11 November 2009
A
nother dataset that the city of San Francisco makes publicly available is the Department of Building Inspection’s monthly permit report. This report contains all the building permit activity within the city, from permits to add new condos to inspections of sprinkler systems. We took one full year of data, from September 2008 to August 2009, and brought it into SpatialKey. During the selected year-long time period there were over 25,000 permits issued. We can see the breakdown by the type of building on the right. Residential housing takes the top three spots (divided into Apartments, and one and two family homes).
We mapped the concentration of where these permits were issued. The different types of buildings, such as apartments versus office buildings, have very different distributions throughout the city. Some of these distributions are expected, such as the high concentration of permits for offices in the downtown area of San Francsico. But some of the distributions are more interesting and tell a story about the urban makeup of the city. Notice that apartments are much more concentrated closer to downtown in neighborhoods like the Tenderloin, Nob Hill, and Hayes Valley, most heavily around the eastern and northern areas surrounding the financial district. Two-family homes (ie duplexes) have a different concentration that includes neighborhoods like Cow Hollow and the Mission. And one-family homes are in neighborhoods like Pacific Heights, Noe Valley, and Twin Peaks.
The maps here show the number of building permits by the type of building.
Here are some alternate screenshots that are at a more granular resolution, so you can see a bit more detail on the different areas of the city. Click each thumbnail for a much larger version:
Try it for yourself
You can open up the sample report that we created to visualize these building permits. The report will load with two layers: the building permits and the neighborhood boundaries of San Francisco. You can change which types of building permits are shown by selecting items in the “Proposed Use” filter pod that is open in the report.
Looking for easy-to-use location intelligence from your own data? Get started with our free trial, and start visualizing your data in minutes without installing any software.
Notes on the data
It’s always important to remember what data we’re looking at. This is the number of building permits issued between September 2008 and August 2009. A single building might have multiple permits issued, which could be everything from renovations or re-roofing to a change from residential to commercial, etc.
This is the third part of an ongoing exploration of publicly accessible San Francisco data from DataSF.org. Please see the other posts in the series.
The images and reports in this post were created with publicly accessible data. We have no association with the city of San Francisco (but we’d love to, so contact us if you’re from the San Francisco government and want to use SpatialKey).
Posted by Doug McCune in DataSF, San Francisco, examples with no comments
2 November 2009
The Sacramento Police Department makes their dispatch database publicly available via monthly text files. These files are exported from Sacramento’s Computer Aided Dispatch (CAD) system, which supports police dispatch and response functions in their 911 center. These files include information about each dispatch, including details like date and time, type of call – from homicides to traffic stops – and location.
The first few rows of the Sacramento dispatch export
It took just a couple of minutes to import one of these files into SpatialKey, where we can produce rich interactive maps and reports related to dispatch activity in Sacramento. The file from August 2009 contained about 30,600 records with location information. Dispatches for Disturbance-Noise were the 7th most common type of dispatch in August.
Heatmap of the 1079 Noise Disturbances in Sacramento during August 2009.
By using the Temporal Heat Index and Timeline to inspect the date and time of occurrence, we get a better picture of when Disturbance-Noise calls occurred. The Temporal Heat Index summarizes the number of crimes by hour of day and day of week. Notice the dispatch volume is generally highest late at night – especially on Saturday and Sunday.
Most dispatches related to noise happen late at night on weekends.
So where are these early morning disturbances? Simply select day/hour grids of interest and zoom in to see the detail. Here’s a look at noise disturbances southeast of Capitol Park between 1 and 3am on weekends in August:
Southeast of Capital Park might be a good place to party but a hard place to sleep on weekends.
Try it for yourself
You can open up the sample report that we created to visualize these dispatches. The report is fully interactive, so you can really explore the dispatch activity in Sacramento. We saved the report with a filter for Disturbance-Noise. Try modifying this filter – and adding others – to see how SpatialKey works. Interested in seeing where and when the 338 Drunk Suspects were encountered? Or the 27 Shooting into Inhabited Dwellings? Maybe you want to see where and when the 2246 Subject Stops occurred. It’s simple with SpatialKey.
Looking for easy-to-use location intelligence from your own data? Get started with our free trial, and start visualizing your data in minutes without installing any software.
Notes
The images and reports in this post were created with publicly accessible data. Check out Sacramento’s dispatch page to see their notes about what data is included. We omitted data without address location in our SpatialKey report.
We have no association with the Sacramento police department (but we’d love to, so contact us if you’re from the Sacramento PD and want to use SpatialKey). SpatialKey does have specific features designed for Law Enforcement.
Posted by Tom Link in Computer Aided Dispatch, Law Enforcement, Sacramento, data import, examples, mapping, solutions, visualization with no comments
20 October 2009
Cities are opening up and providing access to data as part of an initiative to improve the accessibility, transparency, and accountability of City governments. Several cities, including New York City, Washington DC and San Francisco, are among a few to lead this initiative in an effort to serve the public by creating “data mines” of public information. The driving factor behind this initiative is the Government 2.0 work being spearheaded by the White House and President Barack Obama’s mandate that government data must be made available for public consumption on the Internet.
With the abundance of this raw data new challenges arise. How do cities display the information in meaningful ways without complex and costly software? This data is typically shared in the format of CSV (comma separated value ), spreadsheet or XML files containing many thousands of rows. Extracting meaning from the data can be a daunting task requiring multiple pivot tables, graphs, and filters along with the expertise in doing so. And assuming you are able to get this far, you will still be left without an easy solution in which to share this data with others.
How do you expose the location based information within the data? It is possible take a handful of the items in the spreadsheet and plot them in a web based mapping solution but most web based maps fall short in their ability to plot thousands of points in a meaningful way.
With SpatialKey you can take nearly any of these data feeds and transform them into an interactive report in minutes. You don’t need to be a specialist to create and share time- and location-based analyses.
To demonstrate the power and flexibility of SpatialKey an example from the New York Department of Sanitation containing graffiti locations is shown below. You can find this data in the NYC Data Mine by searching for the keyword “graffiti”. This dataset contains requests to clean graffiti (other than bridges or highways) received from the public in the last 12 months. They include location information, open and closed dates, and details about the community. A small snapshot of this data is shown below
Figure 1.0 - Sample of graffiti data from the NYC dataset
It is important to note that SpatialKey was not developed for this specific data and no programming was required to build the reports. It is as simple as exporting a CSV from excel and importing the data into SpatialKey. SpatialKey inspects the data during the import process and detects the data types (text, numbers and dates) and builds a custom user interface tailored to the data structure from the spreadsheet. SpatialKey also handles the geocoding as long as you have address information or X/Y in the data. The import process can be performed with thousands of rows in just a few minutes.
After importing the data a full screen map report is opened as shown in Figure 2.0. The report contains a timeline that highlights the trends of open graffiti reports over the last twelve months and the map highlights hot spots for reported graffiti locations. You can instantly identify these trends and hotspots quickly in SpatialKey then start to drill down to identify additional trends with the filtering tools.
Figure 2.0 - A map and timeline of reported graffiti
In Figure 2.1 a categorical pod for the “status” field in our data is opened and the data is aggregated by the unique statuses in that field. By clicking on the “Closed” status you can filter out all closed incidents and the map reflects only open and pending incidents. In addition you can switch the timeline to show unfiltered data to see the trend of open/pending vs closed incidents. Within the stacked bar chart the open incidents are displayed with the filled area and the closed incidents are shown in the unfilled area.
Figure 2.1 - Displaying the trend of open versus closed reports over time
A custom interface to display and filter data can be built in seconds with no programming or development needed. In Figure 3.0 four categorical pods have been added from different fields available in the graffiti dataset these pods can be used for both display and filtering.
Figure 3.0 - Adding pods for several fields from the graffiti dataset, pods can be used for display and filtering
Here are a few other examples highlighting the power when you combine city data with SpatialKey.
Spreadsheets come to life and provide new meaning with just a few simple steps in SpatialKey. Try it out yourself with our 30 day trial.
Posted by Brandon Purcell in NYC Data, data import, mapping with no comments
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