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Spanish telecomm regulator launches data visualization tool | European Public Sector Information Platform #opendata

Spanish telecomm regulator launches data visualization tool | European Public Sector Information Platform #opendata | Public Datasets - Open Data - | Scoop.it

Via Ivan Begtin
luiy's insight:

Inspired by EU Digital Agenda Scoreboard tool for indicators' data graphing, the Spanish telecommunications regulator "Comisión del Mercado de las Telecomunicaciones" (CMT) has opened up a space on its own public data portal CMTDATA for data visualization. The aim is to provide visual reporting on telecommunications services and infrastructure in provinces and autonomous regions. The data used for each graph is provided in the annual Sectoral Economic Report, and can also be downloaded in CSV, XLS and PDF file formats.


http://cmtdata.cmt.es/cmtdata/

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Open Data and Preservation | The Signal: Digital Preservation

Open Data and Preservation | The Signal: Digital Preservation | Public Datasets - Open Data - | Scoop.it

Yesterday, May 9, 2013, the U.S. government issued an executive order and an open data policy mandating that federal agencies collect and publish new datasets in open, machine-readable, and, whenever possible, non-proprietary formats.  The new policy gives agencies six months to create an inventory of all the government-produced datasets they collect and maintain; a list of datasets that are publicly accessible; and an online system to collect feedback from the public as to how they would like to use the data.  The goals are twofold — greater access to government data for the public, and the availability of data in forms that businesses and researchers can better use.  This builds on the earlier White House Memorandum on Transparency and Open Government.

 

These documents were accompanied by a link to something that actually caught my fancy even more – a greatly expanded Project Open Data Github repository for guidelines, use cases and tools.  This, alongside the ever-growing (and soon to be extensively updated) data.gov, are evidence of real efforts to release more data and make it truly useful and usable.


Via Irina Radchenko
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Big Data et Data Scientists : un point de vue éclairant ...

La valorisation des données de l’entreprise ne saurait se réduire au simple enjeu technologique du Big Data. Pour éviter ce phénomène, l’exploitation de l’information doit être confiée à des Data Scientists capables d’appréhender la problématique dans toutes ses dimensions : métier, informatique, statistique et mathématique.


Via Pascal Hoguet, Lockall
luiy's insight:

L’idée n’est certes pas totalement nouvelle, mais, bénéficiant de l’attention médiatique portée au Big Data, c’est probablement la première fois qu’elle peut être placée de façon aussi centrale et à aussi haut niveau dans le débat. Au-delà du choix d’un outil ou d’une technologie nouvelle, la réflexion sur la place de la Data Science dans l’entreprise lui permet en effet de questionner ses pratiques, ses données et ses méthodes :

 

• Quels sont les processus sur lesquels une analyse fine de l’information permettrait d’être plus efficace (conception produit, marketing produit, relation client, vente en ligne, production opérationnelle, chaîne logistique, maintenance industrielle, gestion du risque financier, pilotage de la marge…) ?

• Quelles sont les données disponibles dans les systèmes d’information de l’entreprise, qui permettraient de répondre plus efficacement aux questions que se posent les pilotes de ces processus, et quelle est la nature de ces données (volume, qualité, variété…) ? À l’inverse, quelles sont les données non stockées dans les systèmes d’information, et qui permettraient pourtant d’enrichir fortement l’analyse métier (données de logs web, données issues de capteurs industriels…) ?

• Quelles sont les méthodes de traitement de l’information (analyse statistique, analyse numérique, intelligence artificielle, machine learning…) qui permettraient effectivement de transformer ces données en des réponses concrètes et opérationnelles aux questions posées par les pilotes de processus ?

Ces analyses et questionnements pourront effectivement conduire certaines entreprises à recourir aux nouvelles solutions technologiques offertes par le Big Data, et ce, notamment si les données à traiter sont volumineuses et peu structurées (texte, voix, image…), et si les processus métier qu’elles doivent éclairer imposent des exigences de traitement rapide (voire en temps réel).

 

Embauchez une équipe de Data Scientists

Conduire efficacement un projet Big Data est une tâche complexe, portant sur un périmètre vaste et touchant de très nombreux acteurs ; elle ne peut dès lors être confiée qu’à une figure triplement compétente : le Data Scientist. "Data Scientist" est un terme qui cristallise une série d’évolutions dans la pratique des "professionnels de l’exploitation de données" confrontés :

 

• D’une part à la progression rapide des moyens informatiques – hardware et software – mis à leur disposition,

 

• D’autre part au rôle grandissant que leur reconnaissent les départements opérationnels dans les prises de décision métier.

Dans ce contexte, le Data Scientist apparaît comme une synthèse de différentes compétences essentielles pour le projet Big Data, mais difficiles à réunir dans l’entreprise :

 

• Le Data Scientist comme mathématicien : parce qu’il choisit, adapte et applique des approches issues de domaines variés de la statistique et de l’intelligence artificielle pour extraire la valeur des données qu’il manipule, le Data Scientist doit être un mathématicien à même d’évaluer et de comparer différents modèles ou méthodes de calcul, d’en anticiper les avantages et les inconvénients, et de les exploiter en connaissance de cause dans un environnement très métier.

 

• Le Data Scientist comme informaticien : qu’il s’agisse d’extraire les données pertinentes des systèmes d’information, de programmer les algorithmes qui lui permettront de les traiter, ou d’aider à concevoir les plateformes qui faciliteront l’exploitation rapide des résultats obtenus, le Data Scientist se doit de maîtriser les langages de programmation et les environnements technologiques (en particulier ceux du Big Data) adaptés aux différents cas qu’il pourra rencontrer.

 

• Le Data Scientist comme expert métier : parce que ses analyses doivent être menées dans une logique de recherche d’efficacité et de rentabilité de l’entreprise, le Data Scientist doit nourrir un dialogue métier avec les pilotes de processus qu’il accompagne, et doit par ailleurs être force de proposition sur les stratégies à mettre en œuvre ou tactiques à adopter, eu égard aux enseignements qu’il tire de ses analyses. À ce titre, il ne peut être un simple expert technique, mais doit garder les yeux grands ouverts sur les enjeux Business de ses travaux.

 

Pour les décideurs désireux de ne pas manquer le virage du Big Data, le recrutement (ou l’identification dans les équipes en place), d’un ou plusieurs Data Scientists, semble donc être une condition incontournable du succès.

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Our Research | Data Sets | Intel Science & Technology Center for Big Data

Our Research | Data Sets | Intel Science & Technology Center for Big Data | Public Datasets - Open Data - | Scoop.it
luiy's insight:
Data Sets

A World of Geo-coded Tweets (Web/Social Media Data Analysis)

A data set that includes links to PostgresSQL dump files containing nearly all geo-tagged Tweets and associated metadata for the whole world, along with detailed instructions for restoring this data into a working database. The data is currently being used as input into MapD (Massively Parallel Database), which uses multiple GPUs to run SQL queries as well as render point and heat maps on the data in real time.

 

MIMIC II (Health Care)

Data from hospital ICU information systems, hospital archives and other external data sources. Created as part of a Bioengineering Research Partnership involving an interdisciplinary team from academia (MIT), industry (Philips Medical Systems) and clinical medicine (Beth Israel Deaconess Medical Center), with the goal of developing and evaluating advanced ICU patient monitoring systems that will substantially improve the efficiency, accuracy and timeliness of clinical decision-making in intensive care.

 

MODIS (Telescope/Satellite Imagery)

For our EarthDB project, we’re assembling a year’s worth of satellite imagery (from NASA’s MODIS instrument) for the whole globe.  Our goal is to develop new tools for creating derived data products from the raw data, rather than requiring scientists to use existing data exports that NASA provides. We are using the Level 1B NASA data (the lowest level of raw data that is geo-referenced), which lives here.  We use raw data at three spatial resolutions, available in sub-directories of the above link:  MOD021KM is 1km resolution, MOD02HKM is 500m resolution, and MOD02QKM is 250m resolution. We also use the MOD03 metadata (also available in a sub-directory), and metadata from here to discriminate between data acquired in daytime and nighttime.

 

University of Washington CoAddition Testing Use-Case (Astronomy/Telescope Imagery)

The Large Synoptic Survey Telescope (LSST) is a large-scale, multi-organization initiative to build a new telescope and use it to continuously survey the entire visible sky. The LSST will generate tens of TB of telescope images every night. The planned survey will cover more sky with more visits than any survey before. The novelty of the project means that no current dataset can exercise the full complexity of the data expected from the LSST. For this reason, before the telescope produces its first images in a few years, astronomers are testing their data analysis pipelines, storage techniques, and data exploration using realistic but simulated images. More information on the simulation process can be found in this paper.  This use-case provides a set of such simulated LSST images (approximately 1TB in binary format) and presents a simple but fundamental type of processing that needs to be performed on these images.

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The FTC says sneaky data brokers may illegally sell your data #dataawareness | Digital Trends

The FTC says sneaky data brokers may illegally sell your data #dataawareness  | Digital Trends | Public Datasets - Open Data - | Scoop.it
Some data brokers are up to no good. What you need to know about your data.
luiy's insight:

Absolutely nothing good. The FTC’s actions here are a necessary step, but more stringent action is required to actually curb the data brokerage industry. In an ideal world, these letters would absolutely require companies like Brokers Data and U.S. Data Corporation to stop offering consumer information to use in insurance decisions – which is what the FTC says they appear to be doing. And the letters would also make the six companies that appear to offer your information to employers stop doing that. These letters don’t legally compel these businesses, though, so they may take their chances until the FTC actually slams them with a fine. 

 

After all, if they don’t end up getting penalized, the rewards for being in the data brokerage industry are too great. It’s obvious that companies are hungry to use data to inform their marketing campaigns. Data brokerage is booming.  That’s why Facebook keeps tightening alliances with three of the largest data brokers in the U.S., Datalogix, Acxiom, and Epsilon. A small consolation is that none of the Facebook-affiliated data brokers received a warning letter. But that doesn’t mean they won’t in the future. 

The FTC has the power to fine data brokers who violate the FCRA, and it has in the past. Social media aggregator Spokeo settled with an $800,000 fine for selling information that violated the FCRA. And the FTC isn’t shy about issuing larger fines to big companies that run afoul of privacy regulations, as its $22.5 million penalty settlement with Google illustrates. 

So what can be done? Harsh fines are a good first step, but considering the vast potential for profit data brokers have, legislation will probably be more crucial to actually changing the brokerage industry. As Digital Trends’ Andrew Couts wrote earlier this year, “we need laws that empower consumers in the face of big data.” Couts suggested laws like California’s recently proposed bill, “The Right to Know Act 2013,” which would require companies to give up a year’s worth of personal data to people who wanted to see what they’ve collected. 

 

After all, the idea of collecting data that’s been voluntarily thrown into the digital ether isn’t an inherently evil pursuit – it’s more the fact that we aren’t told when and where our data is collected, and that most people don’t realize the extreme reach of these companies, that’s so troubling. At least the FTC warnings help people learn about which companies to investigate and look into ways to opt out of their specific programs. 



Read more: http://www.digitaltrends.com/social-media/watch-out-the-ftc-warns-sneaky-data-brokers-who-may-illegally-sell-your-data/#ixzz2Spohsdh2 ;
Follow us: @digitaltrends on Twitter | digitaltrendsftw on Facebook

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Learning Theory - What are the established learning theories?

Learning Theory - What are the established learning theories? | Public Datasets - Open Data - | Scoop.it
This Concept Map, created with IHMC CmapTools, has information related to: Learning Theory, zone of proximal development The area of capabilities that learners can exhibit with support from a teacher., Montessori constructivism, Lave & Wenger...

Via Juan Antonio Ortiz Caturani, L. García Aretio
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William Emeny's curator insight, May 9, 2013 12:55 PM

A stunning infographic summarising different theories of learning. This is amazing!

ELdEverdE's comment, May 10, 2013 5:21 AM
Excelent map to lead within the connected educational system. Thanks!
Joaquin J. Martínez's curator insight, May 10, 2013 9:41 AM

Excelente mapa para no perderse entre las teorías sobre el aprendizaje.

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The Future of Cities, Information, and Inclusion

The Future of Cities, Information, and Inclusion | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Over the next decade, cities will continue to grow larger and more rapidly. At the same time, new technologies will unlock massive streams of data about cities and their residents. As these forces collide, they will turn every city into a unique civic laboratory—a place where technology is adapted in novel ways to meet local needs. This ten-year forecast map, The Future of Cities, Information, and Inclusion (PDF), charts the important intersections between urbanization and digitalization that will shape this global urban experiment, and the key tensions that will arise. 

The explosive growth of cities is an economic opportunity with the potential to lift billions out of poverty. Yet the speed of change and lack of pro-poor foresight has led to a swarm of urban problems—poor housing conditions, inadequate education and health care, and racial and ethnic inequalities. The coming decade holds an opportunity to harness information to improve government services, alleviate poverty and inequality, and empower the poor. Key uncertainties are coming into view:

What economic opportunities will urban information provide to excluded groups?What new exclusions might arise from new kinds of data about the city and its citizens?How will communities leverage urban information to improve service delivery, transparency, and citizen engagement?

As information technology spreads beyond the desktop into every corner of citizens' lives, it will provide a new set of tools for poor and excluded groups to re-engineer their relationship with government, the built environment, and each other. 

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Roll your own maps: Mapbox wants to become the Wikipedia of cartography | Digital Trends

Roll your own maps: Mapbox wants to become the Wikipedia of cartography | Digital Trends | Public Datasets - Open Data - | Scoop.it
Google Maps may dominate the digital mapping space, but open-source mapping is coming up the rear with startup company MapBox is leading the way.

Via Miguel Mimoso Correia, Rui Guimarães Lima
luiy's insight:

The open-source mapping movement is bigger than you might think, burgeoning with underground tenacity and drive that feeds the user-generated machine. Digital map publishers, like Washington, D.C.-based startup MapBox, offer a more customizable alternative to mainstays like Google or Bing Maps that primarily provide its users with professionally curated content and navigation. Not only is MapBox one of the crowd-sourcing pioneers working to build a better breed of map, it’s actually doing it right and making a difference in the open-source mapping space.

 

The small, 25-person MapBox team has been working out of a garage, building mapping software using a combination of privately-purchased satellite data and open data from NASA, as well as a free user-maintained world map called OpenStreetMap. The collaborative project works in a similar fashion to Wikipedia – it can essentially be edited by anyone free of charge – allowing the software to be altered, updated, and user fact-checked on the fly for greater speed, convenience, and customization. 



Read more: http://www.digitaltrends.com/computing/roll-your-own-maps-mapbox-wants-to-become-the-wikipedia-of-cartography/#ixzz2SDw2JgcR ;
Follow us: @digitaltrends on Twitter | digitaltrendsftw on Facebook

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Linking open data to augmented intelligence and the economy - O'Reilly Radar

Linking open data to augmented intelligence and the economy - O'Reilly Radar | Public Datasets - Open Data - | Scoop.it

After years of steady growth, open data is now entering into public discourse, particularly in the public sector. If President Barack Obama decides to put the White House’s long-awaited new open data mandate before the nation this spring, it will finally enter the mainstream.

As more governments, businesses, media organizations and institutions adopt open data initiatives, interest in the evidence behind  release and the outcomes from it is similarly increasing. High hopes abound in many sectors, from development to energy to health to safety to transportation.

“Today, the digital revolution fueled by open data is starting to do for the modern world of agriculture what the industrial revolution did for agricultural productivity over the past century,” said Secretary of Agriculture Tom Vilsack, speaking at the G-8 Open Data for Agriculture Conference.

As other countries consider releasing their public sector information as data and machine-readable formats onto the Internet, they’ll need to consider and learn from years of effort at data.gov.uk, data.gov in the United States, and Kenya in Africa.


Via Irina Radchenko
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Oh the Places You'll Go: 38,000 Historical Maps to Explore at New Online Library

Oh the Places You'll Go: 38,000 Historical Maps to Explore at New Online Library | Public Datasets - Open Data - | Scoop.it
The Digital Public Library of America announces the addition of a vast treasure trove of maps.

Via Stillwater Historians
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Leoncio Lopez-Ocon's curator insight, May 3, 2013 8:21 AM

la magnífica colección de 38 mil mapas digitalizados de David Rumsey accesible en la Digital Public Libray of America

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Open Paca: Données

Open Paca: Données | Public Datasets - Open Data - | Scoop.it
luiy's insight:

En vue de favoriser le référencement et l'exploitation des jeux de données publiés sur le portail Open PACA, nous mettons à disposition des utilisateurs un listing des données contenant les métadonnées de chaque jeu de données publié. 

Ce catalogue est automatiquement mis à jour pour refléter l'actualité du portail.

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La « condition numérique » est-elle déjà définitive ?

La « condition numérique » est-elle déjà définitive ? | Public Datasets - Open Data - | Scoop.it

Aucune thèse dans « La Condition Numérique », l’essai de Jean-François Fogel et Bruno Patino paru en avril 2013 chez Grasset. En revanche se dégage une idée, celle que les dés de la révolution numérique sont désormais joués. Vraiment ?

 

Il y a les livres qui marquent une rupture. D’autres non.  »La condition numérique », un essai de Jean-François Fogel et Bruno Patino, paru chez Grasset, fait parti des seconds. Leur analyse de la transformation de la société sous l’effet d’internet est pourtant fort léchée, argumentée et documentée. Mais, aucune thèse ne vient grandir le lecteur, sauf peut-être celle que… les visionnaires, qu’ils invoquent, avaient raison. Et ils sont nombreux : Marshall McLuhan, William Gibson, Pierre Teilhard de Chardin, Jean Baudrillard, Vladimir Nabokov, Arthur C. Clarke, Jules Verne…


Via Lockall
luiy's insight:

ET SI LES DONNÉES DEVENAIENT UN BIEN PUBLIC

 

D’ailleurs, les lois qui régissent la manière de conduire une entreprise à l’heure digitale,seraient déjà écrites, voire figées : Loi 1 – le client c’est le produit ; Loi 2 – la gratuité est réglée d’avance ; Loi 3 – la valeur réside dans l’expérience ; Loi 4 – acheter n’implique pas posséder. Ces lois sont peut-être valables aujourd’hui, mais demain ? L’avènement d’un Internet des objets, où les machines prendraient en quelque sorte leur propre contrôle, risque de tout changer. Les lois édictées après vingt ans de développement public d’Internet et du Web pourraient être rendues obsolètes, ou, plus probables, être rejointes par de nouvelles. Or pas un mot dans cet essai. Les auteurs ne s’interrogent que sur l’éventuelle transformation des données en bien public. Même s’il s’agit « d’une hypothèse qui demeure politiquement enviable mais difficile à mettre en œuvre ». C’est leur seule concession aux futurs possibles. « Mais selon que les données resteront un bien privé ou deviendront bien commun ou bien public, la nature du capitalisme numérique sera changé : il sera hypercapitalisme, capitalisme régulé ou économie du partage. »

 

La condition numérique en serait donc, alors, elle aussi chamboulée. Car le réel n’est pas la connexion.« Il n’y a pourtant pas lieu de douter du réel : il reste présent, bien sûr, mais il n’est plus seul. […] Le réel, c’est le monde plus la connexion. » Additionner d’autres possibles est donc envisageable. Une thèse à creuser.

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What participants recommend you read before the conference | Governing Algorithms, #algorithms #PersonalData

What participants recommend you read before the conference | Governing Algorithms,  #algorithms #PersonalData | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Bibliography, links, articles and books about : bigdata, algorithms, personal Data, AI, etc, etc

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TIME and Space : Stunning Satellite Images of Earth | TIME.com

TIME and Space : Stunning Satellite Images of Earth | TIME.com | Public Datasets - Open Data - | Scoop.it
Exclusive timelapse: See climate change, deforestation and urban sprawl unfold as Earth evolves over 30 years.

Via Beth Dichter, mtmeme
luiy's insight:
TIME and Space | By Jeffrey Kluger

Spacecraft and telescopes are not built by people interested in what’s going on at home. Rockets fly in one direction: up. Telescopes point in one direction: out. Of all the cosmic bodies studied in the long history of astronomy and space travel, the one that got the least attention was the one that ought to matter most to us—Earth.

That changed when NASA created the Landsat program, a series of satellites that would perpetually orbit our planet, looking not out but down. Surveillance spacecraft had done that before, of course, but they paid attention only to military or tactical sites. Landsat was a notable exception, built not for spycraft but for public monitoring of how the human species was altering the surface of the planet. Two generations, eight satellites and millions of pictures later, the space agency, along with the U.S. Geological Survey (USGS), has accumulated a stunning catalog of images that, when riffled through and stitched together, create a high-definition slide show of our rapidly changing Earth. TIME is proud to host the public unveiling of these images from orbit, which for the first time date all the way back to 1984.

Over here is Dubai, growing from sparse desert metropolis to modern, sprawling megalopolis. Over there are the central-pivot irrigation systems turning the sands of Saudi Arabia into an agricultural breadbasket — a surreal green-on-brown polka-dot pattern in the desert. Elsewhere is the bad news: the high-speed retreat of Mendenhall Glacier in Alaska; the West Virginia Mountains decapitated by the mining industry; the denuded forests of the Amazon, cut to stubble by loggers.

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Beth Dichter's curator insight, May 12, 2013 10:57 PM

How did this come to be? The Landsat program. “Two generations, eight satellites and millions of pictures later, the space agency, along with the U.S. Geological Survey (USGS), has accumulated a stunning catalog of images that, when riffled through and stitched together, create a high-definition slide show of our rapidly changing Earth. TIME is proud to host the public unveiling of these images from orbit, which for the first time date all the way back to 1984.”

Google has taken these “choppy images” and upgraded them into stunning videos with incredible details (more information on this is at the website). TIME has also created a story that utilizes the videos and text to help understand the story they tell.
* Chapter 1 – Satellite Story

* Chapter 2 – Extreme Resources

* Chapter 3 – Climate Change

* Chapter 4 – Urban Explosion

It is said that a picture is worth a thousand words, and these moving images tell a story that is often hard to understand. If we are interested in learning more about how we have impacted our planet this is a great resource.

Tracy Shaw's curator insight, May 13, 2013 12:07 PM

Incredible images showing not only deforestation, but increase in urban sprawl & vanishing glaciers. 

Darren Smith's curator insight, May 13, 2013 6:38 PM

Wow!

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MIMIC II Health Databases #bigdata #clinicalData

MIMIC II Health Databases #bigdata #clinicalData | Public Datasets - Open Data - | Scoop.it
luiy's insight:

The MIMIC II (Multiparameter Intelligent Monitoring in Intensive Care) Databases contain physiologic signals and vital signs time series captured from patient monitors, and comprehensive clinical data obtained from hospital medical information systems, for tens of thousands of Intensive Care Unit (ICU) patients*. Data were collected between 2001 and 2008 from a variety of ICUs (medical, surgical, coronary care, and neonatal) in a single tertiary teaching hospital. The MIMIC II Clinical Database contains clinical data from bedside workstations as well as hospital archives. The MIMIC II Waveform Database includes records of continuous high-resolution physiologic waveforms and minute-by-minute numeric time series (trends) of physiologic measurements. Many, but not all, of the Waveform Database records are matched to corresponding Clinical Database records (for more information, see Record Matching). The databases are thoroughly de-identified (all PHI has been removed and all dates have been changed).

Both databases are distributed freely via PhysioNet. There are no restrictions on access to the MIMIC II Waveform Database. Access to the MIMIC II Clinical Database is available to qualified researchers who obtain human subjects training and sign a simple data use agreement (see Getting Access).

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Global Roads Open Access Data Set (gROADS), v1: Global Roads | SEDAC

Global Roads Open Access Data Set (gROADS), v1: Global Roads | SEDAC | Public Datasets - Open Data - | Scoop.it

The Global Roads Open Access Data Set, Version 1 (gROADSv1) was developed under the auspices of the CODATA Global Roads Data Development Task Group. The data set combines the best available roads data by country into a global roads coverage, using the UN Spatial Data Infrastructure Transport (UNSDI-T) version 2 as a common data model. All country road networks have been joined topologically at the borders, and many countries have been edited for internal topology. Source data for each country are provided in the documentation, and users are encouraged to refer to the readme file for use constraints that apply to a small number of countries. Because the data are compiled from multiple sources, the date range for road network representations ranges from the 1980s to 2010 depending on the country (most countries have no confirmed date), and spatial accuracy varies. The baseline global data set was compiled by the Information Technology Outreach Services (ITOS) of the University of Georgia. Updated data for 27 countries and 6 smaller geographic entities were assembled by Columbia University's Center for International Earth Science Information Network (CIESIN), with a focus largely on developing countries with the poorest data coverage.


Via Irina Radchenko
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Big data and the democratisation of decisions


Via Kenneth Mikkelsen
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Kenneth Mikkelsen's curator insight, April 10, 2013 8:14 PM
Great Report from The Economist Intelligence Unit.
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Big Data Brokers: They Know Everything About You and Sell it to the Highest Bidder

Big Data Brokers: They Know Everything About You and Sell it to the Highest Bidder | Public Datasets - Open Data - | Scoop.it
Data companies are scooping up enormous amounts of information about almost every American. They sell information about whether you're pregnant or divorced or trying to lose weight, about how rich you are and what kinds of cars you have.
luiy's insight:

So they don't sell information about my health?

Actually, they do.

Data companies can capture information about your "interests" in certain health conditions based on what you buy — or what you search for online. Datalogix has lists of people classified as "allergy sufferers" and "dieters." Acxiom sells data on whether an individual has an "online search propensity" for a certain "ailment or prescription."

Consumer data is also beginning to be used to evaluate whether you're making healthy choices.

 

One health insurance company recently bought data on more than three million people's consumer purchases in order to flag health-related actions, like purchasing plus-sized clothing, the Wall Street Journal reported. (The company bought purchasing information for current plan members, not as part of screening people for potential coverage.)

Spokeswoman Michelle Douglas said that Blue Cross and Blue Shield of North Carolina would use the data to target free programming offers to their customers.

 

Douglas suggested that it might be more valuable for companies to use consumer data "to determine ways to help me improve my health" rather than "to buy my data to send me pre-paid credit card applications or catalogs full of stuff they want me to buy."

 

Do companies collect information about my social media profiles and what I do online?

Yes.

As we highlighted last year, some data companies record — and then resell — all kinds of information you post online, including your screen names, website addresses, interests, hometown and professional history, and how many friends or followers you have.

Acxiom said it collects information about which social media sites individual people use, and "whether they are a heavy or a light user," but that they do not collect information about "individual postings" or your "lists of friends."

More traditional consumer data can also be connected with information about what you do online. Datalogix, the company that collects loyalty card data, has partnered with Facebook to track whether Facebook users who see ads for certain products actually end up buying them at local stores, as the Financial Times reported last year.

 

Is there a way to find out exactly what these data companies know about me?

Not really.

You have the right to review and correct your credit report. But with marketing data, there's often no way to know exactly what information is attached to your name — or whether it's accurate.

Most companies offer, at best, a partial picture.

While Acxiom lets consumers review some of the information the company sells about them, New York Times reporter Natasha Singer discovered this summer that only a sliver of information is shared, including whether you have a prison record or bankruptcy filings.

When Singer finally received her report, all it included was a record of her residential addresses.

Some companies do offer more access. A spokeswoman for Epsilon said it allows consumers to review "high level information" about their data — like whether or not you're listed as making a purchase in the "home furnishings" category. (Requests to review this information cost $5 and can only be made by postal mail.)

RapLeaf, a company that advertises that it has "real-time data" on 80 percent of U.S. email addresses, says that it gives customers "total control over the data we have on you," and allows them to review and edit the categories (like "estimated household income" and "Likely Political Contributor to Republicans") that RapLeaf has connected with their email addresses.

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Social data: el papel de la Administración en la sociedad del dato

Social data: el papel de la Administración en la sociedad del dato | Public Datasets - Open Data - | Scoop.it
Las políticas de apertura de datos públicos tienen dos vertientes: open data: la tarea de las Administraciones públicas de abrir sus datos reutilización: la tarea de la sociedad de generar valor a ...

Via juandoming
luiy's insight:
Sociedad reutilizadora

El papel de la Administración pública no termina con la puesta en marcha de un servicio de datos abiertos; antes bien, debe dedicar importantes esfuerzos a la promoción de la reutilización, tanto en su apartado democrático como económico.

Empoderamiento social: la razón de liberar datos para la transparencia es rendir cuentas para que la ciudadanía pueda ejercer un papel de control social; esto precisa de una sociedad educada y corresponsable.Promoción económica: los emprendedores, las investigadoras y las empresas no están todavía en la clave de la reutilización; son precisas políticas de promoción para empezar a sacar partido a los datos.Contexto: democracia y economía

Las políticas de open data no saturan todo el campo del Gobierno abierto, pero asientan la base para la rendición de cuentas, las transparencia y la capacitación ciudadana. Sobre estos cimientos, la participación y la colaboración pueden alzarse firmes.

Un estado de apertura de datos no sólo facilita materia prima para la innovación y la puesta en marcha de nuevos servicios, sino que nivela el campo de juego, permitiendo unacompetencia más perfecta gracias a la igualdad de acceso a la información.

Parece que Europa se encamina hacia la consideración de la reutilización como un derecho de la ciudadanía. Es el momento de que todas las Administraciones públicas empiecen a caminar, de acuerdo entre ellas y siguiendo las necesidades de la ciudadanía.

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Social Network Analysis Interactive Dataset Library - Dynamics Lab @ UCD


Via ukituki
luiy's insight:

About the Social Network Analysis Interactive Dataset Library

This site contains an accessible library of many of the 'open' social network analysis datasets . This library of datasets is open to all, and anyone can add datasets - as a consequence the quantity and quality of the library is growing pretty quickly.

 

This interactive library provides researchers with an accessible overview of the different type of open social network datasets available. It was initially developed as part of a research project to outline the different types of social network datasets at the Dynamics lab in University College Dublin. As of our launch data (April 2013) some datasets have had their features extensively catalogued, while others have just the bare minimum details.

In total there are currently 173 Networks in the library. New datasets can be added by anyone (beginning here) and existing datasets can be edited on their overview page (for an example, see here).

 

There is a tabular view (summary), an interactive visualisation, or you can simply download all the library data. Note that this is an ongoing effort, and there are many publicly available network datasets not yet captured here, and some of the datasets captured within have not had their details populated yet.

 

Our objective is to create a open resource that contains information about available social network datasets, including the key features (e.g. are the networks multimodal, bipartite, multiplex, dynamic etc.) and size (number of nodes, number of edges). This resource will prove useful to both those beginning to think about social networks and those who may be seeking a dataset of very specific structure / size (e.g. in order to test an algorithm).

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ukituki's curator insight, May 3, 2013 9:38 AM

This interactive library provides researchers with an accessible overview of the different type of open social network datasets available. It was initially developed as part of a research project to outline the different types of social network datasets at the Dynamics lab in University College Dublin. As of our launch data (April 2013) some datasets have had their features extensively catalogued, while others have just the bare minimumdetails.

BESegal's curator insight, May 4, 2013 9:40 AM

If you do social network analysis #SNA here's a source of free data sets.

 

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Thematic mapping blog: Norway will open its topographic datasets to the public!

Thematic mapping blog: Norway will open its topographic datasets to the public! | Public Datasets - Open Data - | Scoop.it

Via Ivan Begtin
luiy's insight:

The topographic datasets at 1:50,000 scale will be freely available later this year, together with address, road and cadastre data. A database of 950,000 place names was released to the public one month ago. Hopefully, digital elevation data will be free as well, but it's not yet stated.

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The Value of Big Data Isn't the Data

The Value of Big Data Isn't the Data | Public Datasets - Open Data - | Scoop.it

It is clear that a new age is upon us. Evidence-based decision-making (aka Big Data) is not just the latest fad, it's the future of how we are going to guide and grow business. But data itself isn't the solution. It's just part of the path to that solution.


Via Kenneth Mikkelsen
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Rim Riahi's curator insight, May 2, 2013 6:18 AM

It is clear that a new age is upon us. Evidence-based decision-making (aka Big Data) is not just the latest fad, it's the future of how we are going to guide and grow business. But data itself isn't the solution. It's just part of the path to that solution.

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Une cartographie des livres en bibliothèque

Une cartographie des livres en bibliothèque | Public Datasets - Open Data - | Scoop.it
Bonjour ! Tout d'abord, toutes nos excuses pour le peu de mouvements sur ce blog, et l'absence d'évènements grand public autour de l'open data sur Rennes. Ces évènements vont prochainement revenir,...
luiy's insight:
Une carte de la bibliothèque des Champs Libres

La bibliothèque des Champs Libres à Rennes s’étend sur six étages et dispose de plus de 200 000 documents en libre accès. Notre idée de départ était de cartographier la bibliothèque afin de pouvoir repérer l’emplacement de chaque livre. Par exemple, après une recherche dans le catalogue, pouvoir indiquer au lecteur que l’ouvrage se trouve non seulement aux Champs Libres, mais à tel étage, et pourquoi pas dans telle étagère, tel rayon ?

 

Et ensuite ?

Ce petit projet est une très bonne expérimentation du principe de crowdsourcing, c’est à dire que les habitants peuvent aller directement chercher et construire les données. Il est facilement reproductible dans d’autres bibliothèques, d’autres lieux…

De notre côté, le travail n’est pas fini : nous souhaitons aller jusqu’au bout de l’idée et proposer des prototypes de représentations des données ou d’applications. Il nous reste donc plusieurs étapes :

Finir de collecter les cotes sur les autres étagesEntrer ces informations dans une base de données structuréeRelier les cotes entrées avec la classification Dewey afin de pouvoir manipuler des thématiques compréhensibles et non plus des chiffres (d’ailleurs, nous cherchons toujours une version brute des quatre premiers niveaux Dewey, en xml ou csv par exemple, si un de nos lecteurs a ça sous la main  )Concevoir et réaliser des visualisations avec ces données, en nous appuyant sur les idées et besoins des utilisateurs des bibli, mais aussi des bibliothécaires eux-mêmesRenouveler l’expérience dans les autres bibliothèques de Rennes ?

Voilà pour un premier aperçu de nos préoccupations actuelles. Un évènement public sera organisé dans les prochains mois, et permettra aux personnes intéressées de voir l’avancement des projets et d’échanger avec nous et nos interlocuteurs à la Bibliothèque.

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Big data Compendium 2012 - 2013. NYT

Big data Compendium 2012 - 2013. NYT | Public Datasets - Open Data - | Scoop.it
A look back through the past year of New York Times coverage of the data deluge.

Via AnalyticsInnovations
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