Information Policy

Reading the numbers, understanding the future − Statistics Estonia reinvents data mining

It is hard to underestimate the role that numbers and statistics play in planning public policies and shaping governments’ actions. As highlighted by author and tech commentator Andrew Keen in a recent conversation with us, the world shifting to a data-based playground in which the importance of real-time data collection and information accuracy is becoming ever more crucial. With enforcement of its Reporting 3.0 strategy, Estonia has already managed to improve the quality of data collected by its government statistical organizations; thereby lowering  the administrative burden on enterprises with regards to communicating basic information to Statistics Estonia or the Estonian Tax and Customs Board. What happens in this country when you achieve a result? You take it in, then you think of  ways to make it better.

Top 20 Civic Tech Websites for Urban Planners and City M..

A new category is joining our annual website rankings this year: Civic Technology/Civic Tech. Hundreds of online tools and websites are deployed to enable public participation and community action and empower citizens through open access to data and information. Governments are also relying more than ever on online tools to deliver public services and communicate with their constituents. And with the rise of the smart city movement, urban planning, policy, and development are becoming increasingly dependent on data and Information and Communications Technology (ICT) based solutions.

Smart Cities Need Local Democracy

arcelona’s streets are studded with sensors and responsive systems. Street lights, garbage cans, power metres, parking spots, park landscaping and public transit fit into the city’s “smart” environment, helping to manage everything from congested streets to service delivery. And, while the city is teeming with technology, it hasn’t strayed from strong, local, democratic governance of data.

Continue reading "Smart Cities Need Local Democracy" »

Posted at 07:33 AM in Open Source / Open Data, Smart City | Permalink

Reblog (0) | | | | | Digg This | Save to del.icio.us

By Tim Sandle   

 

Michael Fauscette, from G2 Crowd, has raised concerns about the privacy issues of ambient intelligence in the growing smart cities. What does privacy mean in a city where our location, our actions, even our intentions are being tracked and recorded?

 

Continue reading "Privacy concerns for living in the smart city " »

Posted at 11:02 AM in Open Source / Open Data, Privacy/Security , Smart City | Permalink

Reblog (0) | | | | | Digg This | Save to del.icio.us

Introduction

The key to getting better at deep learning (or most fields in life) is practice. Practice on a variety of problems – from image processing to speech recognition. Each of these problem has it’s own unique nuance and approach.

But where can you get this data? A lot of research papers you see these days use proprietary datasets that are usually not released to the general public. This becomes a problem, if you want to learn and apply your newly acquired skills.

If you have faced this problem, we have a solution for you. We have curated a list of openly available datasets for your perusal.

In this article, we have listed a collection of high quality datasets that every deep learning enthusiast should work on to apply and improve their skillset. Working on these datasets will make you a better data scientist and the amount of learning you will have will be invaluable in your career. We have also included papers with state-of-the-art (SOTA) results for you to go through and improve your models.

Privacy concerns for living in the smart city

By Tim Sandle   

 

Michael Fauscette, from G2 Crowd, has raised concerns about the privacy issues of ambient intelligence in the growing smart cities. What does privacy mean in a city where our location, our actions, even our intentions are being tracked and recorded?

 

Continue reading "Privacy concerns for living in the smart city " »

Posted at 11:02 AM in Open Source / Open Data, Privacy/Security , Smart City | Permalink

Reblog (0) | | | | | Digg This | Save to del.icio.us

Introduction

The key to getting better at deep learning (or most fields in life) is practice. Practice on a variety of problems – from image processing to speech recognition. Each of these problem has it’s own unique nuance and approach.

But where can you get this data? A lot of research papers you see these days use proprietary datasets that are usually not released to the general public. This becomes a problem, if you want to learn and apply your newly acquired skills.

If you have faced this problem, we have a solution for you. We have curated a list of openly available datasets for your perusal.

In this article, we have listed a collection of high quality datasets that every deep learning enthusiast should work on to apply and improve their skillset. Working on these datasets will make you a better data scientist and the amount of learning you will have will be invaluable in your career. We have also included papers with state-of-the-art (SOTA) results for you to go through and improve your models.

25 Open Datasets for Deep Learning Every Data Scientist Must Work With

Introduction

The key to getting better at deep learning (or most fields in life) is practice. Practice on a variety of problems – from image processing to speech recognition. Each of these problem has it’s own unique nuance and approach.

But where can you get this data? A lot of research papers you see these days use proprietary datasets that are usually not released to the general public. This becomes a problem, if you want to learn and apply your newly acquired skills.

If you have faced this problem, we have a solution for you. We have curated a list of openly available datasets for your perusal.

In this article, we have listed a collection of high quality datasets that every deep learning enthusiast should work on to apply and improve their skillset. Working on these datasets will make you a better data scientist and the amount of learning you will have will be invaluable in your career. We have also included papers with state-of-the-art (SOTA) results for you to go through and improve your models.