Map of Best Breweries in America
Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, visualização
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Um mapa com as melhores produtoras de cerveja artesanal nos EUA e uma rota otimizada com algoritmos genéticos
RateBeer puts out a list every year for top 100 breweries in the world. The rankings are based on reviews, range across styles, and historical performance (and maybe a bit of subjectivity). RateBeer just published the list for 2018. Here’s a map of the 73 U.S.-based breweries.
Brewery Road Trip, Optimized With Genetic Algorithm
Now that we know where they are, let’s find out how to visit all of them in one go.
Tags: belo, grafos, mapas, otimização, R-software, SIG
Voronoi diagram from smooshing paint between glass
Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, matemática, videos
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Uma abordagem original aos diagramas de Voronoi.
Tags: belo, otimização
curso de KNIME
Posted by Armando Brito Mendes | Filed under mapas SIG's, materiais para profissionais, software, videos, visualização
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Muito bom curso de KNIME, é introdutório mas introduz um grande número de funcionalidades.
KNIME Online Self-Training
Welcome to the KNIME Self-training course. The focus of this document is to get you started with KNIME as quickly as possible and guide you through essential steps of advanced analytics with KNIME. Optional and very useful topics such as reporting, KNIME Server and database handling are also included to give you an idea of what else is possible with KNIME.
- Installing KNIME Analytics Platform and Extensions
- Data Import / Export and Database / Big Data
- ETL
- Visualization
- Advanced Analytics
- Reporting
- KNIME Server
Tags: análise de dados, big data, data mining, Knime, text mining
norsecorp cyber attack info
Posted by Armando Brito Mendes | Filed under mapas SIG's, visualização
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Um site dinâmico q mapeia informação sobre ciberataques em tempo real
Statistical Atlas
Posted by Armando Brito Mendes | Filed under estatística, mapas SIG's, materiais ensino, visualização
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Um projeto em curso que pretende criar mapas temáticos de todos os dados existentes nos EUA, ambicioso, não?
Age and Sex
This is the age and biological sex of the population.
Disability
This is disability status.
Education
This is who goes to school.
Geology
This is the land and water.
Government
This is how the government functions.
Income and Earnings
This is how much money people make.
Language
This is how people communicate.
Living Arrangement
This is the household makeup.
Mortality
This is how people die.
Origins
This is where people come from.
Population
This is how many people there are.
Poverty
This is who lives below the poverty thresholds.
Transportation
This is how people get around.
Work
This is where and how people work.
Tags: belo, Estat Descritiva, mapas, R-software
Poverty and Race in America
Posted by Armando Brito Mendes | Filed under estatística, mapas SIG's, visualização
Uma boa representação gráfica interactiva
Strategies to tackle poverty, inequality, and neighborhood distress must be informed by local data. The history, geography, and politics of individual metro regions all matter profoundly, and any serious policy strategy must be tailored to local realities.
To help take the policy conversation from the general to the specific, we offer a new mapping tool. It lets you explore changes from 1980 to 2010 in where poor people of different races and ethnicities lived, for every metropolitan region nationwide.
Understanding how the geography of poverty has changed can provide essential context for answering questions like: Are some poor neighborhoods isolated from the region’s job opportunities? What would it take to connect them? Where should family support services be targeted? Which neighborhoods should be prioritized for improvements in essential amenities and opportunities? How can poor people across the metro landscape be better connected to the services and opportunities they seek?
For metro regions to systematically reduce poverty and expand opportunity, local civic and political leaders, advocates, and practitioners should start by sitting down together to understand the evolving realities of poverty, race, and place in their communities. We hope our maps help catalyze these conversations.
Tags: belo, data mining, image mining, mapas
Vector maps on the web with Mapbox GL
Posted by Armando Brito Mendes | Filed under mapas SIG's, materiais para profissionais, software, visualização
Novas funcionalidades da biblioteca Java Script para desenhar mapas vetoriais
Online mapping just got an upgrade:
Announcing Mapbox GL JS — a fast and powerful new system for web maps. Mapbox GL JS is a client-side renderer, so it uses JavaScript and WebGL to dynamically draw data with the speed and smoothness of a video game. Instead of fixing styles and zoom levels at the server level, Mapbox GL puts power in JavaScript, allowing for dynamic styling and freeform interactivity.
For the non-developers: Online maps are typically stored pre-made on a server, in the form of a bunch of image files that are stitched together when you zoom in and out of a map. So developers have to periodically update the image files if they want their base maps to change. It’s a hassle, which is why base maps often look similar. With Mapbox GL, making changes is easier because the development pipeline is shorter.
More details on the JavaScript library here.
Tags: desnvolvimento de software, mapas
High-detail maps with Disser
Posted by Armando Brito Mendes | Filed under mapas SIG's, software, visualização
Software open source para trabalhar com mapas
Open data consultancy Conveyal released Disser, a command-line tool to disaggregate geographic data to show more details. For example, we’ve seen data represented with uniformly distributed dots to represent populations, which is fine for a zoomed out view. However, when you get in close, it can be useful to see distributions more accurately represented.
If the goal of disaggregation is to make a reasonable guess at the data in its pre-aggregated form, we’ve done an okay job. There’s an obvious flaw with this map, though. People aren’t evenly distributed over a block — they’re concentrated into residential buildings.
So Disser combines datasets of different granularity, so that you can see spreads and concentrations that are closer to real life.
Tags: belo, image mining, mapas
