Futurists have long recognized the promise and disruptive potential of artificial intelligence, but there have been many false starts and AI has developed a reputation for overpromising and underdelivering. Success has been relegated to narrow domains like chess where the task is well-defined, rules are explicit, and the objective is clear. Even in these simplified environments the AI platforms have required teams of engineers working relentlessly to refine and optimize a system of algorithms tailored to the specific task to achieve a notable level of performance.

Data scientists at the Urban Institute develop a methodology for identifying problematic landlords from public data sources.

In a RECENT BLOG POST Sam Edelstein reflects on his time as the Chief Data Officer of the City of Syracuse:

Ken Streif at Urban Spatial has introduced an interesting predictive model that cities can adopt to anticipate development intensity and gentrification patterns.

Data scientists at the Urban Institute develop a methodology for identifying problematic landlords from public data sources.

One of my pet peeves is the use of geographic polygon maps, such as state border shapefiles, to display population data as choropleth maps. Because the brain interprets polygon size as a signal of importance, they are often more misleading than they are insightful!

Ken Streif at Urban Spatial has introduced an interesting predictive model that cities can adopt to anticipate development intensity and gentrification patterns.

The Analytics Playbook for Cities

Data scientists at the Urban Institute develop a methodology for identifying problematic landlords from public data sources.

Nick Muerdter put his programming expertise to use to help communities get vaccinated.

Tim Churches, a Senior Research Fellow at the UNSW Medicine South Western Sydney Clinical School at Liverpool Hospital, and a health data scientist at the Ingham Institute for Applied Medical Research, has produced a nice tutorial on acquiring data and creating epidemiological models to understand the spread of the disease.

Twitter has kicked off the New Year by taking the wraps off a new hub for academic researchers to more easily access information and support around its APIs — saying the move is in response to feedback from the research community.

Former US Chief Data Scientist, DJ Patel, spoke on what makes technology radical and revolutionary. At a recent talk he gave some very compelling examples of public services improving when access to data improved:

In a RECENT BLOG POST Sam Edelstein reflects on his time as the Chief Data Officer of the City of Syracuse:

IPUMS has created a GeoMarker tool to allow you to add demographic and community data to any address fields or latitude-longitude point data.

In ground-breaking investigative reporting, data journalist Rob O’Dell and USA Today have systematically tracked the diffusion of cut-and-paste legislation through state government. See:

Have you ever tried working with census data over time and encountered challenges with changes to Census tracts, which alter the units of analysis? Then you will appreciate these projects.

Andy Whitford at the University of Georgia wrote a blog on using DOI Codes to find data appropriate for scholarship in public affairs.

The Stanford Open Policing Project contains approximately 200 million data points on police stops in the US. The data are made available under the Open Data Commons Attribution License.

Ken Streif at Urban Spatial has introduced an interesting predictive model that cities can adopt to anticipate development intensity and gentrification patterns.

Ever wonder how big data firms are using your social media data?

Ken Streif at Urban Spatial has introduced an interesting predictive model that cities can adopt to anticipate development intensity and gentrification patterns.

Grosser & Bumann have created a project to help hone data science skills through better programming.

Preparing data for the analysis takes plenty of time and commonly is considered as one of the less favorite parts of any data science job. It is commonly stated that “data preparation accounts for about 80% of the work of data scientists”.

“Shiny” is a package in R that allows users to create dynamic web applications. Typically these apps require advanced knowledge of several web programming languages, but Shiny allows the user to do all of the development in R, greatly simplifying the learning curve and development time.

Plotly is one of the most popular R packages for creating interactive visualizations.

Ken Streif at Urban Spatial has introduced an interesting predictive model that cities can adopt to anticipate development intensity and gentrification patterns.

Tim Churches, a Senior Research Fellow at the UNSW Medicine South Western Sydney Clinical School at Liverpool Hospital, and a health data scientist at the Ingham Institute for Applied Medical Research, has produced a nice tutorial on acquiring data and creating epidemiological models to understand the spread of the disease.

One of my pet peeves is the use of geographic polygon maps, such as state border shapefiles, to display population data as choropleth maps. Because the brain interprets polygon size as a signal of importance, they are often more misleading than they are insightful!

Paula Moraga has released an online book Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (under development), which describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R.

“Shiny” is a package in R that allows users to create dynamic web applications. Typically these apps require advanced knowledge of several web programming languages, but Shiny allows the user to do all of the development in R, greatly simplifying the learning curve and development time.

Plotly is one of the most popular R packages for creating interactive visualizations.

In partnership with the World Government Summit and Information is Beautiful, the World Government Summit Data Viz Prize winners were announced. The prize focuses on how governments are improving citizens’ lives.

The Analytics Playbook for Cities

Former US Chief Data Scientist, DJ Patel, spoke on what makes technology radical and revolutionary. At a recent talk he gave some very compelling examples of public services improving when access to data improved:

Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter and Julia Lane have released a free textbook on useful computational methods for social sciences:

In a RECENT BLOG POST Sam Edelstein reflects on his time as the Chief Data Officer of the City of Syracuse:

In partnership with the World Government Summit and Information is Beautiful, the World Government Summit Data Viz Prize winners were announced. The prize focuses on how governments are improving citizens’ lives.

The Network of Schools of Public Policy, Affairs, and Administration (NASPAA) has issued a call for white papers on Data Science Curriculum for Public Service.

“Shiny” is a package in R that allows users to create dynamic web applications. Typically these apps require advanced knowledge of several web programming languages, but Shiny allows the user to do all of the development in R, greatly simplifying the learning curve and development time.

In partnership with the World Government Summit and Information is Beautiful, the World Government Summit Data Viz Prize winners were announced. The prize focuses on how governments are improving citizens’ lives.

Ever wonder how big data firms are using your social media data?

Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter and Julia Lane have released a free textbook on useful computational methods for social sciences:

The Stanford Open Policing Project contains approximately 200 million data points on police stops in the US. The data are made available under the Open Data Commons Attribution License.

Amazingly, the NBA has managed to succeed where many police forces have failed.

The Stanford Open Policing Project contains approximately 200 million data points on police stops in the US. The data are made available under the Open Data Commons Attribution License.

Amazingly, the NBA has managed to succeed where many police forces have failed.

The Stanford Open Policing Project contains approximately 200 million data points on police stops in the US. The data are made available under the Open Data Commons Attribution License.

Andy Whitford at the University of Georgia wrote a blog on using DOI Codes to find data appropriate for scholarship in public affairs.

Andy Whitford at the University of Georgia wrote a blog on using DOI Codes to find data appropriate for scholarship in public affairs.

IPUMS has created a GeoMarker tool to allow you to add demographic and community data to any address fields or latitude-longitude point data.

Have you ever tried working with census data over time and encountered challenges with changes to Census tracts, which alter the units of analysis? Then you will appreciate these projects.

One of my pet peeves is the use of geographic polygon maps, such as state border shapefiles, to display population data as choropleth maps. Because the brain interprets polygon size as a signal of importance, they are often more misleading than they are insightful!

Have you ever tried working with census data over time and encountered challenges with changes to Census tracts, which alter the units of analysis? Then you will appreciate these projects.

Plotly is one of the most popular R packages for creating interactive visualizations.

Twitter has kicked off the New Year by taking the wraps off a new hub for academic researchers to more easily access information and support around its APIs — saying the move is in response to feedback from the research community.

In ground-breaking investigative reporting, data journalist Rob O’Dell and USA Today have systematically tracked the diffusion of cut-and-paste legislation through state government. See:

In ground-breaking investigative reporting, data journalist Rob O’Dell and USA Today have systematically tracked the diffusion of cut-and-paste legislation through state government. See:

In ground-breaking investigative reporting, data journalist Rob O’Dell and USA Today have systematically tracked the diffusion of cut-and-paste legislation through state government. See:

“Shiny” is a package in R that allows users to create dynamic web applications. Typically these apps require advanced knowledge of several web programming languages, but Shiny allows the user to do all of the development in R, greatly simplifying the learning curve and development time.

Preparing data for the analysis takes plenty of time and commonly is considered as one of the less favorite parts of any data science job. It is commonly stated that “data preparation accounts for about 80% of the work of data scientists”.

Preparing data for the analysis takes plenty of time and commonly is considered as one of the less favorite parts of any data science job. It is commonly stated that “data preparation accounts for about 80% of the work of data scientists”.

Preparing data for the analysis takes plenty of time and commonly is considered as one of the less favorite parts of any data science job. It is commonly stated that “data preparation accounts for about 80% of the work of data scientists”.

Preparing data for the analysis takes plenty of time and commonly is considered as one of the less favorite parts of any data science job. It is commonly stated that “data preparation accounts for about 80% of the work of data scientists”.

Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter and Julia Lane have released a free textbook on useful computational methods for social sciences:

Grosser & Bumann have created a project to help hone data science skills through better programming.

The Network of Schools of Public Policy, Affairs, and Administration (NASPAA) has issued a call for white papers on Data Science Curriculum for Public Service.

In a RECENT BLOG POST Sam Edelstein reflects on his time as the Chief Data Officer of the City of Syracuse:

Paula Moraga has released an online book Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (under development), which describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R.

Amazingly, the NBA has managed to succeed where many police forces have failed.

Paula Moraga has released an online book Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (under development), which describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R.

Paula Moraga has released an online book Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (under development), which describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R.

Paula Moraga has released an online book Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (under development), which describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R.

Amazingly, the NBA has managed to succeed where many police forces have failed.

One of my pet peeves is the use of geographic polygon maps, such as state border shapefiles, to display population data as choropleth maps. Because the brain interprets polygon size as a signal of importance, they are often more misleading than they are insightful!

Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter and Julia Lane have released a free textbook on useful computational methods for social sciences:

Twitter has kicked off the New Year by taking the wraps off a new hub for academic researchers to more easily access information and support around its APIs — saying the move is in response to feedback from the research community.

Tim Churches, a Senior Research Fellow at the UNSW Medicine South Western Sydney Clinical School at Liverpool Hospital, and a health data scientist at the Ingham Institute for Applied Medical Research, has produced a nice tutorial on acquiring data and creating epidemiological models to understand the spread of the disease.

Nick Muerdter put his programming expertise to use to help communities get vaccinated.

The Analytics Playbook for Cities

Ever wonder how big data firms are using your social media data?

Nick Muerdter put his programming expertise to use to help communities get vaccinated.

Ever wonder how big data firms are using your social media data?

Ever wonder how big data firms are using your social media data?

Futurists have long recognized the promise and disruptive potential of artificial intelligence, but there have been many false starts and AI has developed a reputation for overpromising and underdelivering. Success has been relegated to narrow domains like chess where the task is well-defined, rules are explicit, and the objective is clear. Even in these simplified environments the AI platforms have required teams of engineers working relentlessly to refine and optimize a system of algorithms tailored to the specific task to achieve a notable level of performance.

Futurists have long recognized the promise and disruptive potential of artificial intelligence, but there have been many false starts and AI has developed a reputation for overpromising and underdelivering. Success has been relegated to narrow domains like chess where the task is well-defined, rules are explicit, and the objective is clear. Even in these simplified environments the AI platforms have required teams of engineers working relentlessly to refine and optimize a system of algorithms tailored to the specific task to achieve a notable level of performance.