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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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The #datascience ecosystem, part 3: Data applications | #openSource #tools

The #datascience ecosystem, part 3: Data applications | #openSource #tools | Public Datasets - Open Data - | Scoop.it
The third part in a series on the data science ecosystem looks at the applications that turn data into insights or models.
luiy's insight:
Open-source tools

Probably because this category has the most ongoing research, there is quite a rich collection of open-source modeling and insights tools. R is an essential tool for most data scientists and works both as a programming language and an interactive environment for exploring data. Octave is a free, open-source port of matlab that works very well. Julia is becoming increasingly popular for technical computing. Stanford has an NLP library that has tools for most standard language processing tasks. Scikit, a machine learning package for python, is becoming very powerful and has implementations of most standard modeling and machine learning algorithms.


In the end, data application tools are what make data scientists incredibly valuable to any organization. They're the exact thing that allows a data scientist to make powerful suggestions, uncover hidden trends and provide tangible value. But these tools simply don't work unless you have good data and unless you enrich, blend and clean that data.
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Collecting #Twitter Data: Storing Tweets in #MongoDB | #bigdata #NoSQL

luiy's insight:

In the first three sections of the Twitter data collection tutorial, I demonstrated how to collect tweets using both R and Python and how to store these tweets first as JSON files then having R parse them into a .csv file. The .csv file works well, but tweets don’t always make good flat .csv files, since not every tweet contains the same fields or the same structure. Some of the data is well nested into the JSON object. It is possible to write a parser that has a field for each possible subfield, but this might take a while to write and will create a rather large .csv file or SQL database.

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@DataFrance : Plateforme de visualisation de données ouvertes | #opendata #dataviz

@DataFrance : Plateforme de visualisation de données ouvertes | #opendata #dataviz | Public Datasets - Open Data - | Scoop.it
Éducation, économie, transports publics, etc. Visualisez facilement et partout en France plus de 50 jeux de données sur notre carte interactive.

 

Nous voulons faciliter l’accès à l'open data

Nous avons pour ambition de rendre accessible les données ouvertes au plus grand nombre via une interface simple de consultation. DataFrance s’inscrit dans le mouvement open data et veut contribuer à promouvoir une plus large ouverture des données dans l’intérêt de tout public.

luiy's insight:

Selection de données:

 

- Logement vacants à Paris

- Accesibilité aux médecins généralistes en Gironde

- Vols de voitures en France

- Lycées par taux de reussite au bac à Marseille

- Risque de séisme en France

- Musées de France à Lyon

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Comment publier les données des musées dans le Linked #OpenData ? | #DH

Comment publier les données des musées dans le Linked #OpenData ? | #DH | Public Datasets - Open Data - | Scoop.it

Cet article décrit le processus de publication des données de l'ensemble de la collection du Smithsonian American Art Museum  (SAAM), soit 41000 objets et 8000 artistes, dans le web des données liées et ouvertes.


Via François Le Pivain
luiy's insight:

Modéliser, Lier, Vérifier :

 

Les musées, à travers le monde, ont construit des bases de données avec des méta-données sur des millions d’objets, leur histoire, les personnes qui les ont créés et les entités qui les représentent, mais ces données sont stockées dans des bases de données propriétaires et ne sont pas immédiatement utilisables. Récemment, les musées ont adopté le web sémantique dans l'intention de rendre ces données accessibles.

 

Parmi les projets notables du Linked Open Data, on peut citer The Europeana project qui a publié les données de 1500 musées, librairies et archives en Europe, le musée d'Amsterdam qui a publié les données de 73000 objets et le LODAC museum qui a publié les données de 114 musées au Japon.

 

Mais l’expérience a montré que publier les données des musées dans le web des données liées et ouvertes était difficile : les bases de données sont larges et complexes, l’information est très variée d’un musée à l’autre et il s’avère difficile de les relier à d’autres jeux de données.

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#Commons Transition: Policy Proposals for an #Open Knowledge Society

#Commons Transition: Policy Proposals for an #Open Knowledge Society | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Commons Transition: Policy Proposals for an Open Knowledge Society is our free downloadable e-book. Featuring the three newly updated Commons Transition plans by Michel Bauwens, John Restakis and George Dafermos in an easy to read format, the book is also complemented with special introductory material by Michel Bauwens and John Restakis and an exclusive interview with Commons Transition researcher Janice Figueiredo.

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L'arbre de l'évolution à l'heure numérique | #dataviz #openscience

L'arbre de l'évolution à l'heure numérique | #dataviz #openscience | Public Datasets - Open Data - | Scoop.it
Quand Charles Darwin rencontre Larry Page Le premier arbre phylogénétique, tel qu'il apparaît en 1859 dans De l'origine des espèces au moyen de la sélection naturelle de Charles...

"Dessine-moi un mouton", demandait le Petit Prince à l'aviateur. La représentation graphique a toujours été vecteur de connaissance, mais aujourd'hui, dans une culture qui abandonne peu à peu l'écrit pour l'image, elle devient une composante essentielle de la transmission du savoir. Un second défi se dresse : comment rendre compte de la masse d'informations disponibles pour décrire fidèlement la complexité du monde dans lequel nous évoluons, et notamment la diversité de la biosphère ? La conjugaison de ces deux ambitions a donné naissance au projet OneZoom (www.onezoom.org), un outil numérique qui permet de visualiser une version numérique de l'arbre de la vie. Une immersion dans la biodiversité, et une belle invitation à la curiosité. (...)  - par Guillaume Frasca, La science infuse, 16/10/2012

 

Source : J. Rosindell et L.J. Harmon, OneZoom: A Fractal Explorer for the Tree of Life, PLoS Biology, 16 octobre 2012.


Via Julien Hering, PhD
luiy's insight:

The authors introduce a new phylogenetic tree viewer that allows interactive display of large trees. The key concept of our solution is that all the data is on one page so that all the user has to do iszoom to reveal it—hence the name OneZoom (http://www.onezoom.org). Our interface is analogous to Google Earth, where one can smoothly zoom into any local landmark from a start page showing the whole globe, recognizing familiar landmarks at different scales along the way (e.g., continents, countries, regions, and towns). Equivalently, OneZoom can zoom smoothly to one tip of the tree of life—say, human beings—passing the familiar clades of animals, vertebrates, mammals, and primates at different scales along the way

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The First Interactive Network and Graph Data #Repository with Interactive Graph Analytics and Visualization | #opendata #SNA

The First Interactive Network and Graph Data #Repository with Interactive Graph Analytics and Visualization | #opendata #SNA | Public Datasets - Open Data - | Scoop.it
The First Interactive Network Data Repository with Real-time Interactive Visualization and Analytics
luiy's insight:

Network Data Repository. Exploratory Analysis & Visualization.

 

A network and graph data repository containing hundreds of real-world networks and benchmark datasets. This large comprehensive collection of network graph data is useful for making significant research findings as well as benchmark data sets for machine learning and network science. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive graph analytics engine that allows for visualizing the structure of networks as well as many global graph statistics and local node level properties. 

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All the Open #Datasets from New York City Visualized in a Single View | #opendata #dataviz

All the Open #Datasets from New York City Visualized in a Single View | #opendata #dataviz | Public Datasets - Open Data - | Scoop.it
luiy's insight:

"Visualizing NYC's Open Data" [chriswhong.com] by self-proclaimed urbanist, map maker and data junkie Chris Wong provides a single view of the more than 1,100 open datasets made available by New York City.

 

The visualization of the "dataset of datasets" consists of a force-directed graph, of which the nodes are colored according to whether the according dataset is a table, chart, map, a file or a user-created view (colored blue).

 

The graph acts as an alternative portal to explore the available data, while demonstrating its scale and diversity.

 

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#DataMining: Practical Machine Learning #Tools and Techniques | #Weka #datascience #openaccess

#DataMining: Practical Machine Learning #Tools and Techniques | #Weka #datascience #openaccess | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Teaching material

 

Slides for Chapters 1-5 of the 3rd edition can be found here.

Slides for Chapters 6-8 of the 3rd edition can be found here

 

These archives contain .pdf files as well as .odp files in Open Document Format that were generated using OpenOffice 2.0. Note that there are several free office programs now that can read .odp files. There is also a plug-in for Word made by Sun for reading this format. Corresponding information is on this Wikipedia page.

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Google has #open sourced a #tool for inferring cause from correlations | #algorithms #datascience

Google has #open sourced a #tool for inferring cause from correlations | #algorithms #datascience | Public Datasets - Open Data - | Scoop.it
Google open sourced a new package for the R statistical computing software that’s designed to help users infer whether a particular action really did cause subsequent activity. Google has been using the tool, called CausalImpact, to measure AdWords campaigns but it has broader appeal.

Via Dominique Cardon
luiy's insight:

Google announced on Tuesday a new open source tool that can help data analysts decide if changes to products or policies resulted in measurable change, or if the change would have happened anyway. The tool, called CausalImpact, is a package for the R statistical computing software, and Google details it in a blog post.

 

According to blog post author Kay H. Brodersen, Google uses the tool — created it, in fact — primarily for quantifying the effectiveness of AdWords campaigns. However, he noted, the same method could be used to gauge everything from whether adding a new feature caused an increase in app downloads to questions involving events in medical, social or political science.

 

http://google.github.io/CausalImpact/

 

 

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Seven Ways to Create a Storymap | #opendata #maps #ddj

Seven Ways to Create a Storymap | #opendata #maps #ddj | Public Datasets - Open Data - | Scoop.it
Evidence is Power
luiy's insight:

The above examples describe a wide range of geographical and geotemporal storytelling models, often based around quite simple data files containing information about individual events. Many of the tools make a strong use of image files as pat of the display. it may be interesting to complete a more detailed review that describes the exact data models used by each of the techniques, with a view to identifying a generic data model that could be used by each of the different models, or transformed into the distinct data representations supported by each of the separate tools.


- See more at: http://schoolofdata.org/2014/08/25/seven-ways-to-create-a-storymap/#sthash.tWi68hgm.dpuf

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The #OpenData Research network | #opengov

The #OpenData Research network | #opengov | Public Datasets - Open Data - | Scoop.it
luiy's insight:

The Open Data Research network.

 

Governments, civil society organisations and companies across the world are actively engaging with open data: publishing and using datasets to promote innovation, development and democratic change.

 

The Open Data Research network has been established to connect researchers from across the world working to explore the implementation and impact of open data initiatives. It is a joint project of IDRC and the Web Foundation, and is seeking to develop wider partnerships over the coming year.

 

The network currently hosts the 'Exploring the Emerging Impacts of Open Data in Development Countries (ODDC)' programme.

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Digital Ecologies Research Partnership | #openResearch #opendata

Digital Ecologies Research Partnership | #openResearch #opendata | Public Datasets - Open Data - | Scoop.it
The Digital Ecologies Research Partnership (DERP) is a joint initiative to promote academic inquiry into social dynamics of the web.
luiy's insight:

Launched in 2014, the Digital Ecologies Research Partnership (DERP) is a joint initiative by an alliance of community websites to promote open, publicly accessible, and ethical academic inquiry into the vibrant social dynamics of the web.

 

DERP seeks to solve two problems in the academic research space:

 

First, it is difficult for academic researchers to easily obtain data for their work beyond the confines of the largest social media platforms. DERP is a single point of contact for researchers to get in touch with relevant team members across a range of different community sites. We envision that this will lower the friction to investigating these sites in more depth, and broaden the scope of research happening within the academic community.

 

Second, it remains difficult to conduct good cross-platform analyses in academic research. By bringing a number community of sites together under a single cooperative effort, we intend to lower the friction of doing so, as well as better enable the sites themselves to coordinate with one another on supporting researchers.

 

DERP focuses on providing public data to academic researchers while facilitating an active online research community of Fellows. DERP will only support research that respects user privacy, responsibly uses data, and meets IRB approval. All research supported by DERP will be released openly and made publicly available. Partner platforms may also have additional guidelines and privacy commitments that apply to the research they support.

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Twitter Data Mining Round Up | #python #ddj #openaccess

Twitter Data Mining Round Up | #python #ddj #openaccess | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Since the release of Mining the Social Web, 2E in late October of last year, I have mostly focused on creating supplemental content that focused on Twitter data. This seemed like a natural starting point given that the first chapter of the book is a gentle introduction to data mining with Twitter’s API coupled with the inherent openness of accessing and analyzing Twitter data (in comparison to other data sources that are a little more restrictive.) Twitter’s IPO late last year also focused the spotlight a bit on Twitter, which provided some good opportunities to opine on Twitter’s underlying data model that can be interpreted as an interest graph.

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The First #Ecological Land Units #Map of the World | #opendata #dataviz

The First #Ecological Land Units #Map of the World | #opendata #dataviz | Public Datasets - Open Data - | Scoop.it
luiy's insight:

This map as well as the data layers used to create it can be explored in a new story map that introduces ecological land units. The data is available in the form of services and can enrich any GIS effort.

 

The collaborative partnership between Esri and USGS resulted in a dynamic online map representing the world’s ecological diversity at unprecedented detail and authority. This work leveraged quantitative methods, geographic science, and big data produced by government agencies and the scientific community.  To create this map the data were processed in Esri’s ArcGIS cloud computing environment. This map provides new knowledge and understanding of geographic patterns and relationships by distinguishing the geography of the planets’ ecosystems.

- See more at: http://blogs.esri.com/esri/esri-insider/2014/12/09/the-first-detailed-ecological-land-unitsmap-in-the-world/#sthash.Fm99R5lg.dpuf

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Is Cape Town's new #opendata portal any good? | #dataviz

Is Cape Town's new #opendata portal any good? | #dataviz | Public Datasets - Open Data - | Scoop.it
Code4SA's Adi Eyal takes a look at Africa's first open data city.
luiy's insight:

 ... the City chose to build their portal in-house rather than using one of the existing platforms. The UK open data portal for instance uses an open source platform CKAN. A commercial offering called Socrata is also available if you feel like you need the security of using a closed source solution. The benefit of using an existing platform is that you’re benefiting from the wisdom of those who came before you. It is also often much cheaper than doing it on your own. Our own modest data portal uses Socrata. As a developer, for me the killer feature here is that every dataset comes packaged with a pre-built API and documentation. It also allows non-technical users to create graphs and maps without having to download the data and opening up the spreadsheets. The City’s website in contrast, is not much more than a collection of links.

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Crimes de guerre et décryptage de données : nouvelles révélations de Snowden | #NSA #opendata

Crimes de guerre et décryptage de données : nouvelles révélations de Snowden | #NSA #opendata | Public Datasets - Open Data - | Scoop.it
De nouvelles révélations d'Edward Snowden mettent en lumière les agissement des pays de l'Otan en Afghanistan et le décryptage de données par la NSA américaine.
luiy's insight:

(De Hambourg) C’était un passage attendu du 31c3, le 31ème Chaos Communication Congress qui se déroule en ce moment à Hambourg : dimanche soir, devant 3 500 personnes, la journaliste Laura Poitras et le hacker Jacob Appelbaum ont révélé des documents d’Edward Snowden jusque-là inconnus du public.

 

Simultanément, plusieurs articles contenant plusieurs dizaines de ces documents ont été publiés (en anglais et en allemand) sur le site de l’hebdomadaire allemand Der Spiegel.

 

Des révélations touchant à des domaines très variés, allant de la guerre en Afghanistan aux capacités qu’a la NSA de décrypter les données circulant sur le Web.

 

http://www.spiegel.de/media/media-35508.pdf

 

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TubeKit: A Youtube #Crawling Toolkit | #datascience #tools #bigdata

TubeKit: A Youtube #Crawling Toolkit | #datascience #tools #bigdata | Public Datasets - Open Data - | Scoop.it

 #bigdata

luiy's insight:

TubeKit is a toolkit for creating YouTube crawlers. It allows one to build one's own crawler that can crawl YouTube based on a set of seed queries and collect up to 16 different attributes.

 

TubeKit assists in all the phases of this process starting database creation to finally giving access to the collected data with browsing and searching interfaces. In addition to creating crawlers, TubeKit also provides several tools to collect a variety of data from YouTube, including video details and user profiles

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Project #BigData. Expanding on Project C to look at a different use case | #datascience #opendata

Project #BigData. Expanding on Project C to look at a different use case | #datascience #opendata | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Project Big Data is an interactive tool which enables you to visualize and explore the funding patterns of over 600 companies in the Big Data ecosystem! It is based on the work I did for Project C (which you see and can read about here). The list of companies and their classification into categories is based on a dozen published sources and rough text analytics of the Crunchbase database. Crunchbase is a curated crowed sourced database of over 285k companies.

 

As for the data, there are 645 public & private companies in the data set. From Teradata and IBM to Actuate & Zoomdata. I began by harvesting data from Crunchbase by using their free API w/ Python. As of September, Crunchbase had 1250 funding events for 410 of the companies on my list. I've grouped these companies into 18 categories, allowing you to compare peers as well as trends across categories. Some of the categories are broken down further. For example, the tool allows you to differentiate between cloud-based and on premise solutions or SQL vs. NoSQL databases. I gathered additional data from a variety of sources. For example, LinkedIn was used to find the number of employees.

 

 

OPENACCESS Workbook: Project Big Data v1.0 

https://public.tableausoftware.com/download/workbooks/ProjectBigDatav1_0?format=html

 

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Mining of Massive Datasets | #datascience #freebook

Mining of Massive Datasets | #datascience #freebook | Public Datasets - Open Data - | Scoop.it

Via ukituki
luiy's insight:

Preface and Table of Content

Chapter 1. Data Mining

Chapter 2. Map-Reduce and the New Software Stack

Chapter 3. Finding Similar Items

Chapter 4. Mining Data Streams

Chapter 5. Link Analysis

Chapter 6. Frequent Itemsets

Chapter 7. Clustering

Chapter 8. Advertising on the Web

Chapter 9. Recommendation Systems

Chapter 10. Mining Social-Network Graphs

Chapter 11. Dimensionality Reduction

Chapter 12. Large-Scale Machine Learning

 

Download Full Book :

http://infolab.stanford.edu/~ullman/mmds/book.pdf

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ukituki's curator insight, August 28, 2014 6:22 PM

The book is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining).

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Visualizing Publicly Available US Government Data Online | #dataviz #opengov

Visualizing Publicly Available US Government Data Online | #dataviz #opengov | Public Datasets - Open Data - | Scoop.it

Via Nicholas Goubert
luiy's insight:

Brightpoint Consulting recently released a small collection of interactive visualizations based on open, publicly available data from the US government. Characterized by a rather organic graphic design style and color palette, each visualization makes a socially and politically relevant dataset easily accessible.

 

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Europeana Labs: 30 million metadata records linking to millions of openly licensed media objects | #opendata #datasets

Europeana Labs: 30 million metadata records linking to millions of openly licensed media objects | #opendata #datasets | Public Datasets - Open Data - | Scoop.it
luiy's insight:

Data

 

Our database contains over 30 million metadata records linking to millions of openly licensed media objects - books, photos, art, artefacts, audio clips and more. We'll be featuring some of our very best content here.

 

Europeana Labs combines rights-cleared images, videos, audio and text files with technical expertise, tools, services and business knowledge.

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Data Repositories - Mother's Milk for Data Scientists | #datasets #opendata

Data Repositories - Mother's Milk for Data Scientists | #datasets #opendata | Public Datasets - Open Data - | Scoop.it
Mothers are life givers, giving the milk of life. While there are so very few analogies so apropos, data is often considered the Mother's Milk of Corporate Valuation. So, as a data scientist, we sh...
luiy's insight:

Here are a few repositories from KDnuggets that are worth taking a look at:

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#OpenData Barometer Data | #opengov #dataviz

#OpenData Barometer Data | #opengov #dataviz | Public Datasets - Open Data - | Scoop.it
luiy's insight:

The Open Data Barometer takes a multidimensional look at the current adoption level of open data policy and practice around the world. Three main categories are considered as part of the barometer:

 

- Readiness - identifies how far a country has in place the political, social and economic foundations for realising the potential benefits of open data. The Barometer covers the readiness of government, entrepreneurs and business, and citizen and civil society.

 

- Implementation - identifies the extent to which government has published a range of key datasets to support innovation, accountability and more improved social policy. The barometer covers 14 datasets split across three clusters to capture datasets commonly used for: securing government accountability; improving social policy; and enabling innovation and economic activity.

 

- Emerging impacts - identifies the extent to which open data has been seen to lead to positive political, social and environment, and economic change. The Barometer looks for political impacts – including transparency & accountability, and improved government efficiency and effectiveness; economic impacts – through supporting start-up entrepreneurs and existing businesses; and social impacts – including environmental impacts, and contributing to greater inclusion for marginalised groups in society.

 

These factors have been combined onto a Radar chart, this represents the countries barometer.

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Quantifying Memory: Mapping the #GDELT data in #R (and some Russian protests, too) | #opendata #datascience

Quantifying Memory: Mapping the #GDELT data in #R (and some Russian protests, too) | #opendata #datascience | Public Datasets - Open Data - | Scoop.it
luiy's insight:

The Guardian recently published an article linking to a database of 250 million events. Sounds too good to be true, but as I'm writing a PhD on recent Russian memory events, I was excited to try it out. I downloaded the data, generously made available by Kalev Leetaru of the University of Illinois, and got going. It's a large 650mb zip file (4.6gb uncompressed!), and this is apparently the abbreviated version. Consequently this early stage of the analysis was dominated by eager anticipation, as the Cambridge University internet did its thing.

 

Meanwhile I headed over to David Masad's writeup on getting started with GDELT in python

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