On November 20th, 2012 OLC attended the NYC Data Business Meetup #10 hosted by Matt Turck of Bloomberg Ventures and featuring panelists Christopher Ahlberg of Recorded Future, Josh Becker of LexMachina, Hjalmar Gislason of DataMarket and Nicholas Bonnadio of NumberFire.
After a brief introduction by host Matt Turck of Bloomberg Ventures, Christopher Ahlberg of Recorded Future opened the panel with a short presentation. Recorded Future is turning the web into predictive circles by treating the world’s events as data and using big data to predict future events. Ahlberg feels that the future is available today, on the internet, if we can turn enough text into a dataset. If successful, we may be able to reduce the number of “black swan” surprises by as much as 0.25%.
Josh Becker of LexMachina followed and his firm is applying big data concepts to the legal field. LexMachina has created a database of patent & IP lawsuits, as a joint venture between Stanford’s law school and computer science schools. The problem being solved by LexMachina is a legal system drowning in raw data from over 100k cases, 35k litigating parties and 5 million unique case events. Through its process of capturing, clean coding, tagging and expert outcome coding, Lex Machina is able to provide IP litigation data analytics that can help address the problems of complex cases, corporations under attack and an unpredictable judicial system in the IP litigation realm.
Next up was DataMarket’s Founder/Ceo, Hjalmar Gislason hailing from Iceland via Cambridge, Massachusetts. Gislason, the creator of NYCBDM’s big data nerd logo, has built a google for numbers in DataMarket. Every business needs microeconomic data (growth, inflation, employment number’s) in some capacity, but Gislason has found that companies need data to be more relevant, hence, their creation of industry verticals, starting with Datamarket Energy.
Nicholas Bonaddio, Ceo/Founder of NumberFire presented next, offering his view of the next generation of sports analytics, or colloquially, the “five-thirty-eight of sports”. He uses a multi-step process to revisit sports plays to a) understand what happened, b) use markup chain maps to identify expected points before and after, and c) use these metrics to predict the likelihood of future plays and events. Yes, this information will be useful to owners of fantasy sports teams, but there will also be a market with sportswriters, coaches, announcers and others.