams that support them. They don’t want physicians to be exclusively responsible for quality, but for quality to be measured by the team.

To inform its approach to these changes, Scripps collected and analyzed variation data, or information about whether a particular process was in control. For example, in anticipation of re-engineering its emergency room procedures, Scripps collected and analyzed massive amounts of data on wait times and cross-referenced the information against the type of injury, tests that were ordered and how long it took to discharge the patient. Then they did extensive simulation of our processes using real-life data, modeling how new and different processes might work.

Scripps found that the triage process added an unnecessary and wasteful step in getting patients from the door to a doctor. It was adding time and cost to the system, and not adding significant value. So the company eliminated it. They reduced the critical door-to-doctor time, add capacity to our emergency rooms and improve the quality of our service. As they build a new hospital, Scripps Health is looking into whether they even need to build a waiting room in the ER.

Blue CRUSH (Criminal Reduction Utilizing Statistical History) is a data analytical initiative that provides the Memphis Police Department (MPD) the ability to gain an advantage through insight and agility. At the heart of it is a predictive model that incorporates fresh crime data from sources that range from the MPD’s records management system to video cameras monitoring events on the street. In the realm of crime-fighting analytics, there’s a fine line between the “interesting” and the actionable. It is strength in the latter that makes Blue CRUSH stand out from its predecessors. Blue CRUSH lays bare underlying crime trends in the way that promotes an effective fast response, as well as a deeper understanding of the longer-term factors (like abandoned housing) that affect crime trends. It happens at the precinct level. Looking at multilayer maps that show crime hot spots, commanders can see not only current activity levels, but also any shifts in such activities that may have resulted from previous changes in policing deployment and tactics.

At each weekly meeting, commanders go over these results with their officers to judge what worked, what didn’t and how to adjust tactics in the coming week. They might see, for example, how burglaries are down in one ward, but up another, or where thieves are stealing cars in one ward and dumping them in another. What’s striking, says MPD Chief Godwin, is the granularity. “We’re catching this immediately and we’re doing it every day,” he explains. “On short notice, we’re able to shift officers to a particular ward, on a particular day, right down to the shift level. It’s a bit like a chess match and it’s enabling us to make arrests we never could have before.”

Today, we’re in the digital ocean. We can gather information about students’ daily learning activities and interactions with content as they happen in computer-based instruction. The increase of technology-based learning in schools enables us to have all students doing meaningful activity on digital devices. Computers now allow us to capture all kinds of data about what students do as they interact with learning material, seamlessly recorded as they go about their daily learning activity. These interactions can produce an “ocean” of data that, if used correctly, can give us a completely different view of how students progress in acquiring knowledge, skills, and attributes.

This ability to capture data from everyday student learning activity should fundamentally change how we think about assessment.

Invisible assessments allow us to gather information much more frequently without interrupting the flow of instruction, hence the term “invisible.” This lets us provide teachers, students, and parents with feedback about progress immediately and in time to make adjustments to teaching and learning. It also eliminates the common complaint about the heavy time requirements of traditional assessment.

By capturing many, many observations of a student’s learning activity over time, we are able to build models of student learning and proficiency without the pressure of performance on a single test.

David LeDuc is Senior Director, Public Policy at SIIA. He focuses on e-commerce, privacy, cyber security, cloud computing, open standards, e-government and information policy. Follow the SIIA public policy team on Twitter at @SIIAPubPolicy.

Data collection and use is at crossroads, and decisions by policymakers could have an enormous impact on American innovation, jobs and economic growth. It is essential for policymakers to recognize that data-driven innovation presents an economic growth engine that is revolutionizing our lives and will create 1.9 million U.S. jobs by 2015.  At the same time, we have to address the very legitimate questions about the storage and use of data without strict regulation that stifles economic opportunity.  With this paper, we’ve taken a comprehensive look at the issue – providing significant analysis of where the opportunities lie with data and what needs to be done to unlock its full potential.   Our goal is help government and industry enable the transformative power of data-driven innovation.

In the white paper, SIIA writes,

Technologists, privacy advocates and policymakers can work together to foster the societal, governmental and business opportunities created by data-driven innovation, while also meeting the challenge of protecting privacy…SIIA urges policymakers to proceed cautiously and avoid policies that seek to curb the use of data, as they could stifle this nascent technological and economic revolution before it can truly take hold.

SIIA’s fundamental principle for policymakers is to avoid creating broad policies that curb data collection and analysis. More specifically, SIIA outlines 10 essential policy recommendations that it believes will make certain there is an effective balance between ensuring the tremendous economic and technological opportunity of data, and addressing privacy and other concerns:

1. To meet its full potential, DDI requires a policy framework that provides for an evolving view of privacy rights based on risk and societal benefits.
2. The principle of data minimization should be re-interpreted in light of DDI.
3. Policymakers should encourage de-identification as a way to balance the needs of DDI and privacy protection.
4. Uniform rules should not apply broadly to the collection of personal information and the role of consent.
5. Policymakers should promote technology neutrality and avoid technology mandates.
6. Open standards are critical enablers of DDI, but they must continue to evolve through industry-led standards development organizations, not governments.
7. Policies should allow data collectors and controllers to work with data management and analytics suppliers to comply with privacy and security rules through contracts across varying jurisdictions.
8. Policies must continue to balance the need of protecting the privacy of students, while enabling DDI to greatly enhance the teaching and learning experience.
9. Governments should adopt policies that leverage DDI to make government more efficient and effective and reduce government waste.
10. Governments should continue to embrace open data policies and public-private partnerships that maximize access to critical public data.

As the leading representative of the software and digital content industries, SIIA has long anticipated the opportunities that will arise from the evolution and convergence of information and computing platforms. Many of SIIA’s more than 700 member companies are key enablers of data-driven innovation.

David LeDuc is Senior Director, Public Policy at SIIA. He focuses on e-commerce, privacy, cyber security, cloud computing, open standards, e-government and information policy. Follow the SIIA public policy team on Twitter at @SIIAPubPolicy.

Government’s acceptance and utilization of new technologies is needed to enhance government’s mission.  Technologies that leverage data analytics to provide innovative functions and services hold the key for governments to provide improved services and to better understand how well they are fulfilling their missions.

Today, the White House issued an Executive Order “Making Open and Machine Readable the New Default for Government Information” and an OMB Memorandum (M-13-13) updating the Digital Government Strategy, originally published last May.  The updated policy seeks to further enhance the government’s open data initiative, making machine readable data the default for government data, while helping to establish a framework for effective information management at each stage of the information’s lifecycle to promote openness and interoperability.

Specifically, this Memorandum requires agencies to collect or create information in a way that supports downstream information processing and dissemination activities. This includes using machine readable and open formats, data standards, and common core and extensible metadata for all new information creation and collection efforts.  It also includes agencies ensuring information stewardship through the use of open licenses and review of information for privacy, confidentiality, security, or other restrictions to release. Additionally, it involves agencies building or modernizing information systems in a way that maximizes interoperability and information accessibility, maintains internal and external data asset inventories, enhances information safeguards, and clarifies information management responsibilities.

Beyond open data, governments need to embrace policies that enable a streamlined approach to innovative applications that draw from and analyze this data.  This emphasis on data analytics leads to data driven innovation (DDI) allowing governments to use data to improve the efficiency and effectiveness of government, as well as preventing waste, fraud and abuse.  Embracing open data, as the White House has done through the issuance of this policy, maximizes the full potential of DDI for governments to embrace open data policies, use public-private partnerships to provide access to critical public data, and to adopt enterprise architectures that enables sharing.  These steps will put public sector data to innovative uses that can reap the economic and societal benefits of DDI.

We applaud the efforts of the Administration that led to this policy and encourage the White House to continue to embrace open data policies, while also embracing policies that increase the use of data analytics—pulling data from myriad sources—to make strategic decisions, to encourage research and development around data science, and encourage teaching and training for data scientists and professionals with strong data analytics skills that are already in high demand in both the public and private sectors.

Michael Hettinger is VP for the Public Sector Innovation Group (PSIG) at SIIA. Follow his PSIG tweets at @SIIAPSIG. Sign up for the Public Sector Innovation Roundup email newsletter for weekly updates.