Opening remarks by the Strata program chairs, Edd Dumbill and Alistair Croll.
From hackathons to API-enabled civic data, learn how New York City government is evolving thanks to deeper engagement with the technology community.
by Jon Jenkins
The Kepler Mission began its science observations just over two years ago on May 12, 2009, initiating NASA’s first search for Earth-like planets. Initial results and light curves from Kepler are simply breath-taking, including confirmation of the first unquestionable rocky planet, Kepler-10b, and Kepler-11b, a system of 6 transiting planets orbiting one Sun-like star.
Kepler released light curves for the first 120 days of observations for over 150,000 target stars on February 2, 2011, and announced the identification of over 1235 planetary candidates, including 68 candidates smaller than 1.25 Earth radii, and 54 candidates in or near the habitable zone of their parent star. An astounding 408 candidates orbiting 170 stars as planetary systems were found. Dr. Jenkins will discuss how much we’ve learned over the 24 months about the instrument, the planets and the stars.
by Elissa Fink
Creating visualizations and info graphics with public data helps keep our politicians honest, and our society transparent. Strata and Tableau Public, a free tool for creating interactive online visualizations, have had hundreds of bloggers striving to win their Interactive Public Data Visualization Contest. Come see the best of the best from the contest, and the official announcement of the winner.
This keynote sponsored by Tableau Software
by Jer Thorp
Almost every piece of data is tethered to something in the real world. When we work with numbers, we are often able (and willing) to ignore the real world objects and systems that these numbers represent.
In this presentation, Jer Thorp will discuss his work with names—designing an arrangement algorithm for the 9/11 Memorial in Manhattan. He’ll walk through collaborative processes, admit to a series of failures and ultimately show how humans and software can combine to solve extraordinary problems.
by Randy Lea
The opportunity exists for organizations in every industry to unlock the power of iterative, big data analysis for new applications such as digital marketing optimization and social network analysis that improve the bottom line. Big data analysis is not just the ability to analyze large volumes of data, but also the ability to analyze more varieties of data and perform more complex analysis than is possible with more traditional technologies. But it doesn’t have to be as complicated as it sounds. This session will show you how you can bring the science of data to the art of business and empower more business users and analysts to operationalize insights and drive results. You’ll see examples of how data science is applied by making emerging analytic technologies more accessible to businesses and easily managed by enterprise architects across retail, financial services, and media companies.
This keynote sponsored by Aster Data
by John Rauser
Quantitative Engineer? Business Intelligence Analyst? Data Scientist? The data deluge has come upon us so quickly that we don’t even know what to call ourselves, much less how to make a career of working with data. This talk examines the critical traits that lead to success by looking back to what may be the first act of data science.
Data scientists and technology companies are rapidly recognizing the immense power of data for drawing insights about their impact and operations, yet NGOs and non-profits are increasingly being left behind with mounting data and few resources to make use of it. Data Without Borders seeks to bridge this data divide by matching underserved NGOs with pro bono data scientists so that they can collect, manage, and analyze their data together in the service of humanity, creating a more open environment for socially conscious data and bringing greater change to the world.
by Mark Madsen
History seems irrelevant in the software world, particular when dealing with lots of information. It isn’t. Information explosions are not new. They’ve happened repeatedly throughout human history. A little looking will turn up prior incarnations of information management patterns and concepts that can be repurposed using today’s technologies.
The first person to conceive of something is usually not the first. They’re the first to re-conceive at a point where the current technology caught up to someone else’s idea. We’re at a point today where many old ideas are being reinvented. Come hear why looking to the past beyond your core field of interest is worthwhile.
by Richard Merkin
Dr. Richard Merkin, President and CEO of Heritage Provider Network, is pleased to announce the winner of the first $3 million dollar Heritage Health Progress Prize. Responding to our country’s $2 trillion dollar health care crises, Dr. Merkin created, developed and sponsored the $3 million dollar Heritage Health Prize for predictive modeling to save more than $30 billion in avoidable hospitalizations. It is the largest predictive modeling prize in the world, larger than the Nobel Prize for Medicine and the Gates Prize for Health. Dr. Merkin is genuinely excited to bring new minds to the healthcare table with the prize and believes data miners hold great potential for not only bringing a winning algorithm, but also to grab the attention of data miners globally and raise awareness about competitive innovation, changing the world through healthcare delivery. Dr. Merkin will present the top two teams with $50,000 in the first progress prize, split as $30,000 and $20,000.
by Anne Wright
The BodyTrack project has interviewed a number of people who have improved their health by discovering certain foods or environmental exposures to avoid, or learning other types of behavioral changes. Many describe greatly improved quality of life, overcoming in some cases chronic problems in areas such as sleep, pain, gastrointestinal function, and energy levels. In some cases, a doctor or specialist’s diagnosis led to treatment which mitigated symptoms (e.g. asthma or migraine headache), but where discovery of triggers required self-tracking and self-experimentation.
Importantly, the act of starting to search for one’s sensitivities or triggers appears to be empowering: people who embarked on this path changed their relationship to their health situation even before making the discoveries that helped lead to symptom improvement.
The BodyTrack Project is building tools, both technological and cultural, to empower more people to embrace an “investigator” role in their own lives. The core of the BodyTrack system is an open source web service which allows users to aggregate, visualize, and analyze data from a myriad of sources—physiological metrics from wearable sensors, image and self-observation capture from smart phones, local environmental measures such as bedroom light and noise levels and in-house air quality monitoring, and regional environmental measures such as pollen/mold counts and air particulates. We believe empowering a broader set of people with these tools will help individuals and medical practitioners alike to better address health conditions with complex environmental or behavioral components.
by Ken Bado
Big Data is more than just volume and velocity. MarkLogic CEO Ken Bado will address why complexity is the key gotcha for organizations trying to outflank their competition by managing Big Data in real time. Learn how winners today are using MarkLogic to manage the complexity of their unstructured information to drive revenue and results.
by Hilary Mason
The flow of data across the social web tells us what people, around the world, are paying attention to at any given moment. Understanding this flow is both a mathematical and a human problem, as we develop and adapt techniques to find stories in the data.
Come hear about the expected and the surprises in the bitly data, as well as generalized techniques that apply to any ‘realtime’ data system.
by Arnab Gupta
In 1964, The Twilight Zone aired an episode titled “The Brain Center at Whipple’s,” in which factory owner Wallace Whipple completely eliminates his human workforce in favor of automated machinery. Mr. Whipple’s employees, clearly far ahead of their time, argue to him that human insights far outweigh the advantages provided by mechanical labor. Ironically, at the end of the episode, Mr. Whipple, too, is replaced by a machine.
It’s a well-known dichotomy: man versus machine—and, depending on who’s doing the talking, good (human) versus evil (machine). Today, as technology continues to evolve and machines are capable of ever more advanced processes and functions, the dichotomy is becoming even more pronounced. Look no further than IBM’s Watson, an advanced artificial intelligence machine that squared off against Jeopardy’s best human contestants in 2011—and won.
But, as Opera Solutions’ CEO Arnab Gupta proposes to explore in remarks at Strata, the man-vs.- machine dichotomy is a false one. A far better contest would have been a three-way one, pitting man versus machine versus man-plus-machine. It is almost a certainty that the latter combination would have won.
Consider: nowhere has the machine-vs.-human conflict been played out more fully than in the realm of chess, starting in 1997 with IBM’s Deep Blue vs. Garry Kasparov. Today, chess-playing computers routinely beat the strongest human players. One might conclude that the machines have won. But there’s a twist: as Kasparov has recently stated, a machine plus just an average player can beat all comers, humans or computers. Humans’ ability to think abstractly and creatively, to bring in new ideas, to apply history, to understand irony, opportunity, possibilities—all this, when paired with machines’ abilities to process huge amounts of data flows and bring to light hidden patters and connections that elude human understanding, make the machine/mind connection unbeatable.
In short, it is not humans vs. machines, but rather humans plus machines, which must become the new paradigm for scientists, business people, and others—particularly in the Big Data era. Combining human insight with machine intelligence overcomes the weaknesses of each while delivering never-before-seen strengths.
How can this be accomplished, particularly when machines and people speak different languages and, in truth, “think” differently? How can we create and foster a productive pairing of two very different types of “minds?” Arnab will address the need to create a new language—one mostly visual in nature— to allow humans and machines to work together and realize the full potential of their collaboration. Finding a common language is a pursuit that goes far beyond prosaic “UI” development, and instead forces us to examine how humans can (and might learn to) best understand what machines are saying.
22nd–23rd September 2011