Before you sprint, leap, dive, or vault into the London 2012 vortex, take a second to peruse this week's roundup of data coverage, events, papers, and more!
- 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.