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Rescooped by Becheru Alexandru from Papers
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Conditions for the Emergence of Shared Norms in Populations with Incompatible Preferences

Understanding norms is a key challenge in sociology. Nevertheless, there is a lack of dynamical models explaining how one of several possible behaviors is established as a norm and under what conditions. Analysing an agent-based model, we identify interesting parameter dependencies that imply when two behaviors will coexist or when a shared norm will emerge in a heterogeneous society, where different populations have incompatible preferences. Our model highlights the importance of randomness, spatial interactions, non-linear dynamics, and self-organization. It can also explain the emergence of unpopular norms that do not maximize the collective benefit. Furthermore, we compare behavior-based with preference-based punishment and find interesting results concerning hypocritical punishment. Strikingly, pressuring others to perform the same public behavior as oneself is more effective in promoting norms than pressuring others to meet one’s own private preference. Finally, we show that adaptive group pressure exerted by randomly occuring, local majorities may create norms under conditions where different behaviors would normally coexist.

 

Helbing D, Yu W, Opp K-D, Rauhut H (2014) Conditions for the Emergence of Shared Norms in Populations with Incompatible Preferences. PLoS ONE 9(8): e104207. http://dx.doi.org/10.1371/journal.pone.0104207


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

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

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luiy's curator insight, September 4, 11:17 AM

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

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

Seven Ways to Create a Storymap | #opendata #maps #ddj | Complex Networks | Scoop.it
Evidence is Power

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luiy's curator insight, September 2, 5:13 PM

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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Forget The Wisdom of Crowds; Neurobiologists Reveal The Wisdom Of The Confident | MIT Technology Review

Forget The Wisdom of Crowds; Neurobiologists Reveal The Wisdom Of The Confident | MIT Technology Review | Complex Networks | Scoop.it
The wisdom of crowds breaks down when people are biased. Now researchers have discovered a simple method of removing this bias–just listen to the most confident.

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Marc Tirel's curator insight, July 16, 4:23 AM

I am confident in this article

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#Open311 : An #OpenModel Provides Transparency, #Participation, and Collaboration.

#Open311 : An #OpenModel Provides Transparency, #Participation, and Collaboration. | Complex Networks | Scoop.it

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luiy's curator insight, July 15, 7:30 PM

Open311 technologies use the internet to enable these interactions to be asynchronous and many-to-many. This means that several different people can openly exchange information centered around a single public issue. This open model allows people to provide more actionable information for those who need it most and it encourages the public to be engaged with civic issues because they know their voices are being heard. Yet Open311 isn’t just about this more open internet-enabled model for 311 services, it’s also about making sure the technology itself is open so that 311 services and applications are interoperable and can be used everywhere.

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US military studied how to influence Twitter users in Darpa-funded research

US military studied how to influence Twitter users in Darpa-funded research | Complex Networks | Scoop.it
Defense Department spent millions researching users, including studies on Occupy and Middle East residents, and how to better spread propaganda

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luiy's curator insight, July 10, 5:54 AM

The activities of users of Twitter and other social media services were recorded and analysed as part of a major project funded by the US military, in a program that covers ground similar to Facebook’s controversial experiment into how to control emotions by manipulating news feeds.

 

Research funded directly or indirectly by the US Department of Defense’s military research department, known as Darpa, has involved users of some of the internet’s largest destinations, including Facebook, Twitter, Pinterest and Kickstarter, for studies of social connections and how messages spread.

 
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Coding Together at Scale: GitHub as a Collaborative Social Network

GitHub is the most popular repository for open source code. It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities.
In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration.

 

Coding Together at Scale: GitHub as a Collaborative Social Network
Antonio Lima, Luca Rossi, Mirco Musolesi

http://arxiv.org/abs/1407.2535


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Rescooped by Becheru Alexandru from Influence et contagion
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Evolution of Online User Behavior During a Social Upheaval | #datascience #diregeziparki

Evolution of Online User Behavior During a Social Upheaval | #datascience #diregeziparki | Complex Networks | Scoop.it

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luiy's curator insight, July 6, 11:14 AM

Social media represent powerful tools of mass communication and information diffusion. They played a pivotal role during recent social uprisings and political mobilizations across the world. Here we present a study of the Gezi Park movement in Turkey through the lens of Twitter. We analyze over 2.3 million tweets produced during the 25 days of protest occurred between May and June 2013. We first characterize the spatio-temporal nature of the conversation about the Gezi Park demonstrations, showing that similarity in trends of discussion mirrors geographic cues. We then describe the characteristics of the users involved in this conversation and what roles they played. We study how roles and individual influence evolved during the period of the upheaval. This analysis reveals that the conversation becomes more democratic as events unfold, with a redistribution of influence over time in the user population. We conclude by observing how the online and offline worlds are tightly intertwined, showing that exogenous events, such as political speeches or police actions, affect social media conversations and trigger changes in individual behavior.

Rescooped by Becheru Alexandru from Social Network Analysis #sna
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Mini Lecture: Social Network Analysis for Fraud Detection

Mini Lecture: Social Network Analysis for Fraud Detection | Complex Networks | Scoop.it
In this mini lecture, Véronique Van Vlasselaer talks about how social networks can be leveraged to uncover fraud. Véronique is working in the DataMiningApps group led by Prof. dr. Bart Baesens at the KU Leuven (University of Leuven), Belgium.

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Rescooped by Becheru Alexandru from Talks
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Nonlinear Dynamics and Chaos - Steven Strogatz, Cornell University - YouTube

Nonlinear Dynamics and Chaos - Steven Strogatz, Cornell University - YouTube | Complex Networks | Scoop.it

This course of 25 lectures, filmed at Cornell University in Spring 2014, is intended for newcomers to nonlinear dynamics and chaos. It closely follows Prof. Strogatz's book, "Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering." The mathematical treatment is friendly and informal, but still careful. Analytical methods, concrete examples, and geometric intuition are stressed. The theory is developed systematically, starting with first-order differential equations and their bifurcations, followed by phase plane analysis, limit cycles and their bifurcations, and culminating with the Lorenz equations, chaos, iterated maps, period doubling, renormalization, fractals, and strange attractors. A unique feature of the course is its emphasis on applications. These include airplane wing vibrations, biological rhythms, insect outbreaks, chemical oscillators, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with the mathematical theory. The theoretical work is enlivened by frequent use of computer graphics, simulations, and videotaped demonstrations of nonlinear phenomena. The essential prerequisite is single-variable calculus, including curve sketching, Taylor series, and separable differential equations. In a few places, multivariable calculus (partial derivatives, Jacobian matrix, divergence theorem) and linear algebra (eigenvalues and eigenvectors) are used. Fourier analysis is not assumed, and is developed where needed. Introductory physics is used throughout. Other scientific prerequisites would depend on the applications considered, but in all cases, a first course should be adequate preparation

 

Nonlinear Dynamics and Chaos - Steven Strogatz, Cornell University

https://www.youtube.com/playlist?list=PLbN57C5Zdl6j_qJA-pARJnKsmROzPnO9V


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Jean-Michel Livowsky's curator insight, June 2, 3:22 AM

Nonlinear Dynamics and Chaos...

Jean-Michel Livowsky's curator insight, June 2, 3:23 AM

Nonlinear Dynamics and Chaos

Rescooped by Becheru Alexandru from Influence et contagion
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#Algorithm Distinguishes #Memes from Ordinary Information | #contagion

#Algorithm Distinguishes #Memes from Ordinary Information | #contagion | Complex Networks | Scoop.it
Network theorists have developed a way to identify the top memes in science and study how they evolved 

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luiy's curator insight, May 26, 5:04 AM

Memes are the cultural equivalent of genes: units that transfer ideas or practices from one human to another by means of imitation. In recent years, network scientists have become increasingly interested in how memes spread.

This kind of work has led to important insights into the nature of news cycles, into information avalanches on social networks and into the role that networks themselves play in this spreading process.

 

But what exactly makes a meme and distinguishes it from other forms of information is not well understood. Today, Tobias Kuhn at ETH Zurich in Switzerland and a couple of pals say they’ve developed a way to automatically distinguish scientific memes from other forms of information for the first time. And they’ve used this technique to find the most important ideas in physics and how they’ve evolved in the last 100 years.

 

The word ‘meme’ was coined by the evolutionary biologists Richard Dawkins in his 1976 book The Selfish Gene. He argued that ideas, melodies, behaviours and so on, all evolve in the same way as genes, by means of replication and mutation, but using human culture rather than biology as the medium of evolution.

  

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Amazon.com: Social Physics: How Good Ideas Spread—The Lessons from a New Science (9781594205651): Alex Pentland: Books

Social Physics: How Good Ideas Spread—The Lessons from a New Science

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Rescooped by Becheru Alexandru from Dynamics on complex networks
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Shock waves on complex networks : Scientific Reports : Nature Publishing Group

Shock waves on complex networks : Scientific Reports : Nature Publishing Group | Complex Networks | Scoop.it
Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable nodes, we introduce the concept of node-basin size, a purely topological property which we show to be strongly correlated to the average load of a node.

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Eli Levine's curator insight, May 20, 8:19 AM

Indeed, this is intuitive enough without the mathematics to back it up.  This could be mapped out and used for prioritizing the defense or attack of various points within the network, either in the digital or analog worlds.

 

Way cool science!

 

Think about it.

Rescooped by Becheru Alexandru from Social Network Analysis #sna
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Multilayer Networks tutorial #netsci2014

These are the slides for a tutorial talk about "multilayer networks" that I gave at NetSci 2014. I walk people through a review article that I wrote with my …

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Rescooped by Becheru Alexandru from Influence et contagion
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#Google matrix analysis of directed networks | #datascience #algorithms

#Google matrix analysis of directed networks | #datascience #algorithms | Complex Networks | Scoop.it

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luiy's curator insight, September 2, 10:39 AM

This review describes matrix tools and algorithms which facilitate classification and information retrieval from large networks recently created by human activity. The Google matrix formed by links of the network has typically a huge size. Thus, the analysis of its spectral properties including complex eigenvalues and eigenvec- tors represents a challenge for analytical and numerical methods. It is rather surprising, but the class of such matrices, belonging to the class of Markov chains and Perron-Frobenius operators, was practically not inves- tigated in physics. Indeed, usually the physical prob- lems belong to the class of Hermitian or unitary ma- trices. Their properties had been actively studied in the frame of Random Matrix Theory (RMT) (Akemann et al., 2011; Guhr et al., 1998; Mehta, 2004) and quantum chaos (Haake, 2010). The analytical and numerical tools developed in these research fields allowed to understand many universal and peculiar features of such matrices in the limit of large matrix size corresponding to many-body quantum systems (Guhr et al., 1998), quantum comput- ers (Shepelyansky , 2001) and a semiclassical limit of large quantum numbers in the regime of quantum chaos (Haake, 2010). In contrast to the Hermitian problem, the Google matrices of directed networks have complex eigenvalues. 

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Friendship and natural selection

More than any other species, humans form social ties to individuals who are neither kin nor mates, and these ties tend to be with similar people. Here, we show that this similarity extends to genotypes. Across the whole genome, friends’ genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a “friendship score” that predicts the existence of friendship ties in a hold-out sample. A focused gene-set analysis indicates that some of the overall correlation in genotypes can be explained by specific systems; for example, an olfactory gene set is homophilic and an immune system gene set is heterophilic, suggesting that these systems may play a role in the formation or maintenance of friendship ties. Friends may be a kind of “functional kin.” Finally, homophilic genotypes exhibit significantly higher measures of positive selection, suggesting that, on average, they may yield a synergistic fitness advantage that has been helping to drive recent human evolution.

 

Friendship and natural selection
Nicholas A. Christakis and James H. Fowler

PNAS

http://dx.doi.org/10.1073/pnas.1400825111

 


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Christine Capra's curator insight, July 27, 8:06 PM

So, how does this impact our ability to have meaningful exchanges across diverse populations? 

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Forget The Wisdom of Crowds; Neurobiologists Reveal The Wisdom Of The Confident | MIT Technology Review

Forget The Wisdom of Crowds; Neurobiologists Reveal The Wisdom Of The Confident | MIT Technology Review | Complex Networks | Scoop.it
The wisdom of crowds breaks down when people are biased. Now researchers have discovered a simple method of removing this bias–just listen to the most confident.

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Marc Tirel's curator insight, July 16, 4:23 AM

I am confident in this article

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Early Warning Signs in Social-Ecological Networks

Early Warning Signs in Social-Ecological Networks | Complex Networks | Scoop.it

A number of social-ecological systems exhibit complex behavior associated with nonlinearities, bifurcations, and interaction with stochastic drivers. These systems are often prone to abrupt and unexpected instabilities and state shifts that emerge as a discontinuous response to gradual changes in environmental drivers. Predicting such behaviors is crucial to the prevention of or preparation for unwanted regime shifts. Recent research in ecology has investigated early warning signs that anticipate the divergence of univariate ecosystem dynamics from a stable attractor. To date, leading indicators of instability in systems with multiple interacting components have remained poorly investigated. This is a major limitation in the understanding of the dynamics of complex social-ecological networks. Here, we develop a theoretical framework to demonstrate that rising variance—measured, for example, by the maximum element of the covariance matrix of the network—is an effective leading indicator of network instability. We show that its reliability and robustness depend more on the sign of the interactions within the network than the network structure or noise intensity. Mutualistic, scale free and small world networks are less stable than their antagonistic or random counterparts but their instability is more reliably predicted by this leading indicator. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social-ecological networks.


Early Warning Signs in Social-Ecological Networks.

PLoS ONE 9(7): e101851. doi:10.1371/journal.pone.0101851 (2014)

Suweis Samir, D'Odorico Paolo


Code of the analysis available at https://github.com/suweis


http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0101851


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Tom Cockburn's curator insight, July 31, 3:24 AM

Reliably unreliable systems interacting

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The Network Structure of Jewish Texts

The Network Structure of Jewish Texts | Complex Networks | Scoop.it

Sefaria, is an open source database of Jewish texts and recently, Liz Shayne of UC Santa Barbara attempted to extract the relationships between the texts found there—annotations, allusions, and such—and visualize them. Unfortunately, Sefaria is very much a work-in-progress, so conclusions are likely to early to be drawn, but here is a quick visualization that Shayne performed of the complete network of more than 100,000 nodes and 87,000 links


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Jean-Michel Livowsky's curator insight, July 12, 1:28 PM

Une structure neuronale dans l'organisation des textes sacrés ?

Voilà qui me réconcilie avec la religion !

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Connecting Core Percolation and Controllability of Complex Networks : Scientific Reports : Nature Publishing Group

Connecting Core Percolation and Controllability of Complex Networks : Scientific Reports : Nature Publishing Group | Complex Networks | Scoop.it
Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks.

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Sibout Nooteboom's curator insight, July 13, 3:52 AM

Fascinating advances

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The GDELT Project: realtime network diagram and database of global human society for open research | #opendata

The GDELT Project: realtime network diagram and database of global human society for open research | #opendata | Complex Networks | Scoop.it
The GDELT Project

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luiy's curator insight, June 7, 6:50 PM

The GDELT Project is a realtime network diagram and database of global human society for open research Watching The Entire World

GDELT monitors the world's news media from nearly every corner of every country in print, broadcast, and web formats, in over 100 languages, every moment of every day.

 


Global Reach

 

GDELT monitors print, broadcast, and web news media in over 100 languages from across every country in the world to keep continually updated on breaking developments anywhere on the planet. Its historical archives stretch back to January 1, 1979 and update daily (soon to be every 15 minutes). Through its ability to leverage the world's collective news media, GDELT moves beyond the focus of the Western media towards a far more global perspective on what's happening and how the world is feeling about it.

 

 

Querying, Analyzing and Downloading

 

The entire GDELT database is 100% free and open and you can
download the raw datafiles, visualize it using the GDELT Analysis Service, or analyze it at limitless scale with Google BigQuery.

 

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Career on the Move: Geography, Stratification, and Scientific Impact

Career on the Move: Geography, Stratification, and Scientific Impact | Complex Networks | Scoop.it
Changing institutions is an integral part of an academic life. Yet little is known about the mobility patterns of scientists at an institutional level and how these career choices affect scientific outcomes. Here, we examine over 420,000 papers, to track the affiliation information of individual scientists, allowing us to reconstruct their career trajectories over decades. We find that career movements are not only temporally and spatially localized, but also characterized by a high degree of stratification in institutional ranking. When cross-group movement occurs, we find that while going from elite to lower-rank institutions on average associates with modest decrease in scientific performance, transitioning into elite institutions does not result in subsequent performance gain. These results offer empirical evidence on institutional level career choices and movements and have potential implications for science policy.

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Rescooped by Becheru Alexandru from Social Network Analysis #sna
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Twitter: Social Network Or News Medium?

An extensive research performed by the Korea Advanced Institute of Science and Technology

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Rescooped by Becheru Alexandru from Public Datasets - Open Data -
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#Opendata Compass. What type the companies use which agencies data? | #GovLab

#Opendata Compass. What type the companies use which agencies data? | #GovLab | Complex Networks | Scoop.it
The Open Data 500 is the first comprehensive study of U.S. companies that use open government data to generate new business and develop new products and services.

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luiy's curator insight, May 25, 5:40 AM

Study Goals

Provide a basis for assessing the economic value of government open data Encourage the development of new open data companies
Foster a dialogue between government and business on how government data can be made more useful


The Govlab’s Approach

The Open Data 500 study is conducted by the GovLab at New York University with funding from the John L. and James S. Knight Foundation. The GovLab works to improve people’s lives by changing how we govern, using technology-enabled solutions and a collaborative, networked approach. As part of its mission, the GovLab studies how institutions can publish the data they collect as open data so that businesses, organizations, and citizens can analyze and use this information.


Next Steps

The GovLab is now planning to use this study’s findings to convene a series of roundtables between government agencies and businesses that use their data to help improve the processes and priorities for data release. The Department of Commerce has committed to participate in the first discussion; other federal Departments have expressed an intent to participate in future roundtables.

In addition to our work in the U.S., we are now in discussions with representatives of several national governments and international organizations about the potential to replicate the Open Data 500 study in other countries.

 

Fàtima Galan's curator insight, May 26, 3:31 AM

"#OpenData is free, public data that can be used to launch commercial and nonprofit ventures, do research, make data-driven decisions, and solve complex problems."

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The New Science Of Effective Organizations

The New Science Of Effective Organizations | Complex Networks | Scoop.it
We're on the brink of a newly scientific approach to management, where technology and data replace folk wisdom and fads.
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