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re3data.org | Registry of Research Data Repositories

re3data.org | Registry of Research Data Repositories | dataInnovation | Scoop.it

re3data.org is a global registry of research data repositories. The registry covers research data repositories from different academic disciplines. re3data.org presents repositories for the permanent storage and access of data sets to researchers, funding bodies, publishers and scholarly institutions. re3data.org aims to promote a culture of sharing, increased access and better visibility of research data.


In December 2012 re3data.org launched an alpha version. The registry will be continuously developed and improved together with relevant stakeholders.


re3data.org is funded by the German Research Foundation (DFG). 


Via Irina Radchenko
Fàtima Galan's insight:

"re3data.org provides an overview of existing research data repositories. Since 2012, re3data.org has indexed research data repositories offering researchers, funding organizations, libraries and publishers an overview of the heterogeneous research data repository landscape."

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dataInnovation
Proficient in Information System Design used to the development of Business Intelligence Platforms and Semantic Web Ontologies. With experience in the benefits of the knowledge extraction by integrating LinkedData Technologies and OpenData Sources.
Curated by Fàtima Galan
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Google is making its assistant 'conversational' in two new ways

Google is making its assistant 'conversational' in two new ways | dataInnovation | Scoop.it
Google would like to remind you that you can talk with it.
Today Google is announcing a "Google Assistant" that essentially performs the same tasks as other Google interfaces do, but i
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Regression, Logistic Regression and Maximum Entropy part 2 (code + examples) – Ahmet Taspinar

Regression, Logistic Regression and Maximum Entropy part 2 (code + examples) – Ahmet Taspinar | dataInnovation | Scoop.it
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Rescooped by Fàtima Galan from Influence et contagion
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#Clustering #memes in social media streams | #algorithms #sna

#Clustering #memes in social media streams | #algorithms #sna | dataInnovation | Scoop.it

Via luiy
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luiy's curator insight, November 4, 2014 6:43 AM

The problem of clustering content in social media has pervasive applications, including the identification of discussion topics, event detection, and content recommendation. Here we describe a streaming framework for online detection and clustering of memes in social media, specifically Twitter.

 

A pre-clustering procedure, namely protomeme detection, first isolates atomic tokens of information carried by the tweets. Protomemes are thereafter aggregated, based on multiple similarity measures, to obtain memes as cohesive groups of tweets reflecting actual concepts or topics of discussion.

 

The clustering algorithm takes into account various dimensions of the data and metadata, including natural language, the social network, and the patterns of information diffusion. As a result, our system can build clusters of semantically, structurally, and topically related tweets.


The clustering process is based on a variant of Online K-means that incorporates a memory mechanism, used to "forget" old memes and replace them over time with the new ones. The evaluation of our framework is carried out by using a dataset of Twitter trending topics.


Over a one-week period, we systematically determined whether our algorithm was able to recover the trending hashtags. We show that the proposed method outperforms baseline algorithms that only use content features, as well as a state-of-the-art event detection method that assumes full knowledge of the underlying follower network. We finally show that our online learning framework is flexible, due to its independence of the adopted clustering algorithm, and best suited to work in a streaming scenario.

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Visualizing Government Archives through Linked Data

Visualizing Government Archives through Linked Data | dataInnovation | Scoop.it
Tonight I’m knocking back a gin and tonic to celebrate finishing a piece of software development for my client the Public Record Office Victoria; the archives of the government of the Austral…
Via Cátedra Libre Open Gov (CLOG)
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Meet Google's new search king

Meet Google's new search king | dataInnovation | Scoop.it
Meet John Giannandrea, an expert in artificial intellgience who's taking over as Google's new search chief.
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Taller Intensivo de Periodismo de Datos

Organizado por el Departamento de Ciencias de la Comunicación y Periodismo, se realizó en la UCA, un Taller intensivo sobre Periodismo de Datos, dictado por ...


Via Cátedra Libre Open Gov (CLOG)
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Introduction to Linked Data and the Semantic Web - University of Southampton

Introduction to Linked Data and the Semantic Web - University of Southampton | dataInnovation | Scoop.it
Learn the power of Linked Data, explore how it’s revolutionising the web and get to grips with it by writing queries in SPARQL.
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Pedro Domingos: "The Master Algorithm" | Talks at Google

Pedro Domingos: "The Master Algorithm" | Talks at Google | dataInnovation | Scoop.it
Machine learning is the automation of discovery, and it is responsible for making our smartphones work, helping Netflix suggest movies for us to watch, and g...
Fàtima Galan's insight:

"Where does knowledge come from?

Until very recently, it came from just three sources, number
1. evolution: encoded in your DNA
2. experience: encoded in your neurons
3. culture: the knowledge you acquire by talking with other people, reading books...
Now what's there's a fourth source of knowledge: computers.

"

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The Future of Artificial Intelligence is Here

The Future of Artificial Intelligence is Here | dataInnovation | Scoop.it
By: Abdul Razack, SVP & head of platforms, big data and analytics at Infosys
Artificial intelligence is rapidly changing the business and consumer land…
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Apache Spark vs. Apache Drill | MapR

Apache Spark vs. Apache Drill | MapR | dataInnovation | Scoop.it
If you’re thinking about working with big data, you might be wondering which tools you should use. If you are trying to enable SQL-on-Hadoop then you might be considering the use of Apache Spark or Apache Drill.
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How Applications of Big Data Drive Industries

How Applications of Big Data Drive Industries | dataInnovation | Scoop.it
How industries like banking, healthcare, education, manufacturing, Insurance, retail, etc. are using big data.

Via Luca Naso
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PhysicsTutorRanchi's curator insight, December 19, 2015 8:27 AM

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Fabio Di Pasquale's curator insight, April 5, 2:30 AM

There is a substantial spending on big data, with more than 75% of companies (from different industries) investing in big data in the next two years.

 

Each industry vertical has its own challenges and solutions. Here is a great article and infographics by simplilearn that describe for 10 verticals both main challenges and applications.

The 10 industries are:

1. Banking

2. Communication

3. Healthcare

4. Education

5. Manufacturing

6. Government

7. Insurance

8. Retail

9. Transportation

10. Energy

Emeric Nectoux's curator insight, April 22, 3:29 AM

A Gartner Survey for 2015 shows that more than 75% of companies are investing or are planning to invest in big data in the next two years. These findings represent a significant increase compare to 2012.

Rescooped by Fàtima Galan from Open Government (worldwide)
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Do We Need to Educate Open Data Users?

Do We Need to Educate Open Data Users? | dataInnovation | Scoop.it

Guest post from Tony Hirst Tony Hirst is a Senior Lecturer at The Open University, UK, open data practitioner, and regular blogger at ouseful.info.


Via Cátedra Libre Open Gov (CLOG)
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Google Home, el altavoz inteligente para el salón

Google Home, el altavoz inteligente para el salón | dataInnovation | Scoop.it
Google presenta su altavoz inteligente para trasladar lo que mejor saben hacer, la inteligencia artificial, al salón de las casas. 

Via Adele Robots
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Amazon’s Giving Away the AI Behind Its Product Recommendations

Amazon’s Giving Away the AI Behind Its Product Recommendations | dataInnovation | Scoop.it
Amazon has become the latest tech giant that's giving away some of its most sophisticated technology.
Fàtima Galan's insight:
“We are releasing DSSTNE as open source software so that the promise of deep learning can extend beyond speech and language understanding and object recognition to other areas such as search and recommendations,” the Q&A section of Amazon’s DSSTNE GitHub page reads. “We hope that researchers around the world can collaborate to improve it. But more importantly, we hope that it spurs innovation in many more areas.”
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Rescooped by Fàtima Galan from Influence et contagion
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Computer-based #personality judgments are more accurate than those made by humans | #social-cognitive

Computer-based #personality judgments are more accurate than those made by humans | #social-cognitive | dataInnovation | Scoop.it

This study compares the accuracy of personality judgment a ubiquitous and important social-cognitive activity between computer models and humans. Using several criteria, we show that computers judgments of people's personalities based on their digital footprints are more accurate and valid than judgments made by their close others or acquaintances (friends, family, spouse, colleagues, etc.). Our findings highlight that people’s personalities can be predicted automatically andwithout involving human social-cognitive skills.


Via luiy
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Rescooped by Fàtima Galan from e-Xploration
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SORTING - Visualizing sorting #algorithms | #dataviz #datascience

SORTING - Visualizing sorting #algorithms | #dataviz #datascience | dataInnovation | Scoop.it
A visualization of the most famous Sorting Algorithms.

Via luiy
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luiy's curator insight, January 9, 1:26 PM
ABOUT SORTING

Sorting a sequence of items is one of the pillar of Computer Science. 


A sorting algorithm is an algorithm that organizes elements of a sequence in a certain order. Since the early days of computing, the sorting problem has been one of the main battlefields for researchers. The reason behind this is not only the need of solving a very common task but also the challenge of solving a complex problem in the most efficient way. 

SORTING is an attempt to visualize and help to understand how some of the most famous sorting algorithms work. This project provides two standpoints to look at algorithms, one is more artistic (apologies to any real artist out there), the other is more analytical aiming at explaining algorithm step by step. 

This project does not want to teach the theory of sorting algorithms, there are amazing resources, books and courses for this purpose. SORTING is for the ones who want to see these algorithms under a different ligth and hopefully appreciate the processing and brain power behind these piece of genius that in many ways have changed the way we live.

 
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Open Data: Casting a Digital Net to Catch the Corrupt

Open Data: Casting a Digital Net to Catch the Corrupt | dataInnovation | Scoop.it
By Martin Tisné, Investment Partner at Omidyar Network
Via Cátedra Libre Open Gov (CLOG)
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Rescooped by Fàtima Galan from Linked Data and Semantic Web
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Introducing Linked Data And The Semantic Web

Introducing Linked Data And The Semantic Web | dataInnovation | Scoop.it
Introduction to the semantic web of linked data, its advantages and difference between Web 3.0 and Web 2.0

Via Irina Radchenko
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Introduction to Apache Spark with Examples and Use Cases | MapR

Introduction to Apache Spark with Examples and Use Cases | MapR | dataInnovation | Scoop.it
I first heard of Spark in late 2013 when I became interested in Scala, the language in which Spark is written. Some time later, I did a fun data science project trying to predict survival on the Titanic. This turned out to be a great way to get further introduced to Spark concepts and programming. I highly recommend it for any aspiring Spark developers looking for a place to get started.
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Unsupervised Deep Parsing

Unsupervised Deep Parsing | dataInnovation | Scoop.it
As I have written before, it is not always easy to understand the possibilities of current-day text analytics algorithms, much more can be done than we actually are aware of. Among some of the more
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Rescooped by Fàtima Galan from Future Trends and Advances In Education and Technology
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The 7 technologies changing your world

The 7 technologies changing your world | dataInnovation | Scoop.it
A post to help you navigate the technologies of the Fourth Industrial Revolution

Via Grant Montgomery
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10 text, sentiment, and social analytics trends for 2016

10 text, sentiment, and social analytics trends for 2016 | dataInnovation | Scoop.it
Text, sentiment, and social analytics help you tune in, at scale, to the voice of the customer, patient, public, and market. The technologies are currently being applied in an array of industries ranging from healthcare to finance, media, and consumer markets. They distill business insight from online, social, and enterprise data sources.
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Turning open data into business innovation

OpenData can enable Innovation in the collaborative city and how it translates into an innovation opportunity for the private sector including startups. (Example ...


Via Cátedra Libre Open Gov (CLOG)
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Big Data in Healthcare Sector ? Revolutionizing the Management of Laborious Tasks | Simplilearn

Big Data in Healthcare Sector ? Revolutionizing the Management of Laborious Tasks | Simplilearn | dataInnovation | Scoop.it
As technology grows in healthcare, the type of data sources volumes available for analysis grows with it; Big data solutions targets to harness these huge and complex data.
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