Watch the LIVE WEBCAST of “Open Science and Innovation: Of the People, By the People, For the People”, hosted by the White House Office of Science and Technology Policy (@WhiteHouseOSTP), on Wed, September 30th from 8:10am-12pm ET. Learn more
Only a small fraction of Americans are formally trained as “scientists.” But that doesn’t mean that only a small fraction of Americans can participate in scientific discovery and innovation. Citizen science and crowdsourcing are approaches that educate, engage, and empower the public to apply their curiosity and talents to a wide range of real-world problems. To raise awareness of these tools and encourage more Americans to take advantage of them, the White House Office of Science and Technology Policy and the Domestic Policy Council will host “Open Science and Innovation: Of the People, By the People, For the People,” a live-webcast forum, on Wednesday, September 30th.
Follow on Twitter #WHCitSci
“Better coordination among federal agencies that collect, maintain, and use geospatial information could help reduce duplication of geospatial investments and provide the opportunity for potential savings of millions of dollars.”
For full analysis, please visit GAO here.
GAO-15-193: Published: Feb 12, 2015. Publicly Released: Mar 16, 2015.
GAO-14-226T: Published: Dec 5, 2013. Publicly Released: Dec 5, 2013.
GAO-13-94: Published: Nov 26, 2012. Publicly Released: Nov 26, 2012.
Information Technology: OMB Needs to Improve Its Guidance on IT Investments
GAO-11-826: Published: Sep 29, 2011. Publicly Released: Oct 26, 2011.
Geospatial Information: Better Coordination Needed to Identify and Reduce Duplicative Investments
GAO-04-703: Published: Jun 23, 2004. Publicly Released: Jun 23, 2004.
by Petr Keil, R you cereal? blog, January 2, 2012
Data-driven scientists (data miners) such as Rosling believe that data can tell a story, that observation equals information, that the best way towards scientific progress is to collect data, visualize them and analyze them (data miners are not specific about what analyze means exactly). When you listen to Rosling carefully he sometimes makes data equivalent to statistics: a scientist collects statistics. He also claims that “if we can uncover the patterns in the data then we can understand.” I know this attitude: there are massive initiatives to mobilize data, integrate data, there are methods for data assimilation and data mining, and there is an enormous field of scientific data visualization. … And they are all excited about big data: the larger is the number of observations (N) the better. Rosling is right that data are important and that science uses statistics to deal with the data. But he completely ignores the second component of statistics: hypothesis (here equivalent to model or theory). …
To read this article as well as the interesting debate that followed in the comments, please visit Data-driven science is a failure of imagination | R you cereal?.
- Data Scientists Will Unlock Big Data’s Promise (blogs.wsj.com)
- What is Data Science? (architects.dzone.com)
- The Human Face of Big Data, a Book Review (sys-con.com)
by Alistair Croll, O’Reilly Radar, August 2, 2012
…With the new, data-is-abundant model, we collect first and ask questions later. The schema comes after the collection. Indeed, big data success stories like Splunk, Palantir, and others are prized because of their ability to make sense of content well after it’s been collected — sometimes called a schema-less query. This means we collect information long before we decide what it’s for.
And this is a dangerous thing….
- The future of programming – O’Reilly Radar (radar.oreilly.com)
- The four D’s of programming’s future: data, distributed, device, democratized (revolutionanalytics.com)
- DARPA and Defense Department look to a more open source future (adafruit.com)
by Chad Wellmon, IASC: The Hedgehog Review – Volume 14, No. 1 Spring 2012
‘The history of this mutual constitution of humans and technology has been obscured as of late by the crystallization of two competing narratives about how we experience all of this information. On the one hand, there are those who claim that the digitization efforts of Google, the social-networking power of Facebook, and the era of big data in general are finally realizing that ancient dream of unifying all knowledge. … Unlike other technological innovations, like print, which was limited to the educated elite, the internet is a network of “densely interlinked Web pages, blogs, news articles and Tweets [that] are all visible to anyone and everyone.”4 Our information age is unique not only in its scale, but in its inherently open and democratic arrangement of information. … Digital technologies, claim the most optimistic among us, will deliver a universal knowledge that will make us smarter and ultimately liberate us.5 These utopic claims are related to similar visions about a trans-humanist future in which technology will overcome what were once the historical limits of humanity: physical, intellectual, and psychological. The dream is of a post-human era.6
For the full text of this substantive essay, please visit IASC: The Hedgehog Review – Volume 14, No. 1 Spring 2012 – Why Google Isn’t Making Us Stupid…or Smart – Chad Wellmon.