e-Xploration
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e-Xploration
antropologiaNet, dataviz, collective intelligence, algorithms, social learning, social change, digital humanities
Curated by luiy
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The Next Big Thing in Crowdfunding? Kickstarting People

The Next Big Thing in Crowdfunding? Kickstarting People | e-Xploration | Scoop.it
What skeptics fail to realize is that the motivations of crowdfunding “investors” are different: These are not quant investors looking to maximize financial returns while minimizing risk and volatility.

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One market that has always seemed immune to disruption (as popularized by Clayton Christensen in the Innovator’s Dilemma) has been the market for money itself.

While all sorts of companies were being disrupted — by fledgling competitors introducing lesser-featured products no one really wanted — those who financed the disruptors gained most. Venture capitalists and investment bankers reaped the benefits when those fledgling companies’ innovative features finally moved into mainstream markets.

But those days of benefitting, while remaining immune to, disruption are done. Because of crowdfunding, Christensen’s heartless yet proven principle is finally turning its steely gaze toward the very way capital is allocated and accessed. However, I’m going to argue here not just for the popular notion of crowdfunding as backing “projects,” but as backing people, too.


Via Wildcat2030
luiy's insight:

Besides amusing, isolated examples like the man who sold IPO shares in himself, companies like Upstart (which I founded) and Pave make it easy for people to invest in other people.

 

Why is investing in people a safer bet? Because there are clear — and measurable — signals reflecting their accomplishments and hinting at their potential. It’s not unlike the logic used by big companies or universities faced with countless candidates, by recruiting firms and talent agents, and others. By using data and algorithms — in this case, a sophisticated regression model that considers variables like school, area of study, standardized test scores, internships, job offers — we can statistically predict a person’s future income.

 

Such a model allows a person to “borrow” from his or her future self.

In this way, platforms that crowdfund people assist in allocating capital to individuals who are statistically more likely to do compelling things with that capital. (For us, the model is simple: Backers contribute toward a person’s funding goal and receive in return a small slice of that person’s income for 10 years.)

 

Making more capital available to more of the world — as long as it’s offered on fair and reasonable terms — seems to be a universal good. In purely economic terms, current crowdfunding returns are considered mere rounding errors in the capital markets of today. But newer, smarter, and more efficient forms of financing will certainly drive lower returns for incumbents.

 

The real disruption and impact of crowdfunding won’t be understood for a decade or more. We’re only at the beginning. But it’s no longer an indie experiment, either.

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Animation shows LHC data processing | CERN

The Large Hadron Collider (LHC) produces millions of collisions every second in each detector, generating approximately one petabyte of data per second. None of today’s computing systems are capable of recording such rates, so sophisticated selection systems are used for a first fast electronic pre-selection, only passing one out of 10,000 events. Tens of thousands of processor cores then select 1% of the remaining events for analysis. Even after such drastic data reduction, the four big experiments, ALICE, ATLAS, CMS and LHCb, together need to store over 25 petabytes per year. The LHC data are aggregated in the CERN Data Centre, which performs initial data reconstruction is performed, and a copy is archived to long-term tape storage. Another copy is sent to several large data centres around the world.
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Case Study: How Content Diffuses Through Different Social Networks | Social Media Today

Case Study: How Content Diffuses Through Different Social Networks | Social Media Today | e-Xploration | Scoop.it
Users behave differently on different social media platforms. When a news story breaks it moves across social media in different pulses depending on what the news is and how it travels through these platforms like Twitter, Facebook and WordPress.
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The Atlas of Economic Complexity. Mapping paths to prosperity.

Scribd is the world's largest social reading and publishing site.
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The Modern Data Nerd Isn't as Nerdy as You Think

The Modern Data Nerd Isn't as Nerdy as You Think | e-Xploration | Scoop.it
Data scientists are fast becoming the rock stars of the 21st century. Thanks in part to Nate Silver's eerily accurate election predictions and Paul DePodesta's baseball-revolutionizing Moneyball techniques, math nerds have become celebrities.

Via Pierre Levy
luiy's insight:

Data scientists are fast becoming the rock stars of the 21st century. Thanks in part to Nate Silver’s eerily accurate election predictions and Paul DePodesta’s baseball-revolutionizing Moneyballtechniques, math nerds have become celebrities. It’s debatable how much their work differs from what statisticians have done for years, but it’s a growing field, and many companies are desperate to hire their own data scientists.

The irony is that many of these math nerds aren’t as math nerdy as you might expect.

 

Some of the best minds in the field lack the sort of heavy math or science training you might expect. Silver and Paul DePodesta have bachelor’s degrees in economics, but neither has a PhD. Former Facebook data scientist and Cloudera co-founder Jeff Hammerbacher — who helped define the field as it’s practiced today — only has a bachelor’s in mathematics. The top ranked competitor at Kaggle — which runs regular contest for data scientists — doesn’t have a PhD, and many of the site’s other elite competitors don’t either.

 

“In fact, I argue that often Ph.D.s in computer science in statistics spend too much time thinking about what algorithm to apply and not enough thinking about common sense issues like which set of variables (or features) are most likely to be important,” says Kaggle CEO Anthony Goldbloom.

 

Data scientist John Candido agrees. “An understanding of math is important,” he says, “but equally important is understanding the research. Understanding why you are using a particular type of math is more important than understanding the math itself.”

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Pierre Levy's curator insight, April 15, 2013 11:42 AM

Knowing the field is more important than knowing the math...

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Hive Plots - Visually Interpreting Network Structure and Content Made Possible

Hive Plots - Visually Interpreting Network Structure and Content Made Possible | e-Xploration | Scoop.it
luiy's insight:

To rationally visualize networks, we introduce the hive plot. The hive plot is based on meaningful network properties, which can be selected to address a specific question.

 

Nodes are assigned to one of three (or more) axes, which may be divided into segments. Nodes are ordered on a segment based on properties such as connectivity, density, centrality or quantitative annotation (e.g. gene expression). The user is free to choose whatever rules fit their data and visualization requirements. Edges are drawn as Bezier curves, which can be annotated with color, thickness or label to communicate additional information.

 

Hive plots make it possible to assess network structure because they are founded on network properties, not on aesthetic layout. Visualizations of two networks are directly comparable. Importantly, hive plots are perceptually uniform — differences in hive plots are proportional to differences in underlying networks. This makes it possible to use hive plots to assess network similarity.

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Behavior prediction software company Behavio now part of Google

Behavior prediction software company Behavio now part of Google | e-Xploration | Scoop.it

Behavio, a company that developed software capable of collecting smartphone data in order to certain predict behavior, is now part of Google.


Via LeapMind, Alessio Erioli, Andrea Graziano
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Jayne Fenton Keane's curator insight, April 17, 2013 5:41 PM

This is progressing fast

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Create a PDF e-book of tweets with tweetbook.in

Create a PDF e-book of tweets with tweetbook.in | e-Xploration | Scoop.it
Tweetbook.in lets you create and save a diary like PDF ebook of tweets. It is a simple app that lets you take a backup of your tweets and favourites. It is one of the earliest twitter backup applications.

Via Ana Cristina Pratas
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Cardiff Online Social Media Observatory (COSMOS): Social Media and Data Mining

Cardiff Online Social Media Observatory (COSMOS): Social Media and Data Mining | e-Xploration | Scoop.it
Project Information about the The SOCSI/COMSC Research Network, Cardiff School of Social Sciences at Cardiff University, Wales, UK.

Via Martin Weller
luiy's insight:

Cardiff Online Social Media Observatory (COSMOS) is an Economic and Social Research Council (ESRC) and Joint Information Systems Committee (JISC) half a million pound investment that brings together social, political, health, mathematical and computer scientists to study the methodological, theoretical, empirical and policy dimensions of Big ‘Social’ Data.   Our objective is to establish a coordinated international social science response to this new form of data in order to address next-generation research questions.

Our empirical research programme is contextualized in terms of the ‘coming crisis of empirical sociology’ (Savage and Burrows, 2007), which is located in the increasing asymmetry between traditional social scientific methods and the power of transactional data generated through the internet. This has led some commentators to question the extent to which university-based sociology and social science can compete with the data rich resources built into the marketing and data generation strategies of the large multi-national corporations that hold and marshal much of this transactional data.

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#baidu : 'Chinese Google' Opens research lab dedicated to “deep learning”

#baidu : 'Chinese Google' Opens  research lab dedicated to “deep learning” | e-Xploration | Scoop.it
Wired (blog) 'Chinese Google' Opens Artificial-Intelligence Lab in Silicon Valley Wired (blog) The artificial intelligence community moved toward systems that solved problems by crunching massive amounts of data, rather than trying to build “neural...

Via RomanGodzich
luiy's insight:

It doesn’t look like much. The brick office building sits next to a strip mall in Cupertino, California, about an hour south of San Francisco, and if you walk inside, you’ll find a California state flag and a cardboard cutout of R2-D2 and plenty of Christmas decorations — even though we’re well into April.

 

But there are big plans for this building. It’s where Baidu — “the Google of China” — hopes to create the future.

In late January, word arrived that the Chinese search giant was setting up a research lab dedicated to “deep learning” — an emerging computer science field that seeks to mimic the human brain with hardware and software — and as it turns out, this lab includes an operation here in Silicon Valley, not far from Apple headquarters, in addition to a facility back in China. The company just hired its first researcher in Cupertino, with plans to bring in several more by the end of the year.

Baidu calls its lab The Institute of Deep Learning, or IDL. Much like Google and Apple and others, the company is exploring computer systems that can learn in much the same way people do. “We have a really big dream of using deep learning to simulate the functionality, the power, the intelligence of the human brain,” says Kai Yu, who leads Baidu’s speech- and image-recognition search team and just recently made the trip to Cupertino to hire that first researcher. “We are making progress day by day.”

If you want to compete with Google, it only makes sense to set up shop in Google’s backyard. “In Silicon Valley, you have access to a huge talent pool of really, really top engineers and scientists, and Google is enjoying that kind of advantage,” Yu says. Baidu first opened its Cupertino office about a year ago, bringing in various other employees before its big move into deep learning.

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#DataScience : WEKA, for Waikato Environment for Knowledge - Machine Learning Group

#DataScience : WEKA, for Waikato Environment for Knowledge - Machine Learning Group | e-Xploration | Scoop.it
luiy's insight:

An exciting and potentially far-reaching development in computer science is the invention and application of methods of machine learning (ML). These enable a computer program to automatically analyse a large body of data and decide what information is most relevant. This crystallised information can then be used to automatically make predictions or to help people make decisions faster and more accurately.

Project Objectives

Our objectives are to

make ML techniques generally available;apply them to practical problems that matter to New Zealand industry;develop new machine learning algorithms and give them to the world;contribute to a theoretical framework for the field.

 

Software

Our team has incorporated several standard ML techniques into a software "workbench" called WEKA, for Waikato Environment for Knowledge Analysis. With it, a specialist in a particular field is able to use ML to derive useful knowledge from databases that are far too large to be analysed by hand. WEKA's users are ML researchers and industrial scientists, but it is also widely used for teaching. Recently, our team has also worked on MOA, an environment for mining data streams.

 

http://es.wikipedia.org/wiki/Weka_(aprendizaje_autom%C3%A1tico)

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Has the design professional become a dinosaur?

Has the design professional become a dinosaur? | e-Xploration | Scoop.it

In this day and age, is there a need for design professionals? Is DIY the wave of the future?


Via Luca Baptista
luiy's insight:

The amount of information available through the websites of architects and interior designers, social media sites, online communities, blogs and reality shows gives consumers unprecedented access to the world of design. Add to that lifestyle retailers, and it appears we can assemble everything  we need to outfit a home, remodel it or even build it from the ground up. Even though statistical evidence shows that costs escalate as much as 40% compared to what it would cost if hiring a design professional, most DIYers would do it all over again.

 

DESIGNOSAURUS REX

 

There is also the reality that design professionals charge fees, and paying fees is like paying more taxes, it chips away some more at our hard earned money. An attorney, dentist, plumber or electrician also provide specialized services, which we need from time to time. Do you ever really need a design professional?

 

With tangible evidence to the contrary, why should you hire a design professional?

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Jusqu'où vont vos tweets ? Découvrez-le via une sublime visualisation de données

Jusqu'où vont vos tweets ? Découvrez-le via une sublime visualisation de données | e-Xploration | Scoop.it
Comment se propage un tweet ? Des français lancent Where Does My Tweet Go? pour vous aider à visualiser l'impact d'un message publié sur Twitter.
luiy's insight:

Benoît Vidal, en charge du digital chez MFG Labs, est venu vers moi avec deux références qui ne pouvaient que piquer mon intérêt.

 

En effet, il a d’un côté participé très tôt à l’aventure Cinémur et de l’autre co-fondé Dataveyes (qui est finaliste du concours start-up Presse-Citron ).

 

C’est aujourd’hui avec la casquette d’architecte de l’information pour MFG Labs qu’il m’a proposé de découvrir Where Does My Tweet Go (ou WDMTG pour faire court).

 

Qu’est-ce que « Where Does My Tweet Go » ?

Benoît Vidal : « WDMTG propose une nouvelle expérience digitale pour découvrir les tweets les plus intéressants, via un « algorithme visualisé » appelé SpreadRank.


Le SpreadRank permet de déterminer les tweets qui propagent le plus à travers le réseau. Nous visualisons l’algorithme pour éviter l’effet « boîte noire » des services de personnalisation et recommandation plus classiques (Zite, etc).


Le SpreadRank s’avère très efficace et permet de différencier fortement les tweets beaucoup retweetés mais seulement à travers leur communauté (exemple : un tweet de Justin Bieber) versus les tweets avec une vraie valeur informationnelle qui propagent fortement (exemple : arrestation de DSK à New-York).


En somme, WDMTG permet de comprendre comment un message se propage sur twitter, et intéresse de fait fortement les marques. »

Comment est née l’idée de WDMTG ?

Benoît : L’idée est née de la volonté de montrer et de mesurer la puissance virale d’un message sur un réseau comme twitter, le réseau social où l’information propage comme sur aucun autre réseau. C’est en visualisant cette propagation que le SpreadRank est né. La visualisation nourrit l’algorithme et non le contraire.


À l’inverse de Klout, nous ne calculons pas un score sur les personnes, mais sur les messages. Bien sûr, l’influence d’une personne joue dans la vie d’un tweet, mais observer la pénétration d’un message à travers le réseau est bien plus pertinent ; les messages avec un SpreadRank élevé ont de fait plus d’impact.

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Clinical Oncology News - Artificial Intelligence Comes to Cancer Care

Clinical Oncology News - Artificial Intelligence Comes to Cancer Care | e-Xploration | Scoop.it

Two years after beating human champions on “Jeopardy!,” the cognitive computing system IBM Watson is ready for a new challenge: advising clinicians on the treatment of cancer. Announced on Feb. 8 by partners IBM, WellPoint, Inc., and Memorial Sloan-Kettering Cancer Center, the new venture is one of the first commercially developed Watson-based products. Also announced at the same time is a set of utilization management tools to streamline the review process between patients’ physicians and health plans.

Using advances in natural language processing and analytics, Watson is able to process information in a way similar to how people think, according to a press release from the partners. Since its appearance on “Jeopardy!,” Watson has improved by 240% in system performance.

The Watson product in oncology, called Interactive Care Insights for Oncology, provides a Watson-based advisor, accessible through the cloud, that is intended to help identify individualized treatment options for patients with cancer, starting with lung cancer, according to the press release. In principle, oncologists anywhere will be able to access detailed treatment options to help them decide how best to care for a patient.

 


Via Wildcat2030
luiy's insight:

Using advances in natural language processing and analytics, Watson is able to process information in a way similar to how people think, according to a press release from the partners. Since its appearance on “Jeopardy!,” Watson has improved by 240% in system performance.

 

The Watson product in oncology, called Interactive Care Insights for Oncology, provides a Watson-based advisor, accessible through the cloud, that is intended to help identify individualized treatment options for patients with cancer, starting with lung cancer, according to the press release. In principle, oncologists anywhere will be able to access detailed treatment options to help them decide how best to care for a patient.

To prepare for its work in oncology, Watson has taken in more than 600,000 pieces of medical evidence, and 2 million pages of text from 42 medical journals and clinical trials, the press release states. Watson is able to search through 1.5 million patient records and provide physicians with evidence-based treatment options in seconds.

 

In less than a year, Memorial Sloan-Kettering in New York City has immersed Watson in the complexities of cancer and genetic research. Starting with 1,500 lung cancer cases, the medical center’s clinicians and analysts are training Watson to extract and interpret physician notes, lab results and clinical research, while sharing their expertise and experiences in treating patients with cancer.

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Facebook folly: what if social networks don't understand estrangement needs?

Facebook folly: what if social networks don't understand estrangement needs? | e-Xploration | Scoop.it
My mother popped up on Facebook a few months ago as a "suggested friend". Her smile came up on the side of my screen, and I couldn't help but let my mouse gravitate to her name and linger over it. With most people, if their mothers are already on Facebook then they're already "friends". But I became estranged from my parents half a decade ago, and hadn't exchanged words with my mother for over four years. At a time when there's so much discussion about a "right to be forgotten" and methods to delete your digital life, I've done a lot to digitally forget my parents, and delete them from my digital life. I'd rejected invitations to connect from their work colleagues and friends so that snippets of their life wouldn't flash incidentally into mine and tempt me to linger.
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Nathan Awaits... - AI for everyone.

Nathan Awaits... - AI for everyone. | e-Xploration | Scoop.it
Want to add artificial intelligence to your software? Now you can. Visit {REFURL} to sign up for free beta test.
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MOOC Mania: Debunking the hype around massive open online courses - The Digital Shift

MOOC Mania: Debunking the hype around massive open online courses - The Digital Shift | e-Xploration | Scoop.it

Via L. García Aretio
luiy's insight:

But it wasn’t just the tools that were different, the academic backgrounds of the professors behind these innovations were different, too. They were largely from the field of education rather than computer science, and the emphasis was on building learning networks and communities—and helping learners think about how to negotiate online learning spaces—and not simply on replicating or scaling the content delivery of typical engineering courses.

 

It’s interesting that this origin of MOOCs remains largely ignored (and unfortunate as there are decades of experience from those who’ve taught online and taught with technology that are being left out of many of these discussions), but it’s not particularly surprising. MOOC mania taps into powerful narratives—both true and false—about the relevancy of the curriculum, the cost of college, and the adaptability of education institutions. Many institutions are joining MOOCs, hoping that the mania pans out and that these free online classes will, if nothing else, keep their brands up-to-date. But the questions about who exactly they’re serving with these classes will have to be answered sooner or later as having tens of thousands of students sign up for a class is hardly the right metric upon which to build the future of education.

 

As K–12 schools begin to investigate MOOCs—weighing their potential benefits and challenges—it will be crucial to ask questions about course completion and student success. While these online classes might offer a way to deliver online education to the masses, it will be just as important—if not more so—to think through how we can provide massive student support.

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Data Visualization, Design and Information Munging // Martin Krzywinski / Genome Sciences Center

Data Visualization, Design and Information Munging // Martin Krzywinski / Genome Sciences Center | e-Xploration | Scoop.it
luiy's insight:
HE ART OF π, φ AND e

Numerology is bogus, but art based on numbers has a beautiful random quality.

 

For other examples of numerical art, see my inessiness project. Nixie clock lovers should investigate theaccidental similarity number.

ART OF π

Cristian Ilies Vasile had the idea of representing the digits of π as links that connected segments associated with successive digits. The image is composed of links (segment:position) 3:0 → 1:1 → 4:2 → 1:3 → 5:4 …

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Oycib. Collaborative infrastructure for e-Research. by @luiy

Oycib. Collaborative infrastructure for e-Research. by @luiy | e-Xploration | Scoop.it
luiy's insight:

The Oycib infrastructure is based in an ethnographic observation model based agents called e-Xploration. The infrastructure allows the analysis, interpretation and visualization of profiles and digital practices.

 

The proposed profiles analysis is based on the metaphor of Maya social organization.

 

Furthermore, we propose work in the context-awareness to enhance the collaboration and cooperation among people and groups.

 

This infrastructure is developed with different systems based on OPEN philosophies, such as: ELGG, SCi2, GEPHI and SIGMA.

 

Finally, the Oycib project is developed in an international context with institutions in Mexico and Spain: Universidad Autónoma del Estado de Hidalgo (UAEH), Barcelona Tech (UPC) and Consejo Nacional de Ciencia y Tecnología (CONACYT).

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Emergency Situation Awareness tool for social media | CSIRO

Emergency Situation Awareness tool for social media | CSIRO | e-Xploration | Scoop.it
Social media channels provide a new, rich source of information from which disaster managers and emergency response agencies can obtain real-time awareness of developing situations.
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Digital Social Research

Digital Social Research | e-Xploration | Scoop.it
Harnessing technology for Social Science Research
luiy's insight:
What is Digital Social Research

New Data. ‘Born-digital’ data sources including social transactional data. Ease of access to secure data.

New Methods. Taking advantage of new data and infrastructure, collaboration, and new forms of interpretative research.

New Capability. Increased capability in tools, resources and services and the emerging
e-Infrastructure.

New Studies. Study of e‑Science, understanding innovation pathways and assessment of impact.

New Practice. Increasing scale and diversity of information and range of collaborative tools, evolving publishing models.

New Scale. Increasing internationalisation and interdisciplinary working.

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What do you mean... open?... from Davecormier.com

What do you mean... open?... from Davecormier.com | e-Xploration | Scoop.it

Via Pierre Levy
luiy's insight:

This post is a mixture of my own research and lots of v. interesting input I’ve gotten from colleagues on Twitter. I’ll make my best effort to mention those people who contributed… feel free to let me know if I’ve forgotten you...

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Pierre Levy's curator insight, April 12, 2013 11:23 AM

The story that I’m trying to tell here is about the values that underpin the word ‘open’. I know many of the people involved in open education/learning/educational resources as deeply principled people who are engaged in the idea of openness for reasons that are important to them. In examining these values i have found two strands: one openness that speaks of valuing the creator/teacher/artifact, and another sense of openness that speaks of the user/learner. Most of us, I would imagine, borrow from both sides. But this story is particularly about how the ideas of around ‘open source’ influence a pull towards valuing the creator over the user, and how that pull might affect the field of learning going forward

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Citizen science: Amateur experts

Equipped with smartphones, computers and do-it-yourself sampling kits, lay volunteers are tweeting about snowfall, questing for comets and measuring the microbes in their guts. They are part of a growing group of 'citizen scientists', networks of non-scientists who help to analyse or collect data as part of a researcher-led project. They learn about science and get a chance to participate, but the scientists involved stand to gain too.

 

Citizen science: Amateur experts

Trisha Gura
Nature 496, 259–261 (11 April 2013) http://dx.doi.org/10.1038/nj7444-259a


Via Complexity Digest
luiy's insight:

Publications using data from citizen science are becoming more common, and even encouraged. Researchers at Princeton University in New Jersey, for example, have used data from Nature's Notebook to expand a model of the timing of leaf-bud bursting from the Harvard Forest area in Massachusetts to the entire eastern seaboard of the United States. The team published its expanded model this year (S.-J. Jeonget al. Geophys. Res. Lett. 40, 359–364; 2013). Not only did peer reviewers welcome the citizen-science data, but one actually gave advice on how to use the citizen-science model more effectively, says Weltzin.

 

If all goes well, citizen science is a way to communicate science, engage in outreach and accomplish research aims. “You are getting the information that you need at the same time that you are getting people involved,” says Weltzin. “It is like playing Whack-a-Mole with all hammers out. You meet all of your objectives at one time.”

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Adam Smith hates Bitcoin

Adam Smith hates Bitcoin | e-Xploration | Scoop.it

Paul Krugman blazes a high-tech path to the 18th century.


Via Luca Baptista
luiy's insight:

There have been many good pieces written on the dubious economics of Bitcoin; I especially liked this one by Neil Irwin. One thing I haven’t seen emphasized, however, is the extent to which the whole concept of having to “mine” Bitcoins by expending real resources amounts to a drastic retrogression — a retrogression that Adam Smith would have scorned.

Smith actually wrote eloquently about the fundamental foolishness of relying on gold and silver currency, which — as he pointed out — serve only a symbolic function, yet absorbed real resources in their production, and why it would be smart to replace them with paper currency:

The gold and silver money which circulates in any country, and by means of which, the produce of its land and labour is annually circulated and distributed to the proper consumers, is, in the same manner as the ready money of the dealer, all dead stock. It is a very valuable part of the capital of the country, which produces nothing to the country. The judicious operations of banking, by substituting paper in the room of a great part of this gold and silver, enable the country to convert a great part of this dead stock into active and productive stock; into stock which produces something to the country. The gold and silver money which circulates in any country may very properly be compared to a highway, which, while it circulates and carries to market all the grass and corn of the country, produces itself not a single pile of either. The judicious operations of banking, by providing, if I may be allowed so violent a metaphor, a sort of waggon-way through the air, enable the country to convert, as it were, a great part of its highways into good pastures, and corn fields, and thereby to increase, very considerably, the annual produce of its land and labour.

And now here we are in a world of high information technology — and people think it’s smart, nay cutting-edge, to create a sort of virtual currency whose creation requires wasting real resources in a way Adam Smith considered foolish and outmoded in 1776.

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BigML - Create a Model then Generate a Prediction

BigML - Create a Model then Generate a Prediction | e-Xploration | Scoop.it
BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.

Via Ana Cristina Pratas
luiy's insight:

BigML's predictive models will show you the patterns that are hidden in your data. You can adjust the granularity of the model by using the "live pruning" slider to prune away branches with less data, allowing you to focus on the most common cases, or explore fine details. Click on a decision node and follow the path to increasingly more specific cases by following the "branches" downward. See which values create the split points at every node. At every node, the model shows what the most likely prediction is.

 

 

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Jean Jacoby's curator insight, April 28, 2013 4:33 PM

Not sure that I'd ever need to use this, but wow, it looks impressive!