Tag Archives: Federal Government

NIST Big Data Working Group

The US National Institute of Standards and Technology (NIST) kicked off their Big Data Working Group on June 19th 2013.  The sessions have now been broken down into subgroups for Definitions, Taxonomies, Reference Architecture, and Technology Roadmap.  The charter for the working group:

NIST is leading the development of a Big Data Technology Roadmap. This roadmap will define and prioritize requirements for interoperabilityreusability, and extendibility for big data analytic techniques and technology infrastructure in order to support secure and effective adoption of Big Data. To help develop the ideas in the Big Data Technology Roadmap, NIST is creating the Public Working Group for Big Data.

Scope: The focus of the NBD-WG is to form a community of interest from industry, academia, and government, with the goal of developing a consensus definitionstaxonomiesreference architectures, and technology roadmap which would enable breakthrough discoveries and innovation by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life. Deliverables:

  • Develop Big Data Definitions
  • Develop Big Data Taxonomies
  • Develop Big Data Reference Architectures
  • Develop Big Data Technology Roadmap

Target Date: The goal for completion of INITIAL DRAFTs is Friday, September 27, 2013. Further milestones will be developed once the WG has initiated its regular meetings.

Participants: The NBD-WG is open to everyone. We hope to bring together stakeholder communities across industry, academic, and government sectors representing all of those with interests in Big Data techniques, technologies, and applications. The group needs your input to meet its goals so please join us for the kick-off meeting and contribute your ideas and insights.

Meetings: The NBD-WG will hold weekly meetings on Wednesdays from 1300 – 1500 EDT (unless announce otherwise) by teleconference. Please click here for the virtual meeting information.> Questions: General questions to the NBD-WG can be addressed to BigDataInfo@nist.gov

 

To participate in helping the US Government in their efforts, sign up at http://bigdatawg.nist.gov/home.php

Does A Classification Marking Inherently Bias Perceived Reliability?

In “HOW SECRECY CAN DISTORT DATA” (http://www.newyorker.com/online/blogs/elements/2013/06/the-problem-with-secret-information.html), David Berreby cites two studies that posit that an individual will rate classified information, on average, with 15% more credibility than non-classified information.  I find the article and the studies cited to be naive in their approach to supporting the notion that adding a classification label lends some inherent credibility to information when judged by legitimate professionals.

The methodologies of these studies don’t exactly lend themselves to authoritative results. Perhaps if individuals from the Intelligence services were recruited for comparison it may be slightly more informative but even within those groups the ability to discern credibility (and the responsibility to make that judgement) run a very broad spectrum. Further, gauging between classified and unclassified sources is probably not meaningful as decisions are made from multiple lines of evidence in _any_ field meaning that a bias, should it actually exist, would likely not be a factor in real-world decisions. I would be very interested to see a study performed with a more valid population and a measure inserted to test if these biases actually influenced any decision in a meaningful way.

Anyone know of any studies analyzing these factors?

US Government Spying on American Citizens

From Whence are the Dangers of Intelligence Collection on American Citizens?

Corporate spying, not US Government spying and what you should know
Consumer Intelligence

The ubiquity of cell phones has made the capturing of actual behavior (versus behavior stated in surveys) a multi-billion dollar enterprise.  A boon to legitimate enterprises and researchers, there are nagging questions regarding the ethics of collecting personal information solely on the basis of a (unapproachably worded) legal disclaimer.  The powerful sensor package carried in our pockets may rival those of a military drone aircraft or a manufacturing robot.  Further, collection and resale of sensor data in mobile devices will continue to expand as more sensors are added.  A highly insightful article in the Wall Street Journal posted recently in their blog section displays a fantastic analysis, hinting at one small aspect of surreptitious consumer information gathering.  There has been a significant volume of emotional arguments expressed by those concerned with the US Government’s Prism project–the law and ethics of which are well-controlled and well-understood, the individual risk of disclosure negligible, and the threat imposed by disclosure minimal.  The sheer volume of information, the cost of analysis, the lack of actionable intelligence, and high degree of noise are a huge barrier to actual violation of individual liberties and in practice likely preclude the US Government spying activity on citizens.  In contrast, the WSJ article above highlights a few of the major commercial collectors of consumer intelligence, the contents of which are very typically acted upon.   Perhaps articles like these may do something to educate people to one reason some mobile services are free.  Then consumers may choose by whom and to what degree they wish to be surveilled.